sPlot Projects

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:

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 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:

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:

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:

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:

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:

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:

Daniel Laughlin, University of Wyoming

Project outline:

Environmental filtering is a key process in community assembly that sorts species along environmental gradients according to variation in ecophysiological tolerances. However, our current understanding of how traits explain turnover in community composition along environmental gradients at a global scale is generally limited to aboveground traits. Plant population persistence is achieved through belowground resource uptake, defense, anchorage, regeneration, and clonal mobility, yet our understanding of how these trait combinations are distributed along global gradients remains limited. The sUnderfoot iDiv working group has assembled a database the integrates belowground plant traits, including fine root economics, clonality, bud banks, rooting depth, and lateral extent.

We propose to determine how belowground plant traits influence the likelihood that a species can occur in a particular environment by integrating our trait database with the sPlot database of vegetation plots. Climate (minimum temperature, aridity, and precipitation seasonality), topography and local water availability, and disturbance (fire) for each plot will be extracted from global databases. This unprecedented integration of these databases would facilitate the most powerful statistical analysis to test how belowground traits determine species distributions.

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

Lead author:

Gayana Bexultanova, University of Glasgow

Project outline:

In the context of ecological and ethnobotanical research, understanding vegetation composition in various biomes is of primary importance. This paper aims to use an extensive database of relevés to the east of 60° E meridian and north of 40° N parallel, encompassing forest, steppe, meadow, wetland, tundra, mountain tundra, high mountain vegetation, to characterise the vegetation composition in corresponding regions and identify plant species of ethnobotanical importance, drawing on data on plant use by local populations from historical sources and recent studies. We also aim to evaluate the availability of other food and medicinal plants in the region.
Based on the results obtained, further research will be aimed at predicting the vegetation composition of the mammoth steppe approximately 50,000-15,000 years ago. Assuming the relative stability of plant composition in a biome over time as biomes shift, we will reconstruct the vegetation composition of the corresponding biomes in the mammoth steppe. This will allow us to suggest plant species that may have been utilised by early humans in this region and shed light on historical ecosystems and human-environment interactions.
Methodologically, our study focuses on statistical and ecological methods used to determine plant species and their ratios in different biomes. We will use data preprocessing, statistical analysis and ecological modelling to achieve the objectives of the study. In addition, the integration of ethnobotanical data adds depth to our analyses by providing a more comprehensive understanding of the ecological and cultural significance of plant species.

Lead author:

Nan Zhang, Chinese Academy of Sciences

Project outline:

Plant phenology, the study of recurring biological events in plant organisms, is essential for understanding various ecosystem processes. Several studies suggests that variations in functional traits are associated with phenological variation. However, most of these studies have been constrained to limited sites and data, resulting in a lack of comprehensive research on the association between plant functional traits and vegetation phenology. Therefore, we would like to evaluate the linkages between plant functional traits and phenology across temperate zones to deepen our comprehension of  how plants adopt strategies to modulate the timing of key plant life cycle events.

There are various methods to assess the relative impacts of different plant function traits on phenology variability. One widely accepted method is to examine the correlation between traits and phenology using Pearson’s correlation coefficient. Another method is to directly disentangle the relative significance through the utilization of  generalized linear models, stepwise regression, and random forest analyses.

By combining community-level plot data from “sPlot” and satellite-derived phenology product, we intend to employ the aforementioned methods to quantify and unravel the contributions of plant traits to the phenology variation. With the environmental data accordingly, we could furtherly explore the global temperate pattern of phenology as well as the relative roles of abiotic and biotic effects on it.

Lead author:

Teja Kattenborn, University of Freiburg

Project outline:

The acceleration of global environmental change underscores the pressing need for a comprehensive understanding of how the biosphere interacts with its environment. To reliably examine these connections across diverse ecosystems, having spatially continuous data on plant functional traits is imperative. Trait databases such as TRY boast an extensive repository of plant trait measurements for thousands of species for individual locations. Previous approaches have attempted to spatially extrapolate such local trait measurements using environmental predictors or Earth observation data. Thereby, a common challenge is the scarcity of the original data, which leads to significant uncertainty in the extrapolations in data-scarce regions. Meanwhile, citizen scientists have been actively gathering dense observations of species occurrences worldwide. Despite considerable noise and the absence of a consistent sampling strategy, such crowd-sourced data can, when matched with trait data from trait databases, adequately represent global trait patterns at coarse spatial scales. Aiming to exploit this potential to create global trait maps at high spatial resolution, here we explore the synergetic use of citizen science, environmental predictors, and Earth observation data to generate global maps of 31 ecologically relevant plant functional traits at resolutions of 2°, 0.5°, 0.2°, and 0.01°. We link species occurrences from the Global Biodiversity Information Facility (GBIF) with the TRY database and generate continuous global trait maps as a function of climate, soil, and remote sensing data using XGBoost models. We found a high correspondence of the mean trait values from the GBIF-based extrapolations to community-weighted mean traits from sPlotOpen, a global, environmentally balanced dataset of vegetation plot data (up to r = 0.73). Across almost all traits, these correlations are higher than the majority of previously published trait maps. Additionally, when compared to similar extrapolations based on sPlotOpen alone, we found that GBIF-based extrapolations increased transferability of all models by up to 12%. Despite the inherent noise and biases of their crowd-sourced origins, GBIF-based models are remarkably capable of producing even closer approximations of the trait distributions of scientifically controlled vegetation plots than their own sparse reference data. Considering the rapid growth and availability of crowd-sourced data, the capacity of models to overcome their noisy and opportunistic nature further affirms the potential of databases such as GBIF to complement more scientifically rigorous data collections.

