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Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Asynchronous migration of insect herbivores and their host plants towards higher elevations following climate warming is expected to generate novel plant–insect interactions. While the disassociation of specialised interactions can challenge species' persistence, consequences for specialised low‐elevation insect herbivores encountering novel high‐elevation plants under climate change remain largely unknown. To explore the ability of two low‐elevation Lepidoptera species, Melitaea celadussa and Zygaena filipendulae, to undergo shifts from low‐ to high‐elevation host plants, we combined a translocation experiment performed at two elevations in the Swiss Alps with experiments conducted under controlled conditions. Specifically, we exposed M. celadussa and Z. filipendulae to current low‐ and congeneric high‐elevation host plants, to test how shifts in host plant use impact oviposition probability, number of eggs clutches laid, caterpillar feeding preference and growth, pupation rate and wing size. While our study shows that both M. celadussa and Z. filipendulae can oviposit and feed on novel high‐elevation host plants, we reveal strong preferences towards ovipositing and feeding on current low‐elevation host plants. In addition, shifts from current low‐ to novel high‐elevation host plants reduced pupation rates as well as wing size for M. celadussa, while caterpillar growth was unaffected by host plant identity for both species. Our study suggests that populations of M. celadussa and Z. filipendulae have the ability to undergo host plant shifts under climate change. However, these shifts may impact the ability of populations to respond to rapid climate change by altering developmental processes and morphology. Our study highlights the importance of considering altered biotic interactions when predicting consequences for natural populations facing novel abiotic and biotic environments. [ABSTRACT FROM AUTHOR]

The article explores the relationship between climate, phytochemical diversity, and plant mycorrhizal types on global latitudinal patterns in leaf herbivory. The study challenges the latitudinal herbivory hypothesis, which suggests that insect herbivory rates decline with increasing latitudes. The researchers compiled a large dataset of herbivory rates, climatic factors, phytochemical diversity, and plant mycorrhizal types from published materials. They found that climate, particularly temperature and precipitation, had significant effects on herbivory and its latitudinal pattern. However, phytochemical diversity and plant mycorrhizal types did not have a significant impact on herbivory. The study suggests that climate plays a crucial role in shaping global patterns of plant-herbivore interactions. [Extracted from the article]

Understanding the ecological rules structuring the organization of species interactions is a prerequisite to predicting how ecosystems respond to environmental changes. While the ecological determinants of single networks have been documented, it remains unclear whether network ecological rules are conserved along spatial and environmental gradients. To address this gap, we reconstructed 48 plant–herbivore interaction networks along six elevation gradients in the Central European Alps in Switzerland, using DNA metabarcoding on orthoptera faeces. We developed hypotheses on the ecological mechanisms expected to structure interaction networks, based on plant phylogeny, plant abundance, leaf toughness, leaf nitrogen content and plant metabolomics. We show that plant phylogenetic relationships and species abundance have the greatest explanatory power regarding the structure of the ecological networks. Moreover, we found that leaf nitrogen content is a key determinant of interactions in warmer environments, while phenolic compounds and tannins are more important in colder environments, suggesting that determinants of species interactions can shift along environmental gradients. With this work, we propose an approach to study the mechanisms that structure the way species interact with each other between bioregions and ecosystems. [ABSTRACT FROM AUTHOR]

Microclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high‐resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open‐access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution. [ABSTRACT FROM AUTHOR]

