Lead author:

Valério D. Pillar, UFRGS, Brazil

Project outline:

Identifying the relationships between diversity and stability is relevant for the adaptation to climate change. Are plant communities with higher diversity more stable under the impact of climatic anomalies?  Here we propose to evaluate the effects of functional diversity and functional redundancy on the stability (resistance and resilience) of primary productivity, estimated by remote sensing proxies (e.g., NDVI), during and immediately after precipitation anomalies worldwide. For this, the sPlot database will be sampled in order to select plots that (1) could be spatially and temporally aggregated locally in order to compose larger units with a size compatible with the resolution and time window of the remote sensing product (e.g. MODIS started on year 2000), (2) for which core plant trait data is available at the TRY database for a reasonable proportion of the species found at the plots, and (3) for which precipitation data obtained from remote sensing (TRMM) is available (0-60º N-S). For each aggregated unit (set of plots in a given site), we will compile precipitation data obtained by satellite (TRMM) and identify periods (growing seasons) with negative and positive precipitation anomalies compared to climatic normals (1981- 2010). Aggregated units whose vegetation was described during an anomalous period, or without any identified precipitation anomaly posterior to the vegetation description will be discarded. For the remaining aggregated units, we will compile remote sensing indexes to be used as proxy for primary productivity (e.g., MODIS NDVI and EVI) and with these indexes we will compute, for each aggregated unit, baseline values considering only neutral periods (outside precipitation anomalies). For each aggregated unit, we will select the closest anomalous precipitation period posterior to the vegetation survey, for which we will compute resistance and resilience[1], and percentage change (positive or negative)[2] for the primary productivity proxies. Also, for each aggregated unit we will compute community-weighted means (CWM), functional diversity (Rao entropy), and functional redundancy (difference between Gini–Simpson index of species diversity and Rao entropy) using plant traits from TRY (gap filled data). The links between CWM, diversity, redundancy and stability (resistance and resilience) will be examined by means of path analysis and linear models, across all biome types or for each biome type separately.

[1] Isbell, F. et al. (2015) Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature, 526, 574–577.

[2] Fischer, F.M. et al. (2016) Plant species richness and functional traits affect community stability after a flood event. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 371.

Lead author:

Javier Loidi (Basque Country University, Spain) and Robert K Peet (University of North Carolina, USA)

Project outline:

Deciduous broadleaved summer-green forests are dominant in three regions of the Northern Hemisphere: Eastern Asia, Western and Central Europe, and Eastern North America. The dominant climate of these three regions is temperate, and these forests seem to be a clear adaptive response to cold winters and warm and wet summers. These three regions also share a common ancient history until they were separated in the Tertiary. After they split, each region experienced a common pattern of climatic changes, but with unique tectonic episodes and orographic circumstances. These specific histories were responsible for some known biodiversity patterns that exist today such as the difference in tree species richness among the three regions. Our primary aim is to do a global synthesis of the biodiversity of the herbaceous floras of the three regions. Most papers dealing with the global diversity of temperate forests have focused on tree floras, while fewer articles have examined the herbaceous understory. The distribution and diversity patterns of the understory are, nonetheless, strongly related to the glacial refugia that existed during the cold periods in Europe and North America. By doing a comparative analysis of the floristic and functional diversity of the understories of the three regions, we expect to gain insight into the historical and macroclimatic drivers of biodiversity. Our secondary aim is to incorporate into the study plant traits related to the seed regeneration niche. Seed traits are of high importance in the processes of plant community assembly and movement, but they have been rarely incorporated into vegetation studies because they are under-represented in database compilations. The advantage of focusing studies on temperate forests is that there is a relatively high number of seed  biology studies at the species level, at least for European and North American forest species. There is also a potential number of references to be found in Russian and Japanese sources. Therefore, temperate woodlands offer a good opportunity to conduct a first global synthesis of seed traits at the community level, and possibly link these to community change during periods of climate change.

Lead author:

Franziska Schrodt, University of Nottingham, UK

Project outline:

Fresh waters are especially important ecosystems due to them hosting relatively larger proportion of biodiversity compared to terrestrial systems and being a source for essential but threatened ecosystem services, such as provision of drinking water and climate change mitigation (Vörösmarty et al. 2010). However, aquatic macrophytes have shown inconsistent patterns in relation to many climate-derived biogeographical and ecological gradients (e.g. Kindleman et al. 2007, Alahuhta 2015) and to date no large scale (“global”) database of aquatic macrophyte distributions exists. 

This project aims to combine the extensive database assembled by Alahuhta et al. (globally 19 regions with data from 29 to 2000 lakes) with data on aquatic macrophytes from sPlot and traits from TRY in order to analyse global patterns in taxonomic, phylogenetic and functional diversity and their interrelationships with environmental variables (including climatic data as well as soils and remotely sensed vegetation indices (using Sentinel 2 data where available), indices of water quality e.g. from the USGS) and spatial variables (based on Moran’s eigenvector maps). Our purpose is to compare patterns in different diversity measures and related ecological gradients found among different study regions. 

We further aim to assess potential differences between native and invasive aquatic macrophyte – ecological relationships making use of the GloNAF database on global naturalized alien floras. Our object is to study whether native macrophyte species respond differently than invasive species to ecological gradients. Specifically, we hope to find out if dispersal contributes more strongly to distribution of invasive than native species.  Our study will combine community and species level data to address these fundamental macroecological study questions in a notoriously understudied biological group, namely aquatic macrophytes.

Lead author:

Borja Jiménez-Alfaro, iDiv - Martin Luther University, Germany

Project outline:

Convergence is a classical ecological concept that explains the similarity in structure or function between organisms in different areas subject to similar evolutionary or environmental forces. At the community level, functional convergence or trait convergence generally refers to the similarities or dissimilarities between co-occurring species in response to community assembly processes. The interplay of species evolution and community assembly result in plant communities with different species´ relative abundances that sustain ecosystems. Functional convergence between ecosystems exists when vegetation types from distant regions show similarity in their dominant functional attributes. Functional convergence has been traditionally shown in Mediterranean ecosystems, and more recently also in temperate rainforests of Chile and New Zealand. The causes of this convergence can be primarily attributed to similar environmental constrains, but also to similarities in evolutionary history, assembly drivers, or just chance. However, despite a few well-known examples of functional convergence in plant communities, the real extent of this pattern across world biomes is unknown.

This project will use the sPlot vegetation database to test whether ecosystem convergence exists across different continents. We will use the world biomes defined by Schlultz as operational units with a consistent climatic similarity worldwide. We will look at functional similarities across continents within the same biome, assuming climatic conditions as a major driver of ecosystem convergence. We will analyze vegetation plots representing forests and grasslands as the most dominant terrestrial ecosystems. For each one of the world biomes, we will compare the Community Weighted Means calculated for each plot for different traits. Only those biomes and continents with a minimum number of samples (for example 300 plots) will be compared. Analyses will include single-trait and multi-trait variation using univariate and multivariate statistics, respectively. Convergence or divergence will be estimated as a surrogate of the similarities detected in the statistical tests across different continents. Results will show a general overview of the cases in which ecosystem convergence can be expected across different continents within each biome, for single traits and for the full trait combination.

Lead authors:

Stephan Kambach and Helge Bruelheide, Institute of Biology / Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg (MLU) and Department of Community Ecology, Helmholtz-Centre for Environmental Research Leipzig (UFZ) 

Project outline:

In the literature there are several different definitions and methods to infer the position of a species niche and, likewise, the corresponding niche breadth (i.e. the range of tolerated abiotic and biotic conditions). Geo-referenced vegetation surveys are a valuable tool to simultaneously infer the realized niche breadth for a large set of species across habitat types and ecoregions. In an ongoing project we found a high correlation between climate-envelope and species co-occurrence based niche breadth estimates for species present in the Alps Vegetation Database (Kambach, Lenoir, Bruelheide et al., under revision). We also found a considerable mismatch between niche breadth estimates derived from the Alps region and estimates that were obtained at the global extent leading us to the question “Can niche breadth estimates that are calculated from large, but restricted datasets accurately predict species global niche breadth?”We plan to introduce this study with a short review of published niche breadth estimation methods which we will then group based on their considered niche dimension (e.g. via climate envelopes, on-site measurements, species co-occurrence, etc.) and behaviour in simulated vegetation datasets.The emerging non-redundant niche breadth estimation methods will then be applied to derive niche breadth estimates for the species that comprehensively represented in the sPlot database. We plan to calculate and compare niche breadth estimates that are derived at the global but also at a regionally and ecologically restricted datasets (e.g. based on habitat types). Our aim is to explore under which circumstances niche breadth estimates that are derived from a restricted subset of the species global occurrence can yield valid estimates of species’ globally achieved niche breath.

Lead authors:

Jose M Serra-Diaz (Aarhus University, Denmark), Franziska Schrodt (University of Nottingham, UK), Jens-C. Svenning (Aarhus University, Denmark)

Project outline:

The big question that we will address is: “How will tree species diversity react to future global climate change?” Forests are among the most important ecosystems on Earth, harboring a substantial proportion of biodiversity and providing vital ecosystem services such as carbon sequestration, climate regulation, erosion protection, and timber and non-timber forest products. The diversity of tree species plays a central role in forest ecosystems and for the subsistence of millions of people in rural communities world-wide. Part of the challenge in understanding drivers of tree diversity is that we do not have a complete picture of the current tree distribution and diversity of tree species worldwide.

To improve our understanding of global tree distributions, we will apply advanced SDM-based approaches with thorough handling of spatial autocorrelation, pseudo-absences and model complexity to the ca. 65,000 identified tree species globally. For those species with very few records, we will complement the use of SDMs with functional traits and phylogeny to provide insights on species range responses to climate. Specifically, we will use gap filled trait data to understand climatic responses for rare species – where there are too few records to implement the SDM approach with confidence. In an additional step, this will potentially allow estimating climatic-response functions which will then be projected under different climate change scenarios and evaluate shifts in tree diversity under climate change. 

Lead authors:

Gwendolyn Peyre (University of the Andes, Colombia)

Project outline:

This project is part of the “mountain diversity” studies that are based on sPlot data and focus on different dimensions of plant diversity in the alpine regions of the world. We focus on beta diversity and specifically in understanding the spatial patterns of plant assemblages and differentiation along spatial and environmental gradients in mountain ranges across the globe. We aim at conducting a bioregionalization analysis based on vascular plants in the world’s main mountain ranges to identify bioregions and characterize them within each range, and compare the level of division between ranges. Our study area will include the northern Andes, Rocky Mountains, Alps and Himalayas, which together encompass North-South vs. East-West orientations and temperate vs. tropical features. We plan using vegetation plot data corresponding to the Alpine biome and contained in sPlot, and work with presence/absence data. We will employ three different and complementary approaches: generalized dissimilarity modelling (GDM), partitioning around medoids (PAM) and Kohonen self-organising map (SOM), to carry out the bioregionalization analysis so we can test their efficiency on different datasets, and select the most significant results. All techniques rely on the concept of relationship between increasing ecological distance and observed compositional dissimilarity between vegetation plots, and all are considered adequate for vegetation data spread over large areas. 

Lead authors:

Renske E. Onstein, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Project outline:

 It is widely recognised that we are entering an extinction event on a scale approaching the past mass extinctions seen in the fossil record. This dramatic loss of biodiversity significantly affects ecosystem services valuable to human well-being. Some places on Earth are most threatened by extinctions due to their exceptionally rapid loss of habitat. These places make up the 36 biodiversity hotspots. Although flowering plants (angiosperms) with a standing diversity of ~250.000 species dominate the vegetation of biodiversity hotspots, our knowledge of angiosperm vulnerability to extinction is lacking. For example, it is well known that extinctions may be selective on functional traits - such as body size in animals, in which larger animals have higher threat of extinction. However, for angiosperms these functional predictors of extinction, or conversely, traits that promote resilience to global change, are unknown. Here, we present a framework to identify traits predictive of extinction threat in angiosperms across space (biodiversity hotspots) and time (the present as well as the geological past) to prioritise functional groups for targeted conservation. The sPlot database will provide the global phylogenetic, distributional, functional trait, that will be coupled with Red List conservation status data for all angiosperms present in the sPlot database. We will use quantitative analytical tools (e.g. structural equation modelling) and phylogenetic comparative methods to analyse these data. First, we will test for trait-driven extinctions across large temporal, spatial and taxonomic scales (i.e. which traits across the sPlots in biodiversity hotspots are associated with IUCN Red List extinction threat status? And have these traits influenced extinction rates in these angiosperms in the geological past?). Second, we aim to identify when, where and why functional traits evolved, and whether patterns of convergence are the result of similar selection pressures across biodiversity hotspots (i.e. does the distribution of functional traits across biodiversity hotspots deviate from a pattern resulting from random evolution of traits on the phylogeny? And if so, is this the result of convergence or in-situ radiations?). This approach maximises our ability to make generalisations. Unravelling the generality of the traits and processes that lead to extinctions is imperative for targeted conservation of vulnerable functional groups across biodiversity hotspots, and across ecosystems more generally.

