Projects

 

PROJECTS APPROVED BY THE sPLOT STEERING COMMITTEE:

(#01) sPlot – a global database of fine-grain plant community data

Lead author:

Jürgen Dengler, University of Bayreuth, Germany

(#02) A resampling strategy to analyze community assembly rules in a big data world

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.

(#03) Global trait-environment relationships revealed by sPlot

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.

(#04) The role of climate stability for trait variability across scales and biomes (DISCONTINUED)

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.  

(#05) The role of climate stability for trait variability across scales and biomes: Can Earth observation data be used to measure changes in taxonomic and functional diversity?

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. 

(#06) Global patterns of phylogenetic similarity and abundance of plants in their native and exotic ranges

Lead author:

Tiffany Knight, iDiv - Martin Luther University Germany

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.  

(#07) Scaling taxonomical, functional and phylogenetic community diversity (DISCONTINUED)

Lead author:

Oliver Purschke, iDiv - Martin Luther University, Germany

(#08) A global assessment of functional diversity and redundancy effects on ecosystem stability during climatic anomalies

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.

(#09) Downscaling of species distribution models: towards fine-grain presence-absences for grasses

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.

(#10) A global model of local fern diversity

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).

(#11) Probabilistic species pools at the plot level

Lead author:

Helge Bruelheide, iDiv - Martin Luther University, Germany

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. 

(#12) Temperate deciduous forests of the northern hemisphere

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.

(#13) Global patterns of aquatic macrophyte diversity – environment relationships with focus on native versus invasive species

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.

(#14) Functional convergence of terrestrial ecosystems within world biomes

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.

(#15) Cross-scale transferability of species niche breadth estimates

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.

(#16) Projecting tree diversity and distributions in a changing world

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. 

(#17) Spatial patterns of plant assemblages in mountains. A global analysis

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. 

(#18) Global patterns of taxonomical and functional diversity above the treeline

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. 

(#19) Toward a mechanistic description of land uses for ecological studies: Building a Vegetation <> Land-use converter for Europe

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.

(#20) Trait-dependent extinctions across flowering plants in biodiversity hotspots

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.

 

 

 

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