European grasslands face strong declines in extent and quality. Many grassland types are priority habitats for national and European conservation strategies. Countrywide, high spatial resolution maps of their distribution are often lacking. Here, we modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. First, we applied ensemble models to provide distribution maps of the individual habitat types, using training data from various sources. Copernicus Sentinel satellite imagery and variables describing climate, soil and topography were used as predictors. The performance of these models was assessed based on the true skill statistics with a split‐sampling of the data. Second, the individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert‐based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat‐type proportions with extrapolations from field surveys. Most individual maps had useful to excellent predictive performance (TSS ≥ 0.6). For most grid cells in the combined maps, the most and second most likely habitat types were either ecologically closely related or representing two grassland types along a nutrient gradient. The same was true for omission errors. We found good agreement between the predicted and estimated proportions from field surveys. The area of raised bogs appears to be underestimated, while dry grasslands showed highest agreement. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, thereby providing the foundation for diverse conservation applications. A particular challenge remains in capturing the transition from nutrient‐poor to nutrient‐rich grasslands, which is highly important for biodiversity conservation. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are statistical tools that relate species observations to environmental conditions to retrieve ecological niches and predict species' potential geographic distributions. The quality and robustness of SDMs clearly depend on good modelling practices including ascertaining the ecological relevance of predictors for the studied species and choosing an appropriate spatial resolution (or 'grain size'). While past studies showed improved model performance with increasing resolution for sessile organisms, there is still no consensus regarding how inappropriate resolution of predictors can impede understanding and mapping of multiple facets of diversity. Here, we modelled the distribution of 1180 plant species across the European Alps for two sets of predictors (climate and soil) at resolutions ranging from 100‐m to 40‐km. We assessed predictors' importance for each resolution, calculated taxonomic (TD), relative phylogenetic (rPD) and functional diversity (rFD) accordingly, and compared the resulting diversities across space. In accordance with previous studies, we found the predictive performance to generally decrease with decreasing predictor resolution. Overall, multifaceted diversity was found to be strongly affected by resolution, particularly rPD, as exhibited by weak to average linear relationships between 100‐m and 1‐km resolutions (0.13 ≤ R2 ≤ 0.57). Our results demonstrate the necessity of using highly resolved predictors to explain and predict sessile species distributions, especially in mountain environments. Using coarser resolution predictors might cause multifaceted diversity to be strongly mispredicted, with important consequences for biodiversity management and conservation. [ABSTRACT FROM AUTHOR]

Theory predicts that a large fraction of phytochemical diversity—the richness of individual chemical compounds produced by plants—governs the complexity of interactions between plants and their herbivores. While the effect of specific classes of chemical compounds on plant resistance against herbivores has been largely documented, the effect of community‐level variation in phytochemical diversity on plant–herbivore interactions has so far received minimal consideration.We hypothesized that plant communities bearing on average higher levels of phytochemical diversity should sustain lower herbivory rates, overall. Yet, the magnitude of this effect could vary across different environmental conditions, potentially because of climate‐mediated effects on phytochemical production and changes in herbivore community richness and composition.To address these hypotheses, we used previous knowledge of species‐level phytochemical make‐up for more than 400 plant species of the Swiss Alps. Using common garden experiments, we estimated season‐wide herbivore damage on low (average 3,500 unique molecules) and high (average 4,500 unique molecules) phytochemical diversity plant communities that were planted in the colline, mountain and alpine vegetation sites along two elevation transects in the Alps.We found that high phytochemical diversity plant communities showed reduced levels of herbivore damage in the colline (low elevation) sites, but this pattern reversed in the alpine (high elevation) sites. Our results suggest that the outcome of phytochemical diversity on plant–herbivore interactions depends on the characteristics of the local herbivore communities, together with trade‐offs between chemical defences and other plant traits (i.e. physical defences and plant palatability).Synthesis. Phytochemical diversity is a key component of functional diversity, influencing community composition and dynamics. We show that the effect of phytochemical diversity on herbivory is environmental‐dependent, generating ecological switches when moving from low to high elevation. Through upward movement of plants under climate change, phytochemical community structure will be likely modified, ultimately disrupting local community assembly processes. [ABSTRACT FROM AUTHOR]

Ecological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately. [ABSTRACT FROM AUTHOR]