The research objectives are to:
O1. Identify which functional traits relate to extinction threat across the 36 biodiversity hotspots, and verify whether this is congruent with predicted extinction threat based on evolutionary history;
O2. Quantify the spatial distribution of vulnerable traits in hotspots to identify where (continent), when (time) and why (evolutionary selection pressure) these traits have originated during angiosperm evolution;
O3. Classify the functional groups in need of conservation priority, given their trait-driven extinction threat in hotspots

This is expected to result in at least two publications:
1. Trait-dependent extinctions across flowering plants in biodiversity hotspots;
2. Broad-scale evolutionary convergence of flowering plant traits in biodiversity hotspots.

Lead authors:

Alexander Zizka, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Project outline:

Phylogenetically derived woodiness, the repeated convergent evolution of woody growth form from herbaceous ancestors, happened hundreds of times during the history of flowering plants, but little is known about its recent geographic prevalence and its impact on evolutionary and ecological success. In this project we will combine occurrences and abundances from sPlot with a novel database on derived woody species and their phylogenetic relationships; and use Bayesian statistical modelling to (1) identify global diversity patterns of derived woody species and determine their correlation with current day climatic factors, (2) compare the environmental niche of derived woody species with their evolutionary sister lineages, and (3) test if the transition towards woodiness is coupled with other characteristic traits into a characteristic syndrome or functional type, in particular traits related to the leaf economics spectrum such as specific leaf area.

Lead authors:

Gabriel Walther, Max Planck Institute for Biogeochemistry Jena, Germany.

Project outline:

We conduct a global analysis of intraspecific trait variation (ITV) of plants to investigate their adaptive potential to changing environmental conditions. We assume that species with a higher ITV have a higher adaptive potential to environmental changes. Thus, we want to investigate (i) which traits are especially variable, (ii) which species groups (functional, phylogenetic) show a higher ITV than others and (iii) which variables (e.g. categorical traits, geographical range, abundancy, bioclimatic variables) are most suitable to explain and predict ITV.

We analyse data provided by the TRY database on 14 traits (plant height, specific leaf area, leaf dry matter content, leaf area, leaf thickness, leaf dry mass, leaf fresh mass, leaf density, leaf carbon content (dry mass), leaf phosphorus content (dry mass), leaf nitrogen content (dry mass), leaf chlorophyll content (area), stem diameter, stem specific density). We selected species with at least 25 measurements per trait. From that we calculate a robust version of the coefficient of variation (the CVrobust), which facilitates comparisons of ITV within and across species and traits, for each selected species-trait-combination.

We then compare the CVrobust across all traits to identify traits that show a higher ITV than others. To identify species groups with a higher ITV than others, we analyse the CVrobust of species grouped by categorical traits obtained via TRY (growth form, woodiness, leaf compoundness, leaf phenology, leaf type, photosynthetic pathway, phylogeny). For this, we follow a machine learning based regression approach (boosted regression trees) where the categorical traits are used as predictors to model the ITV (expressed as CVrobust) per trait.

Furthermore, we hypothesize that species with a large distribution (i.e. larger range in geographical and environmental space) show a higher ITV compared to species with a small distribution. We further assume that rare species might have a higher ITV than frequent species. Therefore we want to complement our data by information on species distribution (geographical and environmental space) and species abundance as provided by sPlot.

Lead authors:

 Zhiyao Tang, sPlot Consortium Member, Institute of Ecology, Peking University

Project outline:

Biodiversity patterns and their underlying mechanisms have long been focal topics of study for ecologists and biogeographers. However, compared with spatial variation in species richness, ß-diversity, or the dissimilarity of species composition between two or more sites has until recently received limited attention. In a previous, Kraft et al. (2011, Science) found that the global plant ß-diversity is derived from the size of species pool (or γ-diversity in their papers); however, we found that environments per se were important for regulating the elevational and latitudinal gradients of plant patterns ß-diversity in China (Tang et al., 2012, Ecography) . Both papers are limited by the data limitation, with the Kraft paper used only 197 sites across the world, while the Tang paper used only data from China (although contained much more sites). The sPlot dataset provides a unique opportunity to disentangle the influence of species pool and environment per se in regulating the elevational and latitudinal gradients of plant ß-diversity in forests. 

There are many methods to calculate ß-diversity. Here we mainly will use two approaches: 1. dissimilarity of species composition for the closely paired plots (to do this, we need to find large number of plot-pairs within limited distance); 2. If the first approach is not applicable, we can use the slope between dissimilarity of species composition and distance of any plot-pairs for each ecoregion. Both have been described in Tuomisto et al. (2010, Ecography).

Tuomisto, H. A diversity of beta diversities: straightening up a concept gone awry. Part 1. Defining beta diversity as a function of alpha and gamma diversity. Ecography 33, 2-22, doi:10.1111/j.1600-0587.2009.05880.x (2010).

Lead authors:

Zhiyao Tang, Yanpei Guo, Hongtu Zhang - Institute of Ecology, Peking University

Project outline:

Nitrogen (N) and phosphorus (P) are two elements that limit the funcitoning of ecosystems, e.g., carbon (C) sequestration, especially under future conditions of rising atmospheric CO2, N and P deposition, and global climate change. C constitutes the basic structure of plants and accounts for ca. 50% of plant biomass; N is an essential component of enzymes; and P is an essential element of nucleic acids and membrane lipids. The concentrations of N ([N]) and P ([P]) in plant  tissues are also critical in controlling other ecological processes, such as grazing, parasitism, and decomposition. Estimates of N and P concentrations and the relationships between the metabolically active N and P concentrations and photosynthetic capacity are often used to predict the future C sequestration of  ecosystems under global changes.

At the global scale, Wright et al. (2004) analyzed patterns of leaf C, N, and P stoichiometry at species level (the Wright paper). However, the species level cannot  reflect the patterns and processes at the community level, which depend on the abundance (or biomass) of different species within a community. Within a site, leaf nutrient concentrations could vary by an order of magnitude among species. Over- or under-representation of any species may cause errors when estimating ecosystemlevel features. Therefore, it is necessary to integrate abundance (or relative abundance) across a collection of species to better understand ecosystem processes. Recently, the Tang et al. (2018) (the applicant, Zhiyao Tang) has explored the large scale patterns of N and P concentrations and contents of Chinese biomes based on the community weighted mean (CWM) of all the species occurring in the communities (Tang et al., 2018, PNAS). However, both papers are restricted by the data limitation, as the Wright paper did not integrate the relative abundance (or coverage, or biomass), while the Tang paper only used data from China. The sPlot, together with TRY, provides a unique dataset to explore the community weighted mean (CWM) of the plant stoichiometry of the world.

The CWM and abundance based variance can be easily estimated based on data from the sPlot and the TRY. We will compare the CWM, variance of the N and P among biomes, ecoregions and also correlate the relationship between N and P across the world, and along the environmental gradients.

Lead authors:

Hamada E. Ali, Botany Department, Faculty of Science, Suez Canal University,

Christine Römermann, Institute of Ecology and Evolution, Friedrich-Schiller-Universität Jena,

Project outline:

Invasive species influence the economic or environmental functioning in many ecosystems worldwide, these effects maximized due to the current changes in climate and land-use. Many studies have shown that, among others, invasive species are especially successful in their new range because they are free of competition. However, whether the functional composition of the new, invaded habitat also plays a role for invasion success is less clear. To find reasons why species become successful invaders, it is important to analyse the difference between a species’ native habitat and the new habitat which it successfully invaded in terms of functional compositions. Asking such a question will help to assess the role the habitat composition of the invaded areas play in successful invasion.

The project aims at comparing the functional composition of the invaded vs. the native habitat using both above and belowground plant functional traits and how  the functional composition of the invasive vs. native communities will differ based on the functional composition of the invasive species itself. We aim to combine the distribution data from sPlot database, plant functional traits data from TRY database, and climate data (temperature and precipitation) from WorldClim Global  Climate Data (http://www.worldclim.org/bioclim) in order to detect global patterns of functional composition of native vs. invasive habitat. Global Invasive Species Database (http://issg.org/database/welcome/) will be used to define which species are invasive in each habitat. Moreover, we will use these data to forecast the future distribution of invasive species under future global change scenarios.

Lead authors:

Carlos Alberto Arnillas. University of Toronto – Scarborough

Risto Virtanen. University of Oulu. Ecology and Genetics

Marta Carboni. Department of Sciences Università Roma

Project outline:

Community assembly mechanisms are often considered to work on the whole community in similar ways: either a community is strongly affected by environmental filters (causing coexisting species to be similar) or it is affected by interspecific interactions (e.g., competition, facilitation, which might lead to greater differentiation among species) [1–4]. However, recent studies suggest that dominant and non-dominant species do not only differ in their success (or not) under local conditions, but also in the traits that allow them to survive as dominants or non-dominant species[5–7].

In addition, recent studies have shown evidence for an asymmetry in community assembly mechanisms[8–13]. For instance, dominant plants were found to be phylogenetically under-dispersed, while non-dominants were either randomly dispersed or over-dispersed. Assuming that phylogenetic relatedness is a proxy of species trait similarity [see 14 for detailed assumptions], underdispersion of dominant species suggests that environmental filtering is more important than  interspecific interactions in organizing the dominant species, while non-dominant phylogenetic patterns indicate that non-dominants are either equally affected by both mechanisms or more strongly affected by interspecific interactions[1]. The evidence for such dominance asymmetry is however local or regional [8–12], or global but constrained to herbaceous systems[13].

We aim to assess the generality of dominance asymmetry at a global scale and across multiple plant community types. Following Arnillas et al.[13], we will divide the community in at least three dominance groups using height and cover, or proxies thereof. Then, we will compare phylogenetic and trait dispersal patterns between the different groups. If the dominance asymmetry holds true across multiple community types, we expect to find the dominant group of species less  dispersed than the non-dominant plants at each site, regardless of the local conditions. We will identify trait syndromes characteristic of dominant and non-dominant species and assess their phylogenetic signature. We expect to be able to link differences in assembly mechanisms to differences in previously identified reproductive[7] and non-reproductive[15,16] syndromes characteristic of dominant and nondominant species.

Method outline:
1. Data cleaning and filtering: identification of the plots that have all the data needed to perform the analysis (cover, phylogeny, traits; ideally traits locally measured, height, and coordinates)
2. Definition of a set of operative definitions of dominance (e.g., symmetric partition by number of species, symmetric partition by cover, inflection point, inclusion or not of multiple growth forms)
3. Measure phylogenetic and trait dispersal in each dominance group and estimate the difference between them. Compare results using different definitions of dominance.
4. Test global trends in dominance asymmetry: phylogenetic signal of dominance/nondominance; existence or not of trait syndromes; are trends related to climatic or other environmental gradients.