Lead author:

Shuya Fan & Mark van Kleunen (University of Konstanz)

Project outline:

Species naturalization into diverse ecosystems worldwide is occurring at an unprecedented rate, leading to the homogenization of global biotas. Understanding the patterns and mechanisms of global alien species naturalization has thus become a critical issue in ecological research. Darwin’s naturalization conundrum invokes phylogenetic relatedness to explain the naturalization of alien species, by describing two seemingly contradictory hypotheses regarding that alien species phylogenetically closely or distinctly related to native species are more likely to successfully naturalize. Reconciling the conundrum has gained increasing attention in recent years, though different studies often yielded inconsistent results. Previous research has revealed that the influence of phylogenetic relatedness on species naturalization depends on the latitude of the study site. In harsh environments at high latitudes, closely related species are more likely to naturalize, while in more benign environments at low latitudes, naturalized species tend to be more distantly related to native species. Additionally, the validity of these two hypotheses also depends on the spatial scale; at larger scales, close phylogenetic relatedness with native species is more likely to facilitate naturalization. Although both spatial scale and latitude jointly affect the validity of the two hypotheses in Darwin’s naturalization conundrum, studies that integrate these factors remain insufficient. Therefore, we aim to: 1) examine whether the phylogenetic relatedness between native and naturalized species consistently exhibits a latitudinal gradient pattern at various spatial scales; and 2) identify the dominant factors driving the variation in phylogenetic relatedness across latitude and spatial scales. To achieve these objectives, the sPlot database will be used to obtain global vegetation community data. The GloNAF (van Kleunen et al. 2019; DOI: 10.1002/ecy.2542) and POWO (https://powo.science.kew.org/) databases will respectively identify naturalized and native plant species in each plot. In each plot, phylogenetic relatedness between native and naturalized species will be calculated, and variations in this relatedness with latitude and plot area will be further assessed. Note that we will also use data from plots without any naturalized species, as we have for each plot a potential pool of naturalized species (from the GloNAF database). Moreover, environmental data, including climate, soil, and human activity for each plot, will be integrated to analyze the main drivers in the trends of Darwin’s naturalization conundrum with latitude and area.

Lead author:

Leon Nill, Humboldt-Universität zu Berlin

Project outline:

Understanding the functioning and distribution of ecosystems are central interests of biogeography. The tropical realms receive much attention in conservation and sustainability agendas since they harbour astonishing biodiversity and almost half the human population. Yet, regarding research and conservation of the tropics, there has been a strong historical bias toward tropical rainforests compared to dry forests, woodlands, and savannas. These ecosystems also exhibit considerable complexity in structural, compositional, and functional terms, and how to capture this complexity adequately is a challenge. Although much research has focussed on understanding the underlying ecological and evolutionary processes of this diversity, fundamental biogeographic puzzles remain only partly understood and classified, including forest-savanna transitions and potential bistability, as well as the actual distribution of tropical grassy biomes, which requires clarifying how to ideally characterise these systems. Process- and function-based frameworks may help structure complexity in this regard, and produce consistent, scalable, and ecologically meaningful descriptions but are yet to be operationalized for tropical forests and savannas.

In this study we intend to assess if recurring general ecosystem types can be meaningfully derived from observational data on plant distribution and traits. We intend to integrate these ecological records with remotely sensed spectral traits in order to structure the diversity of tropical dry forests and savannas along key functional attributes using informed cluster analysis. Our approach is based purely on observations covering a wide array of functional and compositional attributes, with the advantage of isolating ecosystem characterisation from drivers of ecosystem assembly (e.g., climate, soil, disturbance, biotic interactions). The result of our exercise are archetypes of tropical ecosystems which will help to better understand the present biogeographic patterns in relation to functional traits, facilitate comparisons across geographies, and move beyond singular – often climate-deterministic – approaches to ecosystem characterisation. By leveraging remote sensing derived proxies on ecosystem structure, composition, and phenology we aim at exploring the potential of mapping these types across the tropical geographies.

Lead author:

Yanhao Feng, Lanzhou University, China

Project outline:

The goal of this project is to explore whether locally more abundand plant species have more positive responses to climate warming on a global scale. This is important because it could determine the diversity and composition of natural communities in the context of climate change. To achieve the goal, we plan to combine the sPlot dataset and a global dataset of plant warming response we have compiled from 578 studies of warming experiments including 683 speciesa and a comprehensive list of functional traits and fitness measures (biomass, reproduction). Our previous research has proposed a trait-based framework to analyse the global dataset of plant warming responses, and shown how plant species respond to climate warming from traits to fitness. So, we want to conduct a follow-up study to test if warming responses of species depended on their local abundaces. We have tried to use the open version of the sPlot dataset to obtain the relative abundance of all our 683 study species for preliminary analysis. To make our results more reliable, we plan to use sPlot 4.0 to update the preliminary results.