References:
1 Webb, C.O. (2000) Exploring the phylogenetic structure of ecological communities: an example for rain forest trees. Am. Nat. 156, 145–155
2 Cadotte, M.W. and Davies, T.J. (2016) Phylogenies in ecology: a guide to concepts and methods, Princeton University Press.
3 Mayfield, M.M. and Levine, J.M. (2010) Opposing effects of competitive exclusion on the phylogenetic structure of communities. Ecol. Lett. 13, 1085–1093
4 Kraft, N.J. et al. (2008) Functional traits and niche-based tree community assembly in an Amazonian forest. Science 322, 580–582
5 Avolio, M.L. et al. (2019) Demystifying dominant species. New Phytol. 223, 1106–1126
6 Mariotte, P. (2014) Do subordinate species punch above their weight? Evidence from above- and below-ground. New Phytol. 203, 16–21
7 Vermeij, G.J. and Grosberg, R.K. (2018) Rarity and persistence. Ecol. Lett. 21, 3–8
8 Arnillas, C.A. and Cadotte, M.W. (2019) Experimental dominant plant removal results in contrasting assembly for dominant and non-dominant plants. Ecol. Lett. 22, 1233–1242
9 Lennon, J.J. et al. (2011) Are richness patterns of common and rare species equally well explained by environmental variables? Ecography 34, 529–539
10 Chai, Y. et al. (2016) Patterns of taxonomic, phylogenetic diversity during a long-term succession of forest on the Loess Plateau, China: insights into assembly process. Sci. Rep. 6, 27087
11 Norden, N. et al. (2017) Opposing mechanisms affect taxonomic convergence between tree assemblages during tropical forest succession. Ecol. Lett. 20, 1448–1458
12 Ricotta, C. et al. (2008) Common species have lower taxonomic diversity Evidence from the urban floras of Brussels and Rome. Divers. Distrib. 14, 530–537
13 Arnillas, C.A. et al. (submitted) Opposing community assembly patterns for dominant and nondominant plant species in herbaceous ecosystems globally. J. Ecol.
14 Gerhold, P. et al. (2015) Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). Funct. Ecol. 29, 600–614
15 Grime, J.P. (1974) Vegetation classification by reference to strategies. Nature 250, 26–31
16 Grubb, P. (1998) A reassessment of the strategies of plants which cope with shortages of resources. Perspect. Plant Ecol. Evol. Syst. 1, 3–31

Lead authors:

Meelis Pärtel, University of Tartu, Estonia

Project outline:

Biodiversity at any given spatial scale depends on diversity at larger scales. However, not all regional diversity is relevant for a local site; many organisms in the region simply have different habitat preferences than those available in the local site. An operational link from locally observed (alpha) diversity to larger spatial scales can be established through dark diversity: the set of species that are locally absent at the time of sampling while being both present in the region and ecologically suitable for the local study site. With dark diversity we are better equipped to understand and protect ecosystems.

Dark diversity cannot be measured but it can be estimated. A promising dark diversity estimation method is based on species co-occurrences: if we know which species typically co-occur, we can be confident that they have similar habitat requirements. As a result, we can use observed taxa to estimate occurrence likelihood for absent taxa. During the big data era, information on species co-occurrences is growing rapidly and sPlot is the largest plant co-occurrence data source. To use sPlot for dark diversity estimations globally requires algorithms to distinguish signal from noise by filtering initial data-sets according to study region, sampled scale or other parameters. Comparison with standardized sampling can help to work out ecoinformatic routines to exploit such big data sources.

In September 2018 we launched DarkDivNet (www.bit.do/DarkDivNet), a global standardized sampling network to specifically study the dark diversity of plant communities. Interested scientists all over the world can join the network. As of September 2019 we have >150 potential study areas and many of them have already been sampled.

With this project we aim to refine the methods for estimating plant dark diversity based on recorded species and co-occurrences in sPlot.  We will compare the dark diversity estimated from local sampling in DarkDivNet to the ecoinformatic co-occurrence approach in sPlot. We will explore which filters are needed to get comparable results with local sampling in DarkDivNet (e.g. subsetting sPlot according to geographical and climatic distance, community similarity etc.). We will examine how consistent are dark diversity estimations across various regions, ecosystem types and spatial scales.

Lead authors:

Keiichi Fukaya & Yasuhiro Kubota - Lab. Biodiversity & Conservation Biogeography, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan.

Project outline:

Understanding numbers of organisms and their taxonomic diversity on the planet is a fundamental issue in evolutionary biology ever since Darwin. Nonetheless, species pool properties of biodiversity remain unclear yet.  A solution to these problems is to obtain data on species abundance distribution (SAD) over a global extent that directly informs size and biodiversity of the metacommunity (i.e., species pool). However, such data is unrealistic beyond our observation ability. In this view, Fukaya et al. (2020) developed a novel hierarchical model that estimates SADs over a large geographic extent, which we call as "macroscale SADs". The model integrates spatially replicated multispecies detection-nondetection observations and information on the geographical distribution of plant species. Fukaya et al. (2020) applied the model to the vegetation dataset in the East Asian islands, Japan, and successfully estimated absolute size of communities and species abundance for 1,248 woody plants at a 10 km grid square resolution. Notably, the estimated macroscale SADs enabled us to identify fundamental macroevolutionary properties of metacommunity, such as the rate of speciation and the average lifespan of species (Ricklefs 2003), based on the unified neutral theory (UNTB; Hubbell 2001) with protracted speciation (Rosindell et al. 2010, Haegeman & Etienne 2017). Their accurate estimates are critically informative for both basic and applied field of ecology and biogeography; the proposed approach improves the identification of the species pool (γ diversity) along geographical gradients, facilitating our understanding of the origin and maintenance of biodiversity from an evolutionary perspective, the evaluation of the role of macroevolutionary processes in community assembly, and the design of the protected areas network to capture metacommunity/metapopulation structures across a large geographic extent. In this project, we apply the macro-scale SAD model to vegetation data across countries and regions in the sPlot and estimate global-scale abundance for plant species. Then, we reveal macroevolutionary parameters (speciation rate and species lifespan) related to the origin and maintenance of plant biodiversity on the planet. This analysis of global-scale SADs highlights region-specific historical diversification processes which shaped large-scale plant diversity patterns relevant to abiotic characteristics, such as paleogeography and paleoclimate.

Lead authors:

Pedro J Leitão, Remote Sensing Centre for Earth System Research, University of Leipzig

Project outline:

While satellite-borne remote sensing has already transformed our capacity to map and monitor changes in ecosystem structure and function across the planet, extending this capacity to directly detect changes in biodiversity composition has lagged well behind. Trial applications of air-borne, and small-extent space-borne, hyperspectral remote sensing have suggested that this technology holds great promise for cost-effectively mapping plant diversity patterns. However, realisation of this potential across larger spatial extents has proved elusive to date. This working group will bring together remote-sensing specialists, plant community ecologists, and biodiversity modellers to explore a new approach to achieving this vision. The group will trial the integration of satellite-borne hyperspectral data from NASA’s Hyperion mission with the extensive global compilation of field-surveyed vegetation plots held in the sPlot database, through application of a novel correlative modelling strategy focusing on direct estimation of beta patterns from hyperspectral profiles, thereby bypassing the need to identify individual plant species. While Hyperion data cover only small portions of the planet’s surface (selected 7x42km scenes) intersection with the 1.4 million plots currently held in sPlot is expected to be sufficiently extensive to test the potential of this analytical strategy. Such testing will pave the way for future application of this approach to mapping and monitoring changes in alpha and beta diversity patterns across the entire surface of the planet, once a new generation of space-borne hyperspectral sensors offering complete spatial coverage come online within the next few years (e.g. Germany’s EnMAP system).

Lead author:

Francesca Rosa, ETH Zürich - Institute of Environmental Engineering, chair of Ecological Systems Design

Project outline:

Life Cycle Assessment (LCA) allows for an environmental assessment throughout the life cycle and along the whole supply chain of services and products. Although LCA already includes impacts on ecosystem quality, the methodology can be improved to better reflect ecosystem complexity. Notably, the consensus and model recommended by the UNEP-SETAC Life Cycle Initiative quantifies the impacts on biodiversity as “potentially disappeared fraction of species”. Species-richness indicators, however, might not be enough to describe the impacts on the ecosystem and its functionality.

To address this problem, a proof of concept on how to characterize functional plant diversity in life cycle assessment has recently been developed and applied to Germany [Scherer, 2020]. The study focused on land use as the major driver of terrestrial biodiversity loss. This project aims to carry out the next step and scale up the study to the global level. To do this, global data on species composition and traits are needed for which sPlot linked to TRY provides an excellent basis.

To do the analysis, we will first use sPlot data to compute species richness and link the vegetation plot locations to land use data. Second, we select the most representative plant traits from TRY and calculate functional diversity indicators. Third, other factors that might contribute to functional diversity responses are taken into account. Finally, an interpretation of the combined results will be performed, together with an uncertainty analysis and an integration into the LCA framework.

Lead authors:

Dr Aldo Compagnoni, Martin-Luther Universität Halle-Wittenberg, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Project outline:

occur there. As a result, tropical species should be more sensitive to changes in temperature than species from temperate or polar regions. This hypothesis has been extensively tested focusing mostly on animals (Sheldon et al. 2018), and deriving the temperature tolerances of species from species physiological tolerances (Araújo et al. 2013) or their elevational range (Chan et al. 2016).

In this project, I plan to expand previous tests of Janzen’s hypothesis by i) performing a global test on plants, ii) examining the tolerance of plants to both temperature and water availability (henceforth “environmental tolerance”), iii) deriving environmental tolerances from plant distribution data, and iv) estimating the average selection of climate on plant environmental tolerances using plant community data. I propose to calculate species environmental tolerances by looking at the extremes in temperature and water availability observed where species occur. For example, if a species has a wide tolerance of water availability, it will be reflected in the extremes of water availabilities at the sites where it occurs. I will estimate these environmental tolerances combining data from the BIEN and CHELSA databases. Finally, I will quantify the average selection for environmental tolerance at each site using plant community data. For example, plant communities from the European Mediterranean coasts will be composed of species that can tolerate small range of temperatures when compared to plant communities of the Ukrainian steppe. To calculate community-weighted means, I plant to use the sPlot database. My hypotheses are that H1) the average temperature tolerance of communities will depend on the diurnal temperature range, and seasonal temperature range of each community, and H2) the average tolerance of water availability conditions will correlate with the mean water
availability of each community.

My proposed research shares a few aspects with two existing sPlot project: number 24, and 27 (https://www.idiv.de/en/sdiv/working_groups/wg_pool/splot/projects.html) Project 24 focuses on quantifying the niche breadth of the genus Fagus. In the second case, project 27 (Sporbert et al. 2020) tests the abundant center hypothesis by combining European species abundance data, with the distance of species from their climatic optimum. My project, despite sharing some methodological details with these two projects, addresses scientifically different question.

NOTE: this project is conditional on the securement of sufficient Third-Party funding

Lead authors:

Mohamed Zakaria Hatim - Wageningen University, Plant Ecology and Nature Conservation Group - Environmental Sciences Department; Tanta University, Botany and Microbiology Department - Faculty of Science

Project outline:

The Saharo-Arabian region is one of the biggest desert regions in the world. Many studies on the vegetation of the countries of this region have been done. Yet those studies did not give account of the whole region and were local (e.g., (Shaw & Hutchinson, 1934), (Quéney, 1935), (Quézel, 1965), (Bendali et al., 1990), (Ozenda, 1991), (Boulos, 2008), and (Saaed et al., 2019)). The notable attempt to study a big part of the region was made by Zohary (1973). Although his study was quite extensive, it can hardly coincide with the widely recognized international code of phytosociological nomenclature, which means that most of Zohary’s outcomes can be considered nomina nuda (Weber et al., 2000). In this research, we aim at answering these questions: (i) Is it possible to make a convincing classification of the region vegetation based on the collected data from literature and available databases? (ii) Can this research help in understanding the biodiversity of the study region? (iii) Can this study help in fighting desertification and climate changes effects?

Nowadays, A wealth of data has been compiled, covering information about the Saharo-Arabian region vegetation. The potential of this data has not yet been explored beyond the primary interpretation. We will collect all available data from literature, large databases (e.g., sPlot (Bruelheide et al., 2019) and African Plant Database), and datasets provided by the international collaborators to build a central database representing the whole region. We will analyse the collected data at Plant Ecology and Nature Conservation group, Environmental Sciences Department, Wageningen University, The Netherlands. The international collaborators will be consulted and involved in the data interpretation and editing of the resulted article.

References:
Bendali, F., Floret, C., Le Floc’h, E., & Pontanier, R. (1990). The dynamics of vegetation and sand mobility in arid regions of Tunisia. Journal of Arid Environments, 18(1), 21-32.
Boulos, L. (2008). Flora and vegetation of the deserts of Egypt. Flora Mediterranea, 18, 341-359.
Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S. M., Chytrý, M., . . . Sandel, B. (2019). sPlot–A new tool for global vegetation analyses. Journal of Vegetation Science, 30(2), 161-186.
Hennekens, S. M., & Schaminée, J. H. (2001). TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science, 12(4), 589-591.
Ozenda, P. (1991). Flora and vegetation of the Sahara: CNRS.
Quéney, A. (1935). Note sur la végétation et la flore du Sahara et spécialement du Sahara central. Publications de la Société Linnéenne de Lyon, 4(9), 141-143.
Quézel, P. (1965). La végétation du Sahara, du Tchad à la Mauritanie.
Saaed, M. W., El-Barasi, Y. M., & Rahil, R. O. (2019). Our present knowledge about the history and composition of the vegetation and flora of Libya. Webbia, 74(2), 325-338.
Shaw, W., & Hutchinson, J. (1934). The flora of the Libyan desert. Kew Bull, 7, 281.
Weber, H. E., Moravec, J., & Theurillat, J. P. (2000). International code of phytosociological nomenclature. Journal of Vegetation Science, 11(5), 739-768.
Zohary, M. (1973). Geobotanical foundations of the Middle East (Vol. 2): Gustav Fisher Verlag, Stuttgart.

Lead author:

Benton Taylor, Assistant Professor, Harvard University

Project outline:

Nitrogen is an essential limiting nutrient crucial for plant growth. Biological nitrogen fixation (BNF) is the primary process through which atmospheric nitrogen is converted to its biologically-available form. Some nitrogen-fixing bacteria are free-living in soil, while others can form symbiosis with plants and lichen of various growth forms (i.e., lichen, moss, herbaceous plants, shrubs, and trees). Biological nitrogen fixation can be a crucial, if not dominant, input of nitrogen wherever nitrogen-fixers are abundant. However, despite the recognized importance of BNF, we lack a comprehensive understanding of the global patterns of nitrogen-fixer abundances and the mechanisms underlying these abundance patterns. Why do nitrogen fixers not become sufficiently abundant to relieve nitrogen limitation at high latitudes? What drives the general shift from tree to shrub to moss/lichen nitrogen fixation as one moves from the equator toward the poles? We aim to utilize sPlot’s global vegetation database to establish the global distribution patterns of multiple growth forms of nitrogen-fixers and how these abundances change across varied biomes. We are interested in both the absolute abundance of nitrogen fixers, critical for understanding ecosystem-level nitrogen inputs, and the relative abundance of nitrogen fixers, critical for answering fundamental questions on the competition between nitrogen fixers and comparable non-fixing organisms. We then seek to use state-of-the-art statistical modeling to evaluate how climate factors and functional traits together drive nitrogen-fixer distribution patterns. Previous efforts to understand broad patterns of nitrogen-fixer abundances have focused either on specific regions (e.g. North America) or specific nitrogen-fixer growth forms (e.g. nitrogen-fixing trees) and have failed to fully uncover the mechanisms driving these abundance patterns. Our proposed research will, for the first time, provide a global map of nitrogen-fixer distributions of various growth forms (lichen, moss, herbs, shrubs, and trees) and elucidate the ecological drivers of these patterns. This novel understanding will make important contributions to the development of mechanistic theory on the regulation of nitrogen inputs and global patterns of nitrogen limitation.

Lead author:

Matthias Grenié, German Centre for Integrative Biodversity Research (iDiv), Leipzig University

Project outline:

The biotic resistance hypothesis formulated that more species rich ecosystems are less prone to invasions. Following this hypothesis, communities with more species occupy larger niche space (which would translate as a larger occupation of the functional space), which should make establishment and resource competition more difficult than for communities with fewer species. Thus, a community showing a great native species functional diversity should show probably host less alien species and/or with lower functional diversity and/or in a distinct portion of the functional space. While these patterns have been widely evaluated in the temperate region, few studies tested this hypothesis in the tropics, the most species-rich ecosystems on Earth, for which an “own” sub-hypothesis exists, the Tropical Invasion Hypothesis

We here propose to test this hypothesis in the Tropics at a global-scale and to test the classical formulation of the hypothesis using species richness but add a functional perspective to this hypothesis. Indeed the relationship between the functional diversity of native and alien species with focus on Tropics using plot data are almost missing. All in all we have very little knowledge about mechanisms and resulting detailed patterns of plant invasions in the Tropics.

To this end we will use the sPlot plot data in the Tropics and the GloNAF database (www.glonaf.org; van Kleunen et al 2019)to get a list of non-native species in each plot. We would use the TRY gap-filled trait data to analyse patterns of different aspects (richness, divergence, regularity) of functional diversity of both native and non-native species in each plot. To control for differences in environmental conditions we will use CHELSA Bioclim variables as well as SoilGrid variables. To control for difference in human interactions that influence the amount of alien species in a given plot we will use the Human Influence Index map which aggregates in a single layer human impact through population density, proximity to roads, landscape naturalness, etc.

Reference:
van Kleunen, M., Pyšek, P., Dawson, W., Essl, F., Kreft, H., Pergl, J., Weigelt, P., Stein, A., Dullinger, S., Konig, C., Lenzner, B., Maurel, N., Moser, D., Seebens, H., Kartesz, J., Nishino, M., Aleksanyan, A., Ansong, M., Antonova, L.A., Barcelona, J.F., Breckle, S.W., Brundu, G., Cabezas, F.J., Cardenas, D., Cardenas-Toro, J., Castano, N., Chacon, E., Chatelain, C., Conn, B., de Sa Dechoum, M., Dufour-Dror, J.M., Ebel, A.L., Figueiredo, E., Fragman-Sapir, O., Fuentes, N., Groom, Q.J., Henderson, L., Inderjit, Jogan, N., Krestov, P., Kupriyanov, A., Masciadri, S., Meerman, J., Morozova, O., Nickrent, D., Nowak, A., Patzelt, A., Pelser, P.B., Shu, W.S., Thomas, J., Uludag, A., Velayos, M., Verkhosina, A., Villasenor, J.L., Weber, E., Wieringa, J.J., Yazlik, A., Zeddam, A., Zykova, E. & Winter, M. (2019) The Global Naturalized Alien Flora (GloNAF) database. Ecology, 100, e02542.

Lead author:

Eric Garnier, CNRS, Centre d’Ecologie Fonctionnelle et Evolutive (UMR 5175), Montpellier Cedex 5, France

Project outline:

Pollen is a powerful proxy to reconstruct both vegetation and climate variation throughout time. Among other micro-fossil studies, pollen is one of the most accurate proxy due to the stronger modelling method used to reconstruct paleoclimate and paleoenvironment: transfer function for climate (Chevalier et al. 2020) and biomization (Prentice et al. 1996; Harrison et al. 2010) for biome reconstructions. In both cases, the relation between pollen and environmental forcing relies on uniformitarianism assumption: the pollen response to vegetation/climate is the same today as in the past (Jackson et Williams 2004). That is why the studies on modern analogues is necessary. Especially, the main problem is due to the difference between pollen and plant taxa, as pollen is not  always identifiable at the species level.
Arid biomes such as desert, steppes and shrublands need a special focus to better understand the mechanism controlling their distribution through space and time (Lu et al. 2018), in particular because a spreading of these biomes is expected in the future (Huang et al. 2016; Park et al. 2018). In the Arid Central Asia (ACA, area covering the dry continental Asia from Iran to Mongolia), the pollen calibration work is necessary (Tian et al. 2014). Indeed, a wide diversity of open lands exist in ACA and is controlled by very low annual precipitation. A number of other, still unknown, bioclimatic parameters control this biome and ecotone diversity. Especially in the past, modelling the spatial variation between cold steppes and warm steppes is a complex task(Tarasov et al. 1998).
The paleo pollen signal recorded in peat or lake sediment is commonly used as predictor for past vegetation reconstruction. In the present, a calibration study between surface pollen and surrounding vegetation is necessary to quantify the biases recorded by the pollen signal. The sPlot database will allow us to test whether surface pollen samples can be used as a proxy of extant vegetation by comparing vegetation plots and pollen fractional abundances at the ACA scale. The blue dots on Figure 1 shows the pollen surface samples available in ACA. We require vegetation plot from the same area to estimate the average biases in the pollen rain in ACA. Especially, the aim of this project is to better constraint the link between pollen rain and vegetation/climate in arid area using the powerful tool of trait-based ecology. We will calculate the community-weighted means (CWM) of traits (Garnier et al. 2004) applied on vegetation plot and on modern pollen rain and compare them to assess the reliability of pollen as past trait records. After that, we will try to improve the plant functional type (PFT) classification used in vegetation reconstruction (Harrison et al. 2010) and apply it on past pollen records to understand which trait variation drove the vegetation shift throughout time in Lake Ayrag (Mongolia).

References:

Chevalier, Manuel, Basil A.S. Davis, Oliver Heiri, Heikki Seppä, Brian M. Chase, Konrad Gajewski, Terri Lacourse, et al. 2020. « Pollen-Based Climate Reconstruction Techniques for Late Quaternary Studies ». Earth-Science Reviews 210 (novembre): 103384. doi.org/10.1016/j.earscirev.2020.103384.
Garnier, Eric, Jacques Cortez, Georges Billès, Marie-Laure Navas, Catherine Roumet, Max Debussche, Gérard Laurent, et al. 2004. « PLANT FUNCTIONAL MARKERS CAPTURE ECOSYSTEM PROPERTIES DURING SECONDARY SUCCESSION ». Ecology 85 (9): 2630-37. doi.org/10.1890/03-0799.
Harrison, Sandy P., I. Colin Prentice, Doris Barboni, Karen E. Kohfeld, Jian Ni, et Jean-Pierre Sutra. 2010. « Ecophysiological and bioclimatic foundations for a global plant functional classification ». Journal of vegetation Science 21 (2): 300-317. doi.org/10.1111/j.1654-1103.2009.01144.x.
Huang, Jianping, Haipeng Yu, Xiaodan Guan, Guoyin Wang, et Ruixia Guo. 2016. « Accelerated dryland expansion under climate change ». Nature Climate Change 6 (2): 166-71. doi.org/10/gbn62d.
Jackson, Stephen T., et John W. Williams. 2004. « Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? » Annual Review of Earth and Planetary Sciences 32. doi.org/10/fwjqs3.
Lu, Kai-Qing, Gan Xie, Min Li, Jin-Feng Li, Anjali Trivedi, David K. Ferguson, Yi-Feng Yao, et Yu-Fei Wang. 2018. « Pollen spectrum, a cornerstone for tracing the evolution of the eastern central Asian desert ». Quaternary Science Reviews 186: 111-22. doi.org/10/gdjvqw.
Park, Chang-Eui, Su-Jong Jeong, Manoj Joshi, Timothy J. Osborn, Chang-Hoi Ho, Shilong Piao, Deliang Chen, Junguo Liu, Hong Yang, et Hoonyoung Park. 2018. « Keeping global warming within 1.5° C constrains emergence of aridification ». Nature Climate Change 8 (1): 70.

Lead author:

Qiong Cai  & Zhiyao Tang - Institute of Ecology, College of Urban and Environmental Sciences, Peking University (PKU)

Project outline:

Global patterns of local species diversity are believed to be affected by both regional (e.g., diversification, extinction and dispersal) and local (e.g., adaptions to local environments and biotic interactions) processes. Nonetheless, their relative importance remains elusive. In addition, the unique historical and biogeographic features of different regions could influence regional processes, which in turn affect local species diversity. Fagus-dominated forests, one of the most representative temperate forests in the Northern Hemisphere, are disjointedly distributed in three continents, providing an ideal system to study the relative importance of regional and local processes on local species diversity patterns.

There are different methods to test the relative roles of regional and local effects on local species richness. One widely accepted method is to examine the relationship between regional and local species richness. Another method is to directly disentangle the relative importance of biogeographic region, contemporary climate and other regional or local factors, by methods such as generalized linear models, stepwise regression and random forest analyses.

Combining a database of Fagus plots in China by extensive field surveys with that in sPlot, it is possible to get one of the largest datasets of beech forests ever assembled. Furtherly, with the regional species pool information and climate data accordingly, we could explore the global pattern of local species diversity of beech forests as well as the relative roles of regional and local effects on it.

Lead author:

Maria Laura Tolmos & Holger Kreft - Biodiversity, macroecology and biogeography, University of Göttingen, Germany

Project outline:

Assessing how multiple facets of tree diversity (i.e. taxonomic, phylogenetic, and functional) vary with elevation at multiple spatial scales may provide new insights into the ecological and evolutionary processes influencing biogeographical patterns throughout the world. In this study, we will evaluate how tree taxonomic, phylogenetic, and functional diversity at local to landscape scales across the world respond to changes in elevation. Specifically, we will test whether changes in biodiversity with elevation are a result of one or multiple factors (e.g. temperature, precipitation, evapotranspiration, anthropogenic influence, elevation span), as well as looking into specific tree diversity patterns in different biogeographical regions. Further, we will analyze the evolutionary relationships of tree species with their regional floras and the entire global floras, while evaluating whether tree species in higher elevations are a subset of the ones in lower elevations of the same gradient. Additionally, we will test if changes in phylogenetic diversity with elevation are consistent with recognized evolutionary hypotheses: Tropical Niche Conservatism (TNC) or Out of The Tropics hypothesis (OTT). For this purpose, we will use a big tree plot dataset from mountainous regions worldwide to quantify alpha and gamma scales using alternative taxonomic, phylogenetic, and functional diversity indices. Using species lists from different regions across the globe we will quantify phylogenetic  relatedness within and across elevations, and modelling tools will allow us to evaluate how multiple facets of diversity are influenced by different factors throughout elevations.

Lead author:

Léonard El-Hokayem, Martin Luther University Halle-Wittenberg, yDiv

Christopher Conrad, Martin-Luther University Halle-Wittenberg, iDiv

Project outline:

Groundwater resources are biodiversity hotspots, and provide crucial ecosystems services. Yet, groundwater dependent ecosystems (GDE) are exposed to several anthropogenic threats, including climate change. Tackling these threats requires improving the on-the-ground identification of GDE at the global scale. In order to close critical gaps in current global GDE monitoring capacity, we will use existing vegetation databases and tap the potentials of remote sensing together with the ever-emerging variety of global datasets from different disciplines to map GDEs at the global scale and assess threats to these local hotspots of biodiversity. The project will focus on the development of a novel combined vegetation related and hydrological ecosystem-based concept to map, analyze and evaluate GDEs at the global scale by means of mixed multiscale and multi-instrument methods. The approach will include a novel designed methodology to identify those ecosystems reliant on resident groundwater (terrestrial vegetation) based on remote sensing analyses. For the biome-wise detection of groundwater dependent ecosystems (GDEs) in three biomes (temperate broadleaf & mixed forests, Mediterranean forests, woodlands & scrub, tropical & subtropical grasslands, savannas & shrublands) and assessments of threats, machine learning methods will integrate remote sensing and global geodata in the fields of climatology, hydrology, hydrogeology, geomorphology, vegetation geography, and land and water use. First exploration and further proof of concept, global validation and optimization will strongly rely on the occurrence of phreatophytes (species or genus level) available from vegetation databases (sPlot, the global vegetation plot database). Regional validation will focus on existing GDE maps, while local validation will rely on botanical field mapping in defined study areas. After creation of a harmonized global up-to-date map for GDEs, threatened systems to model hotspots for potential changes in plant diversity will be pinpointed.

Lead author:

Dario Ciaramella, Italy

Project outline:

Coniferous forests are distributed all over the world within several ecoregions. Despite being considered as a monotonous formation of homogeneous physiognomy and floristic composition, they are complex mosaics of different plant communities with a wide range of climatic and topographic conditions, as well as with an old biogeographic history. It has been hypothesized that all the present-day coniferous forests of the Northern Hemisphere are derived from the Arcto-Tertiary Geoflora and were later modified and splitted in many isolated occurrences by continental cooling and drying trends, mountain uplifting, and glaciation during and after the LGM. In contrast, the coniferous forests of the Southern Hemisphere are characterised by substantially different floristic affinities with those of Paleartic and Nearctic latitudes, and are derived from a Gondwana flora. The fact that most of the genera and closely related species are common to a number of fragmented areas suggests a common history of evolution of these forests. For instance, the floristic core of temperate high-montane coniferous forests shows strong similarities to boreal forests, at least in the lower strata with mosses and lichens almost all cosmopolitan. Recent studies pointed out the importance of the evolutionary and glacial-postglacial history of the known spatial patterns of forest species richness at the global scale, beyond climatic, edaphic and topographic drivers. At the same time, both ecology and history might be imprinted on the distribution of life forms in different regions, but relevant information is still unsatisfactory.

With the data provided by sPlot, we intend to examine the complete vascular plant communities of these forests, which will be deconstructed in different layers and life-forms, to shed light on the past events which affected the extant forest composition. We will use variables characterising the current climate, LGM climate, elevation and terrain ruggedness. After delimiting discrete geographic regions encompassing the variability of these forests, we will try to find informative (dis-)similarities between these areas. Specifically, we will ask the following questions:
i) Do life-forms and forest layers respond similarly to environmental factors at the global scale? What are the relative effects of historical and current climate on the life-form composition of these forests?
ii) Is distribution of the tree, shrub and floor layers species richness similar in the defined discrete regions? For instance, the low richness of tree species in the European nemoral areas is attributed to their severe elimination during Quaternary glacial periods. Do the other forest components show similar patterns?
iii) How are the affinities between the understory and tree floras in terms of taxonomy and phylogeny? Can we expect these similarities to be high to detect a common history along the Tertiary for both groups of plants?

To answer these questions, after data filtering, stratification and resampling, we will employ generalized linear mixed models (GLMMs) and redundancy analysis (RDA) with variance partitioning to predict the effects of environmental variables on species richness and the variation in life forms along abiotic gradients, respectively. We will calculate the turnover component of spatial taxonomic (TBDturn) and phylogenetic (PBDturn) beta-diversity following Simpson's index of dissimilarity to explore the relationships between the biotic dissimilarities and the environmental drivers at each taxonomic rank of each layer group, and compare them among regions.

Lead author:

Francesco Sabatini, University of Bologna, Italy

Project outline:

Land-use change and intensification are among the most important drivers of the biodiversity crisis. Most studies testing for the effect of land-use intensity on plant biodiversity, however, either focussed on gamma diversity only, therefore neglecting the role of compositional turnover, or were limited to small spatial extents. Here, we aim at disentangling the regional effect of land-use change on plant species composition across ecoregions. Specifically, we will 1) model how changes in land-use and land-use intensity affect the spatial distribution of plant species composition over a 25-year period, 2) calculate the proportion of plant species committed to extinction as an effect of changes in land use, and 3) identify hotspots where an increase in land-use intensity is likely to induce a higher than average number of species to go extinct.
Based on a selection of well-sampled ecoregions in sPlot 3.0, we will calibrate ecoregion-specific Generalized Dissimilarity Models (GDMs) linking between-plot compositional dissimilarity to geographical distances, ecological dissimilarities, and differences in land use. To account for the lack of time-series data in sPlot 3.0, vegetation plots will be paired to the closest date for which environmental (e.g., climatic) and land-use predictors are available, so to fit time-invariant GDMs. Fitted GDMs will then be used to predict the compositional dissimilarity within each ecoregion and create wall-to-wall maps of species composition in year 1990 and 2015. By comparing predictions at these two times, we will highlight areas where change in land use and land-use intensity are expected to induce changes in species composition, and quantify the proportion of species committed to extinction with an approach based on species area curves.

We expect that land use significantly impacted the composition of plant communities over the last 25 years, but the variation across ecoregions is probably wide, with higher proportions of plant biodiversity committed to extinction in deforestation frontiers in the tropics and subtropics, i.e., areas with high rates of agricultural expansion and intensification. In developed countries, instead, where forest transition occurred before 1990, we expect that the increasing trends in land-use intensity will be, at least partially, counteracted by a positive effect of land abandonment and tree cover expansion.

Lead author:

Agathe Toumoulin, Masaryk University, Czech Republic

Project outline:

Fossil leaf traits are commonly used to reconstruct paleoclimate and compare fossil localities. Several uni- and multivariate methods exist, based on classic functional traits (e.g. leaf area and leaf mass per area) but that also consider other characters for some of which an empirical relationship with climate/environment was sometimes evidenced but the function for the individual remains debated or unknown (e.g., type of margins, length to width ratio, leaf base and apex forms). The most known method is the Climate Analysis Multivariate Program (CLAMP) which considers 36 leaf characters and provides 11 paleoclimate estimates (e.g., mean annual temperatures, precipitations of the three driest months, length of the growing season), using canonical correspondence analysis and its own modern trait-climate datasets. However, few of the response traits used in today’s vegetation studies are visible on fossil leaves and it is not certain that all visible characters are functional traits. Recently, Traiser et al. (2018) created a database dedicated to fossil leaf traits, Morphyll. It currently provides measurements for 22 paleofloras of different European (mostly German) localities and Paleocene to Miocene in age (i.e., spanning the last 60 to 20 million years) with trait measurements for ~ 6000 leaves. Some of the traits present in this database are also present in TRY (i.e., leaf area, SLA (LMA may be calculated from fossils), leaf margin type, leaf shape, lamina length and width), which make comparison to extant vegetation possible.
The combination of TRY, sPlot and Morphyll data provides us with the opportunity to describe the distribution of some of the traits visible on fossils within extant bioclimatic zones, to investigate their possible sensitivity to environmental parameters and create a new framework for analysis of deep-time environments.
The project will follow these steps: (1) modern and fossil trait data will be cleaned and homogenized to be comparable. Within each fossil assemblage, trait mean values will be calculated per taxa (nb: we may not use Community Weighted Mean because the abundance of taxa in the fossil assemblage is not the same as that of the community at the time). (2) sPlot will be used to create a functional classification of vegetation units based on similar distributions of the considered traits (i.e., those visible on the fossils, cluster analysis). (3) fossil assemblages will be associated with modern functional analogue classes (using similarity techniques), from which environmental and climate parameters (e.g., temperatures, precipitations, soil characteristics) will be extracted. Finally, (4) the results obtained with this new approach will be compared to previous paleoecological analysis made on these floras (e.g., including CLAMP results and analyses based on the taxonomic composition of the assemblages).

Lead author:

Georg Hähn, Martin-Luther University, Germany

Project outline:

Exploring the distribution of traits (e.g. functional diversity) across plant communities is a well-known technique to infer resource partitioning and assembly rules. Unfortunately, the explanatory power of functional diversity depends on the choice traits and availability of species information. Some traits remain to be hardly measurable, but strongly linked to a species’ evolutions, e.g. metabolic characteristics that confer herbivore and pathogen resistance. Simultaneously accounting for the functional and evolutionary differences among plant species in a community (e.g. phylogenetic diversity) could become a complete and leading tool to understand ecosystem functioning and plant community assemblage at a global scale. Previous studies of phylogenetic and functional diversity are either limited by species level or scale. While the correlation of phylogenetic and functional diversity remains unclear, patterns of stable climate conditions and trait diversity have been explored in many studies. These studies have proposed different theories to explain how stable climate conditions affect coexistence mechanisms due functional characteristic (traits). At local scales (small grain sizes, i.e. at the vegetation-plot level), where competition play a major role, climatic events can promote diversity through temporal niche partitioning: species that differ in their functional characteristics (traits) will be favoured at different periods of time, leading to increased trait diversity within communities. Long-term climatic variability (i.e. climate change velocity) at coarse spatial scale, have been demonstrated to decrease trait variability, with long-term unstable and harsh environments having the lowest diversity of trait states ('physiological tolerance hypothesis'). We will calculate Rao`s quadratic entropy based on the distances in the phylogeny, as a proxy for phylogenetic diversity and on the distances of the traits as a proxy for functional diversity. For functional diversity we will try to use as less as possible trait values to avoid a high correlation between functional and phylogenetic diversity. Furthermore, we will use generalised additive model to show the relationship between functional and phylogenetic diversity corrected for the geographical space. The influence of climate variables on the diversity indices will be explored with boosted regression tree modelling.

Lead author:

Helge Bruelheide & Georg Hähn, Martin-Luther University, Germany

Project outline:

Phosphorus (P) is an essential macronutrient for plant growth and development. It is a key component of the photosynthetic machinery, a major constituent of phospholipids, and it plays a major role in energy transfer, cell membrane maintenance, and signal transduction. Soil represents the largest P stock in terrestrial ecosystems. The concentration of phosphorus in soils is determined by the balance between its inputs (through mineral weathering, fertilization and atmospheric deposition) and outputs (through plant uptake, leaching, and erosion). The availability of phosphorus in soils is an important factor in determining the concentration of phosphorus in plant leaves, and thus, a strong correlation between soil and leaf P concentration would be expected.

Recently, He et al. (2021) constructed a database of total P concentration of 5275 globally distributed (semi-)natural soils from 761 published studies. Soil total P concentration varied significantly across the globe and varied with parent material, soil types, biomes and continents. Using soil organic carbon concentration, parent material, topography, vegetation and climate variables, He et al. (2021) were able to predict soil total P concentrations and to produce a global map of P concentration in 0-30 cm soil depth. Soil total P concentrations are much larger on the northern than the southern hemisphere and within the northern hemisphere increased with latitude.

This pattern is similar to what Bruelheide et al. (2018) described in sPlot paper #3 for leaf phosphorus concentrations. The concentration of phosphorus in the leaves is determined by both the amount of P available in the soil and the plant's ability to uptake and utilize phosphorus from the soil. Although the dependence of leaf nitrogen to leaf phosphorus (N:P ratio) on length of the growing season was the most interesting finding in Bruelheide et al. (2018), the objectives of that publication were too broad to allow us delving deeper into the phosphorus topic. Here, we plan a follow-up paper asking (1) to which degree community-level leaf and soil P concentrations are correlated with each other globally and which further community-level plant characteristics result in deviations from the 1:1 expectation. Here, in particular the plant species mycorrhizal type, leaf N content and root traits as well as leaf longevity might play an important role. The concentration of phosphorus in the leaves is not only influenced by uptake rates but also the plant's ability to store phosphorus.

Lead author:

Matt Scowen, Bankor University, United Kingdom

Project outline:

The Intergovernmental Science-Policy Platform for Biodiversity and Ecosystem Services recognises the importance of accurate spatial assessment of ecosystem services (ES) for sustainable land management and policy decisions (IPBES, 2016)¹. However, commonly used landcover based approaches for ES spatial assessment assume the same level of ES provision for each habitat type wherever it occurs, and so poorly explain variance in ES supply leading to low model accuracy (Eigenbrod et al., 2010)². Processes by which ES are generated are not determined by landcover but by organisms, and ecological properties and processes within that landcover (Rieb et al., 2017)³. Thus, we hypothesise that biodiversity/traits present in an area may provide a better indication of the ES than the land cover alone, and so inclusion of these data in ES models has potential to 1) increase our understanding of the underlying processes, and 2) improve model accuracy. 

We use machine learning (ML) to explore the additive effect of including species and species trait diversity in ecosystem service (ES) models. We have obtained ES data for four ES (food supply, water supply, water quality and recreation) and we use these data to test, train and validate our ML models.  We hypothesis links between biodiversity and associated traits, and food supply, water supply, water quality and recreation. We test these hypotheses using ML models, determining the relative importance of one aspect of biodiversity over another when predicting ES supply, and quantifying the additive impact of including biodiversity information in addition to more traditional, land cover data.  Essentially, a model is built independently for each ES using the same workflow.  For each model the additive effect of including biodiversity variables is assessed using model accuracy and variable importance measures. Our global and continental scale crop yield models indicate that the addition of species traits improves model performance, and we hypothesise that the addition of root traits with likewise improve the performance of our global water quality model. To test this hypothesis, we propose to combine sPlot species data with the freely available global root trait database (GRooT)⁴ to map root traits to water resource zones for which we have water quality data. Species data from sPlot has recently been used to map root traits to ecoregions⁶ and we propose to follow similar mapping methods but focussed on the watersheds where we have ES data.   

Lead author:

Camille Delavaux, ETH Zürich

Project outline:

The introduction of non-native plant species is one of the largest ecological problems of our time, fundamentally altering ecosystems, ecosystem services provided to humankind, and costing tremendous resources. Although the vast majority of plant species worldwide associate with mycorrhizal fungi in mutualisms that can alter their resource uptake and competitive outcomes, with emerging work suggesting they are important in the context of invasions, the bulk of invasion research has overlooked their influence. Some mycorrhizal fungi are widespread, but others are geographically restricted, suggesting that plant species relying on these fungi may be at a disadvantage and less likely to invade if their fungal partners are not present in situ. However, in disturbed environments, mycorrhizal communities may be degraded; therefore, disturbance may create environments ideal for non-mycorrhizal plants. This broadly predicts a strategy of mutualism matching in less disturbed sites, but one of non-association in heavily disturbed sites. Therefore, considering mutualist compatibility alongside disturbance will be integral to an improved understanding of global plant invasions. Here, we propose to construct a synthesis of plant invasions globally, integrating climate, human, native diversity and mutualistic drivers. There are two main goals of this project: (1) lead a global synthesis of drivers of plant invasion occurrence and severity for vascular plant species and (2) test for the influence of mutualist compatibility between native communities and non-native species on plant invasions, while integrating land use change. We aim to tackle these goals by combining global datasets of plot level species occurrences and abundance (sPlot), environmental data (Global Environmental Composite), native status (GloNAF & Kew), mycorrhizal status (FungalRoot), and land use change (Landsat based CCDC segments) to test our hypotheses at the global scale. In doing so, this project will push the field of invasion ecology to fully consider native resident community traits, both in the plant and mycorrhizal communities, and disturbance, in determining plant invasions

Lead author:

Helge Bruelheide, Jürgen Dengler, Borja Jiménez-Alfaro, Oliver Purschke

Abstract:

Questions

Vegetation‐plot records provide information on presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level.

Location

sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected between 1885 and 2015.

Methods

We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g. biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots.

Results

We present the first maps of global patterns of community richness and community‐weighted means of key traits.

Conclusions

The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Publications:

Bruelheide, H., Dengler, J., Jiménez-Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Arfin Khan, M.A.S., Arnst, E., Attorre, F., Baraloto, C., Beckmann, M., Berg, C., Bergeron, Y., Bergmeier, E., Bjorkman, A.D., Bondareva, V., Borchardt, P., Botta-Dukát, Z., Boyle, B., Breen, A., Brisse, H., Byun, C., Cabido, M.R., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Curran, M., Ćušterevska, R., Stevanović, Z.D., De Bie, E., De Ruffray, P., De Sanctis, M., Dimopoulos, P., Dressler, S., Ejrnæs, R., El-Rouf Mousa El-Sheikh, M.A., Enquist, B., Ewald, J., Fagúndez, J., Finckh, M., Font, X., Forey, E., Fotiadis, G., García-Mijangos, I., de Gasper, A.L., Golub, V., Gutierrez, A.G., Hatim, M.Z., He, T., Higuchi, P., Holubová, D., Hölzel, N., Homeier, J., Indreica, A., Gürsoy, D.I., Jansen, S., Janssen, J., Jedrzejek, B., Jiroušek, M., Jürgens, N., Kącki, Z., Kavgacı, A., Kearsley, E., Kessler, M., Knollová, I., Kolomiychuk, V., Korolyuk, A., Kozhevnikova, M., Kozub, Ł., Krstonošić, D., Kühl, H., Kühn, I., Kuzemko, A., Küzmič, F., Landucci, F., Lee, M.T., Levesley, A., Li, C.-F., Liu, H., Lopez-Gonzalez, G., Lysenko, T., Macanović, A., Mahdavi, P., Manning, P., Marcenò, C., Martynenko, V., Mencuccini, M., Minden, V., Moeslund, J.E., Moretti, M., Müller, J.V., Munzinger, J., Niinemets, Ü., Nobis, M., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Ozinga, W.A., Pauchard, A., Pedashenko, H., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rodwell, J., Ruprecht, E., Rūsiņa, S., Samimi, C., Schaminée, J.H.J., Schmiedel, U., Šibík, J., Šilc, U., Škvorc, Ž., Smyth, A., Sop, T., Sopotlieva, D., Sparrow, B., Stančić, Z., Svenning, J.-C., Swacha, G., Tang, Z., Tsiripidis, I., Turtureanu, P.D., Ugurlu, E., Uogintas, D., Valachovič, M., Vanselow, K.A., Vashenyak, Y., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Wana, D., Weiher, E., Wesche, K., Whitfeld, T., Willner, W., Wiser, S., Wohlgemuth, T., Yamalov, S., Zizka, G. & Zverev, A. (2019) sPlot – a new tool for global vegetation analyses. Journal of Vegetation Science:30, 161-186.

https://doi.org/10.1111/jvs.12710

Lead author:

Jonathan Lenoir, Université de Picardie Jules Verne, France

Project outline:

A methodological paper proposing and describing a resampling strategy to deal with the unbalanced spatial distribution of data from most global databases such as the sPlot vegetation database (cf. cartogram of the number of vegetation plots per country). The basic idea of the resampling strategy is to perform a systematic sampling within the environmental space to capture a balanced sample that is representative of the available environmental variability. To represent the environmental variability that is available on a global scale, we will use a set of meaningful macroclimatic variables (e.g. the 19 BIOCLIM variables of WorldClim) that we will reduce by selecting the 2 to 3 first dimensions of an ordination method such as principal component analysis. Once the reduced environmental space will be delimited (cf. convex hull approach), a multidimensional grid will be laid out inside the convex hull to perform a systematic sampling. The obtained grid will represent the perfect configuration required to adequately sample the environmental space available at a global scale. All vegetation plots from the sPlot database will then be plotted within this environmental space to assess the density of vegetation plots available per environmental unit. The density of vegetation plots for a given environmental unit will likely be proportional to the total terrestrial surface area available for that environmental unit. Finally, a fixed number (n) of vegetation plots will be randomly selected from each environmental unit to get a balanced sample. This step will be repeated several times (k iterations) for each environmental unit. Among the k iterations of n vegetation plots, we will select the iteration that both maximizes the mean dissimilarity in species composition between the n selected vegetation plots and minimizes the standard deviation in the dissimilarity in species composition between the n selected vegetation plots. Such a resampling strategy will allow us to maximize the diversity of vegetation types sampled per environmental unit as well as among environmental units while minimizing the risk of spatial autocorrelation (cf. pseudo-replicates) in the vegetation data. Although developed in the framework of sPlot, this resampling strategy will also be widely applicable to any large ecological dataset.

Publications:

Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M.A.E.-R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de-Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J.-A., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H.-F., Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M. & Bruelheide, H. (2021) sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots. Global Ecology and Biogeography, 30, 1740-1764.

Lead author:

Helge Bruelheide, iDiv - Martin Luther University, Germany

Project outline:

The trait composition of plant communities is determined by climatic and edaphic factors, as well as by successional stage and disturbance regime. However, the relative strengths of macroclimate and local environmental factors in explaining global trait distributions at the scale of communities still remain unclear. Global studies typically focus on either sets of individual geo-located records or coarse-grain species assemblages, while the fine-grain functional composition of plant communities is only available for very limited local spatial extents. However, environmental factors act on the trait composition of communities through biotic interaction namely at this fine scale. So far, we lacked a comprehensive global database with a spatial resolution corresponding to the community scale at which individuals varying in functional traits co-exist.

Meanwhile, the new sPlot 2.0 database holds 1.1 million vegetation plots from more than 100 databases worldwide. More than 60% of the most frequent species are represented by at least one trait from the TRY 3.0 trait database, and gap-filling techniques have been used to estimate trait values for these most frequent species. For all plots, we calculated the community weighted mean (CWM) and functional diversity (FD) for 18 traits. We plan to use resampling strategies to achieve a representative stratification of plots in global climate space. Using linear regression techniques, principal component analysis (PCA) and redundancy analysis (RDA), we have related CWM and FD to bioclimatic variables. Furthermore, we plan to calculate geographically weighted regressions (GWR) and moving window analysis to assess spatial variation in trait-environment relationships. Finally, we plan to explore the influence of gap-filling and compare relationships based on CWMs of non-gap filled TRY data with those based on original trait mean values.

Publications:

Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Arfin Khan, M.A.S., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, D., Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, I., Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, R., Weiher, E., Welk, E., Wesche, K., Winter, M., Wirth, C. & Jandt, U. (2018) Global trait–environment relationships of plant communities. Nature Ecology & Evolution, 2, 1906-1917.

doi: 10.1038/s41559-018-0699-8

Lead author:

Tiffany Knight, iDiv - Martin Luther University Germany

Masha T. van der Sande - Wageningen University & Research, Wageningen, The Netherlands

Project outline:

It is well recognized that environmental filtering and biotic resistance play a strong role in determining which alien species will successfully naturalize and which communities get invaded.  Environmental conditions filter alien species from the species pool based on their functional traits.  Resident species with similar functional traits will compete with alien species for resources, providing biotic resistance to invasion.  These alternative mechanisms should result in patterns in functional and phylogenetic similarity in co-occurring native and alien species; and the strength and direction of these patterns as compared to null expectations should indicate the relative important of environmental filtering and biotic resistance in structuring invasions. These patterns should depend on the spatial scale of investigation; environmental filtering is expected to be an important mechanism at regional spatial scales whereas biotic resistance determines local co-existence patterns. It is rarely tested whether alien species are limited by different mechanisms in their native and exotic ranges. For example, aliens might have higher abundances in their exotic compared to native ranges due to the availability of resources that are used less by co-occurring species in their exotic range.  The sPLOT dataset combined with phylogenetic and/or functional information on species provides a new opportunity for understanding invasion patterns at both regional and local spatial scales. Addressing the relative roles of environmental filtering and biotic resistance of plants in their native and exotic ranges requires coding plant species as alien or native in each community plot within sPLOT. This is best achieved through collaboration with Global Naturalized Alien Flora (GloNAF).  Species will be identified that have adequate sampling in sPLOT in both their native and alien ranges.  We will compare the phylogenetic and/or functional similarity between each focal alien species and the species that it co-occurs with in its exotic and native ranges using appropriate null models.  We will consider whether these patterns correlate with the relative abundance achieved by species in their native and exotic ranges, and whether patterns of phylogenetic/functional similarity change with spatial scale and across environmental gradients.  

Publications:

van der Sande, M.T., Bruelheide, H., Dawson, W., Dengler, J., Essl, F., Field, R., Haider, S., van Kleunen, M., Kreft, H., Pagel, J., Pergl, J., Purschke, O., Pyšek, P., Weigelt, P., Winter, M., Attorre, F., Aubin, I., Bergmeier, E., Chytrý, M., Dainese, M., De Sanctis, M., Fagundez, J., Golub, V., Guerin, G.R., Gutiérrez, A.G., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Kearsley, E., Klotz, S., Kramer, K., Moretti, M., Niinemets, Ü., Peet, R.K., Penuelas, J., Petřík, P., Reich, P.B., Sandel, B., Schmidt, M., Sibikova, M., Violle, C., Whitfeld, T.J.S., Wohlgemuth, T. & Knight, T.M. Similar factors underlie tree abundance in forests in native and alien ranges. Global Ecology and Biogeography, n/a

doi:10.1111/geb.13027

Lead author:

Michael Kessler, University of Zurich, Switzerland

Project outline:

We want to use a large compilation of vegetation plots with data on ferns and lycophytes (for brevity: ferns) to produce a global model of fern species richness at the local scale. This model can then be linked to data on, e.g., life forms (terrestrial/epiphytic) or phylogenetic relationships, to address questions about the global distribution and evolution of fern diversity. We are still uncertain about the exact delimitation of the first paper, whether it will “just” be the diversity model or whether we go straight for one of the more derived analyses. The plan thus is to first compile the data and conduct some preliminary analyses and based on this, to then decide how to subdivide and place the publications.

Based on 20 years of field work, we have already compiled a database of some 3500 plots with data on ferns. All plots are 20 m x 20 m in size and at least have a differentiation between epiphytic and terrestrial life forms plus indication of whether a species was sterile or fertile. The newer plots also have estimates of numbers of individuals (partly separate by sterile/fertile plants) and data on different epiphytic life zones (Johansson zones). These data are global but with a very strong focus on tropical regions. The aim of the present proposal is to add methodologically comparable data from especially temperate and boreal regions, to achieve a global coverage.

For the modeling, we will use several environmental predictors: A new global climate model at high resolution (~1 x 1 km) (www.chelsa-climate.org) to apply generalized linear models to the plot data to establish richness-climate relationships and then extend this to a global scale; a global dataset of soil conditions (harmonized world soil database, http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/); a global cloud climatology (http://www. earthenv.org/cloud).

Publications

Weigand, A., Abrahamczyk, S., Aubin, I., Bita-Nicolae, C., Bruelheide, H., I. Carvajal-Hernández, C., Cicuzza, D., Nascimento da Costa, L.E., Csiky, J., Dengler, J., Gasper, A.L.d., Guerin, G.R., Haider, S., Hernández-Rojas, A., Jandt, U., Reyes-Chávez, J., Karger, D.N., Khine, P.K., Kluge, J., Krömer, T., Lehnert, M., Lenoir, J., Moulatlet, G.M., Aros-Mualin, D., Noben, S., Olivares, I., G. Quintanilla, L., Reich, P.B., Salazar, L., Silva-Mijangos, L., Tuomisto, H., Weigelt, P., Zuquim, G., Kreft, H. & Kessler, M. Global fern and lycophyte richness explained: How regional and local factors shape plot richness. Journal of Biogeography, n/a

https://doi.org/10.1111/jbi.13782

Lead author:

Francesco Sabatini, University of Bologna, Italy

Project outline:

The definition of a species pool is a crucial step for many types of analysis in community ecology, including community assembly processes, invasability or resistance. Knowledge of the species pool is necessary to estimate the number of non-resident species that potentially can occur in a plot (“dark diversity”). In a heterogeneous database as sPlot with varying plot sizes and samples from a wide range of habitats, the definition of a species pool is also fundamental for calculating species richness at a particular spatial scale.

There are many attempts of defining species pools, both using internal criteria (e.g. sum of all species that occur in a set of plots) or external criteria (e.g. a geographic region or a certain climate space). However, most attempts result in a pool of species that simply reflects the overall g diversity of this set. Similarly, attempts to define the species pool by floristic similarity among plots or by environmental similarity may unnecessarily constrain the potential species pool. Here, I propose to define a species pool as the set of species that are potentially able to occur in a given community. An implication is that a species-pool is community-specific. If a plot vegetation record is considered a community, which in this proposal I do, each plot can be characterized by its own potential species pool. 

Publication:

Sabatini, F.M., Jiménez-Alfaro, B., Jandt, U., Chytrý, M., Field, R., Kessler, M., Lenoir, J., Schrodt, F., Wiser, S.K., Arfin Khan, M.A.S., Attorre, F., Cayuela, L., De Sanctis, M., Dengler, J., Haider, S., Hatim, M.Z., Indreica, A., Jansen, F., Pauchard, A., Peet, R.K., Petřík, P., Pillar, V.D., Sandel, B., Schmidt, M., Tang, Z., van Bodegom, P., Vassilev, K., Violle, C., Alvarez-Davila, E., Davidar, P., Dolezal, J., Hérault, B., Galán-de-Mera, A., Jiménez, J., Kambach, S., Kepfer-Rojas, S., Kreft, H., Lezama, F., Linares-Palomino, R., Monteagudo Mendoza, A., N’Dja, J.K., Phillips, O.L., Rivas-Torres, G., Sklenář, P., Speziale, K., Strohbach, B.J., Vásquez Martínez, R., Wang, H.-F., Wesche, K. & Bruelheide, H. (2022) Global patterns of vascular plant alpha diversity. Nature Communications, 13, 4683. (article online)

Lead authors:

Riccardo Testolin and Fabio Attorre (Sapienza University of Rome, Italy), Borja Jiménez-Alfaro (iDiv - Martin Luther University, Germany)

Project outline:

This project is, together with sPlot #17, part of the “mountain diversity” sPlot studies focusing on different dimensions of plant diversity in the alpine regions of the world. In particular, this study is the first part of a PhD project by Riccardo Testolini in the University La Sapienza, co-supervised by sPlot members Fabio Attorre and Borja Jiménez-Alfaro. We want to use sPlot to compare plant community diversity of alpine areas using vegetation plot data from different continents. Our main aim is to investigate major patterns and drivers of taxonomical and functional diversity in alpine regions worldwide, focusing on alpha- and gamma-diversity. Pre-selected regions with available data are: Alaskan arctic tundra, Rocky alpine mountains, Colombian Páramo, Scandinavian boreal tundra, European Alpine vegetation, oromediterranean Atlas Mountains, Semi-arid Iranian alpine mountains, Pamir plateau and Altai alpine tundra. First, we will explore data quality by filtering vegetation data to a representative number of plots per region, ensuring a relatively equal sampling effort in similar habitats. We will model local plot species richness, functional trait values aggregated in CWMs and functional diversity indices, in response to environmental predictors (mostly climate and soil data) within regions and across regions, using correlative regression analyses (e.g. GLMs). In addition, we will compare regional richness with rarefaction curves, and will use interpolation and extrapolation techniques (e.g. those implemented in iNEXT R package) to estimate species pool sizes. To understand better the observed patterns, we will conduct a climatic and historical characterization of the studied regions. The results will provide a first overview of the global patterns of plant diversity in alpine vegetation, in order to interpret the role of environmental drivers versus regional (historical) differences in shaping alpine communities. 

Publications:

Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos-Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, R., Willner, W., Wiser, S.K., Zibzeev, E.G. & Jiménez-Alfaro, B. (2021) Global patterns and drivers of alpine plant species richness. Global Ecology and Biogeography, n/a. (article online)

Testolin, R., Carmona, C.P., Attorre, F., Borchardt, P., Bruelheide, H., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Mucina, L., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Vassilev, K., Virtanen, R., Wiser, S.K., Zibzeev, E.G. & Jiménez-Alfaro, B. (2021) Global functional variation in alpine vegetation. Journal of Vegetation Science, 32, e13000. (article online)

Lead authors:

Zhiyao Tang, sPlot Consortium Member, Institute of Ecology, Peking University

Qiong Cai, Department of Ecology, College of Urban and Environmental Sciences, Peking University (PKU) and Institute of Biology / Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg (MLU)

Project outline:

The genus Fagus is one of the most representative broadleaved deciduous trees in the Northern Hemisphere. Although phylogenetic relationships of different Fagus species have been broadly studied, much less attention has been given to the comparison of their niche breadth, which is expected to differ strongly across species. It is also interesting to see whether two species far in the phylogenetic tree have small overlaps of the niche.

There have been different methods developed to estimate niche width, such as climate-envelope or species co-occurrence-based estimates. We plan to compare the niche widths of Fagus species by two methods: 1) estimates based on species co-occurrence data, using the Fridley approach, and 2) by calculating the climate space occupied by a species, using environmental data such as climate and soil properties and the ‘hypervolume’ and ‘dynamic range boxes’ approaches. The basic idea is that co-occurrence niche and climatic niche are related to each other.

So far, we have obtained a database of Fagus plots in China by extensive field surveys. Combined with that in sPlot, it is possible to estimate the realized niche breadth of different Fagus species worldwide using the methods mentioned above. We aim as well to get a more comprehensive understanding of the relationships among species in the genus Fagus.

Publications:

Cai, Q., Welk, E., Ji, C., Fang, W., Sabatini, F.M., Zhu, J., Zhu, J., Tang, Z., Attorre, F., Campos, J.A., Čarni, A., Chytrý, M., Çoban, S., Dengler, J., Dolezal, J., Field, R., Frink, J.P., Gholizadeh, H., Indreica, A., Jandt, U., Karger, D.N., Lenoir, J., Peet, R.K., Pielech, R., De Sanctis, M., Schrodt, F., Svenning, J.‐C., Tang, C.Q., Tsiripidis, I., Willner, W., Yasuhiro, K., Fang, J. and Bruelheide, H. (2021), The relationship between niche breadth and range size of beech (Fagus) species worldwide. J Biogeogr. https://doi.org/10.1111/jbi.14074

Lead authors:

Daniel Laughlin, Alexandra Weigelt, Liesje Mommer, Helge Bruelheide (sPlot member) + sRoot consortium

Project outline:

Environmental filtering is a key process in community assembly that sorts species along environmental gradients according to variation in ecophysiological tolerance. However, our current understanding of how traits explain turnover in community composition along environmental gradients at a global scale is limited to aboveground traits of leaves, stems, and seeds. Establishment and survival in plants requires the ability to acquire water and nutrients from the soil, a process that is driven by belowground root traits. Our understanding of the key drivers of community assembly is biased toward aboveground traits and therefore woefully incomplete.

Recently, the sDiv working group sRoot has assembled the largest global database of root traits, including measurements of 4 key functional traits (specific root length, root diameter, root tissue density, and root nitrogen concentration) on >1,000 species. We propose to determine the global environmental drivers of root trait variation by integrating the sRoot database of root traits with the sPlot database of vegetation plots. Climate and soil variables for each plot will be extracted from other available databases. This unprecedented integration of the two largest databases of their kind would facilitate the most powerful statistical analysis to test how root traits vary along climate and soil gradients globally.

We will compute community-weighted means for each root trait on each vegetation plot and regress these on climate and soil factors to test whether these traits vary along these gradients at a global scale. We will also test the adaptive value of root traits by fitting GLMMs to determine whether species occurrence is a function of interactions between root traits and environmental gradients. In other words, we will test whether species occurrence in a given environment depends on their root traits. GLMM’s allow us to incorporate random effects to account for how species occurrence varies along the gradients to isolate the trait-by-environment interaction in the fixed effects, as well as other random factors such as the study from which the root trait data originated. This global scale analysis will substantively advance our understanding of how root traits vary along global environmental gradients.

Publications

Laughlin, D.C., Mommer, L., Sabatini, F.M., Bruelheide, H., Kuyper, T.W., McCormack, M.L., Bergmann, J., Freschet, G.T., Guerrero-Ramírez, N.R., Iversen, C.M., Kattge, J., Meier, I.C., Poorter, H., Roumet, C., Semchenko, M., Sweeney, C.J., Valverde-Barrantes, O.J., van der Plas, F., van Ruijven, J., York, L.M., Aubin, I., Burge, O.R., Byun, C., Ćušterevska, R., Dengler, J., Forey, E., Guerin, G.R., Hérault, B., Jackson, R.B., Karger, D.N., Lenoir, J., Lysenko, T., Meir, P., Niinemets, Ü., Ozinga, W.A., Peñuelas, J., Reich, P.B., Schmidt, M., Schrodt, F., Velázquez, E. & Weigelt, A. (2021) Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs. Nature Ecology & Evolution, 5, 1123–1134. https://doi.org/10.1038/s41559-021-01471-7

Lead authors:

Maria Sporbert - Martin-Luther University Halle-Wittenberg, Germany

Project outline:

In this study we investigate which traits are important for species to become widespread at largescale and/or dominant at small-scale. Here, we expect species large-scale distribution to be mainly driven by dispersal traits, while species small-scale dominance to be mainly influenced by growth and performance traits. From previous analysis we know that in some species small-scale dominance seems to be unrelated to both, the position of the occurrence in species geographic range and the predicted climatic suitability of the occurrence. Therefore, we expect that whether a species is generally common or rare is mainly driven by functional traits related to competitive ability (e.g. plant height, SLA).

Our species set consists of 517 vascular plant species, for which species dominance has been measured as plant cover. Species cover values were retrieved from 744,513 vegetation plots from the European Vegetation Archive. Range maps from the Chorological Database Halle were used to capture species’ geographic ranges and to derive species’ climatic niches. The distance of each plot to the range centre was calculated per species for each occurrence in the  geographic and the climatic space. Species large-scale climatic suitability was predicted from species distribution models (SDMs).

We will apply regression tree analysis to test for the relationship between species’ range size, niche size, species’ dominance in vegetation plots, the position and climatic suitability of the plot occurrence with function traits. Furthermore, we will use principal component analysis to illustrate the relationships.

Publications:

Sporbert, M., Welk, E., Seidler, G., Jandt, U., Aćić, S., Biurrun, I., Campos, J.A., Čarni, A., Cerabolini, B.E.L., Chytrý, M., Ćušterevska, R., Dengler, J., De Sanctis, M., Dziuba, T., Fagúndez, J., Field, R., Golub, V., He, T., Jansen, F., Lenoir, J., Marcenò, C., Martín-Forés, I., Moeslund, J.E., Moretti, M., Niinemets, Ü., Penuelas, J., Pérez-Haase, A., Vandvik, V., Vassilev, K., Vynokurov, D. & Bruelheide, H. (2021) Different sets of traits explain abundance and distribution patterns of European plants at different spatial scales. Journal of Vegetation Science, 32, e13016. https://doi.org/10.1111/jvs.13016

Lead authors:

Daniel C. Laughlin, Department of Botany, University of Wyoming, Laramie, WY 82071 USA

Project outline:

Environmental filtering is a key process in community assembly that sorts species along environmental gradients according to variation in ecophysiological tolerance. However, our current understanding of how traits explain turnover in community composition along environmental gradients at a global scale is limited to easy-to-measure morphological traits. Plant establishment and survival requires the capacity to conduct water through its tissues when water is available and the ability to resist drought-induced embolism when water is scarce. Databases of xylem vulnerability (P50) and hydraulic conductance (Ks) have recently been published including approximately 1000 common woody species.

We propose to determine how xylem physiology influences the likelihood that a species can occur in a particular environment by integrating a database of xylem physiological traits with the sPlot database of vegetation plots. Climate and soil variables for each plot will be extracted from other available databases. This unprecedented integration of the two largest databases of their kind would facilitate the most powerful statistical analysis to test how xylem traits vary along climate and soil gradients globally.

We will test the adaptive value of xylem traits by fitting a hierarchical mixed effects model to determine whether species occurrence is a function of interactions between xylem traits and environmental gradients within and across global ecoregions. In other words, we will test whether species occurrence in a given environment depends on their xylem properties. This global scale analysis will substantively advance our understanding of how xylem traits vary along global environmental gradients.

Publication:

Laughlin, C D., Siefert, A., Fleri, J., Tumber-Dávila, S J., Hammond, W., Sabatini, F M., Damasceno, D., Aubin, I., Field, R., Hatim, M Z., Jansen, S., Lenoir, J., Lens, F., McCarthy, J K., Niinemets, U., Phillips, O L., Attorre, F., Bergeron, Y., Brambach, F., Bruun, H K., Byun C., Ćušterevska, R., Dengler, J., Sanctis, M., Dolezal, J., Jiménez-Alfaro, B., Herault, B., Homeier, J., Kattge, J., Meir, P., Mencuccini, M., Noroozi, J., Nowak, A., Penuelas, J., Schmidt, M., Škvorc, Z., Sultana, F., Ugarte, R M., Zizka, G., Bruelheide, H. (2023). Rooting depth and xylem vulnerability are independent woody plant traits jointly selected by aridity, seasonality, and water table depth. New Phytlogist. https://doi.org/10.1111/nph.19276

Lead author:

Oliver Purschke, iDiv - Martin Luther University, Germany

Project outline:

There are a number of conflicting hypothesis about how temporal environmental variability (EVt) affects the distribution of traits (e.g. functional diversity) within communities. In this study, we aim to quantify the extent to which the effect of EVt on trait variability depends on i) the time scale at which EVt occurs, ii) climate type (i.e. biogeographic region), iii) formation (grassland vs. forest) and iv) spatial grain size. Although effects of spatial gradients of environmental means, e.g. those related to energy, on species and trait diversity are well studied, there has been little emphasis on how temporal variation around environmental mean values affects biodiversity. There is a rich body of theory making predictions about how temporal environmental variability, through changes in the trait distribution within communities, affects coexistence mechanisms that generate biodiversity. For example, at local scales (small grain sizes, i.e. at the vegetation-plot level), where biotic processes such as competition play a major role, temporal environmental variability can promote diversity through temporal niche partitioning: species that differ in their functional characteristics (traits) will be favored at different periods of time, in which case temporal variability will increase trait diversity within communities. In contrast, some forms of environmental variability, such as long-term climatic variability (i.e. climate change velocity), have been demonstrated to decrease trait variability, with long-term unstable and harsh environments having the lowest diversity of trait states ('physiological tolerance hypothesis'), suggesting that the temporal scale at which EVt occurs determines whether EVt promotes or constrains trait variability. Further, because the frequency at which climatic extreme events occur differs among climates, the effect ETv on trait variability is expected to vary among biomes. So far, studies of ETv on trait diversity have focused on single temporal scales and bioclimatic regions, and there is therefore a need for synthetic studies across biomes and scales.  

Lead author:

Brody Sandel, Santa Clara University, USA

Project outline:

Large amounts of data are being generated by Earth observation satellites, but the information that is extracted falls far short of what is needed to monitor biological diversity from space. Global efforts to measure biodiversity from space have, broadly, focussed on two types of variables: ecosystem variables (e.g. LAI, GPP, NPP, leaf chlorophyll and water content) and vegetation indices (e.g. NDVI, EVI). Technical limitations and potentially invalid assumptions still hamper accurate estimates of ecosystem variables, but perhaps a more fundamental issue that prevents the use of ecosystem variables in assessing (changes in) diversity patterns is that their relationships with diversity are not known. For example, plant communities with different species composition may have identical productivity. Vegetation indices (typically described as ‘greenness’) are problematic for the same reasons and in addition it is difficult to establish a precise ecological meaning for vegetation indices. In short, establishing clear links between Earth observation data and ground data is essential for effective monitoring of biodiversity from space. As part of the Biosphere Atmosphere Change Index (BACI), which is funded under the EU Horizons 2020 programme, this study aims to produce spatially up-scaled indices of change in community composition and ecosystem functioning. These maps will be used within the BACI project to validate and inform change detection from Earth observation data. 

Lead author:

Oliver Purschke, iDiv - Martin Luther University, Germany

Lead author:

Brody Sandel, Santa Clara University, USA

Project outline:

The limited accuracy of occurrence data, especially for a large and less well-known group such as Poaceae, is a substantial impediment to understanding the mechanisms shaping species distributions at large spatial extents. Species checklists at the level of “botanical countries” are the only comprehensive dataset that provides reliable coarse-grain presences for all grass species at global scale (WCSP; Royal Botanic Gardens Kew, 2015). At the same time, sPlot made a huge step to gather fine-scale presence-absence data at a global scale. Both coarse-grain and fine-grain presences could be now combined to get fine-scale map of occurrences.

We are using a downscaling method of species distribution model to get fine-scale presence probabilities of grasses based on a hierarchical Bayesian modelling framework. This most recent method of downscaling from coarse-grain resolution and fine-scale environmental data has been developed by Keil et al. (2013). We are adapting it to the case of plant distributions, taking advantage of multi-scale reliable information available for grasses (checklist, vegetation plots, point records). While the method is currently tested at the scale of the USA, our goal is to perform the analysis at global scale.

For Poaceae family, we thus aim to gather for the first time coarse-grain presence data (species checklists) with fine-scale presence-absence data from vegetation plots (sPlot) and point presences (GBIF) to get fine-grain probabilities of grass occurrences worldwide.

References

Keil, P., Belmaker, J., Wilson, A.M., Unitt, P. & Jetz, W. (2013) Downscaling of species distribution models: a hierarchical approach. Methods in Ecology and Evolution, 4, 82–94.

Royal Botanic Gardens Kew (2015) World Checklist of Selected Plant Families.

Lead authors:

Anne Mimet (Helmholtz-Zentrum für Umweltforschung (UFZ), Leipzig, Germany; German Institute of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany)

Julia Joswig (German Institute of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Germany)

Project outline:

Land-uses constitute one of the main threat to biodiversity and ecosystem functions and services in an increasingly anthropized world. By changing the biotic and abiotic conditions, land-uses very strongly change the composition and structure of all plant and animal communities. For plants and low mobile animal species, land-use can have large direct impacts, killing the individuals and/or their offsprings. In addition, land-use very often has strong indirect impacts on species, by changing resource and habitat quality and availability. The filtering processes induce by land-uses on plant communities have been explored during the last 20 years. These studies provide a reliable mechanistic knowledge and understanding of the set of response traits by which land-use filter species and change the functional composition of communities. Meanwhile, our knowledge of how land-use modifies animal communities mainly relies on statistical relationships relating distribution data to land-use descriptions. Compared to plants, the development of a mechanistic understanding of animals’ responses to land-use is complicated by the mostly indirect effects of land-use on animals, via changes in resource and habitat. Building this mechanistic understanding depends on our ability to describe the changes in resources and habitats induce by land-use.  

In this project, we aim to build a Vegetation <> Land-use converter for Europe which will offer a translation between land-uses and functional vegetation groups. The converter will use an ecologically meaningful description of land-uses, where land-use is described into three dimensions: the frequency/intensity and the type of land-use and the potential productivity and an appropriate and extensive set of traits. The sPlot data will be used to calibrate the sections of the model related to the responses to natural gradients and to provide the traits data. Land-use / Vegetation data from numerous European data bases and publications will be used to calibrate the sections of the model related to the responses to the land-uses. By providing the needed basis for establishing mechanistic links between land-use and structure of communities, the converter will be useful to project scenarios of biodiversity (plants, animals and ecosystem services). It will also be used in a current Flexpool project to extract more information about past land-use from Holocene pollen data.