Aim: Ecological gradients are expected to be associated with structural rewiring of species interaction networks. The study of network structures along geographic and ecological gradients, however, remains marginal because documenting species interactions at multiple sites is a methodological challenge. Here, we aimed to study the structural variation in plant–herbivore interaction networks along elevational gradients using molecular metabarcoding. Location: European Alps. Taxon: Plant and Orthopteran herbivores. Methods: We used a standardized DNA metabarcoding method applied to Orthopteran faeces to document the structure of 48 networks of species interactions across six elevational gradients. We examined how structural properties of plant–Orthoptera networks reflecting specialization and robustness vary with elevation. We compared observed variation to null models to account for differences in network size. Results: We found an increase in the levels of generality and nestedness with decreasing temperature, and the correlation was stronger than in null models. These relationships corresponded to greater robustness and reduced the importance of specific keystone species in alpine habitats compared to lowland grasslands. Main conclusions: In cold environments, plant–herbivore networks are wired in a way that may reinforce the resilience of the system to species extinction. Documenting ecological networks along ecological gradients allows a better understanding of the influence of climate on the structure of ecological communities. [ABSTRACT FROM AUTHOR]

Herbivory and plant defenses exhibit a coupled decline along elevation gradients. However, the current ecological equilibrium could be disrupted under climate change, with a faster upward range shift of animals than plants. Here, we experimentally simulated this upward herbivore range shift by translocating low-elevation herbivore insects to alpine grasslands. We report that the introduction of novel herbivores and increased herbivory disrupted the vertical functional organization of the plant canopy. By feeding preferentially on alpine plants with functional traits matching their low-elevation host plants, herbivores reduced the biomass of dominant alpine plant species and favored encroachment of herbivore-resistant small-stature plant species, inflating species richness. Supplementing a direct effect of temperature, novel biotic interactions represent a neglected but major driver of ecosystem modifications under climate change. [ABSTRACT FROM AUTHOR]

Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we propose to derive environmental data layers by mapping ecological indicator values in space. We combined ~6 million plant occurrences with expert‐based plant ecological indicator values (EIVs) of 3600 species in Switzerland. EIVs representing local soil properties (pH, moisture, moisture variability, aeration, humus and nutrients) and climatic conditions (continentality, light) were modelled at 93 m spatial resolution with the Random Forest algorithm and 16 predictors representing meso‐climate, land use, topography and geology. Models were evaluated and predictions of EIVs were compared with soil inventory data. We mapped each EIV separately and evaluated EIV importance in explaining the distribution of 500 plant species using SDMs with a set of 30 environmental predictors. Finally, we tested how they improve an ensemble of SDMs compared to a standard set of predictors for ca 60 plant species. All EIV models showed excellent performance (|r| > 0.9) and predictions were correlated reasonably (|r| > 0.4) to soil properties measured in the field. Resulting EIV maps were among the most important predictors in SDMs. Also, in ensemble SDMs overall predictive performance increased, mainly through improved model specificity reducing species range overestimation. Combining large citizen science databases to expert‐based EIVs is a powerful and cost–effective approach for generalizing local edaphic and climatic conditions over large areas. Producing ecologically meaningful predictors is a first step for generating better predictions of species distribution which is of main importance for decision makers in conservation and environmental management projects. [ABSTRACT FROM AUTHOR]

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity–productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity–insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape‐scale. Here, we provide a landscape‐scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape‐scale grassland productivity. [ABSTRACT FROM AUTHOR]

Plants protect themselves against herbivore attacks with physical traits and toxic secondary metabolites. Levels of plant defences and herbivore performance might shift under climate warming, particularly in alpine habitats, where herbivore pressure is currently low. Plant responses to warming should be driven by species‐specific shifts in physical and chemical defence traits.We investigated the association between plant leaf physical and chemical traits and herbivory under current and warmer climates in three grasslands along a subalpine to alpine gradient. Specifically, we measured the rate of in situ natural herbivory, and performed bioassays to measure overall plant species‐level resistance using the extreme generalist non‐native caterpillar Spodoptera littoralis. We simulated warmer conditions by using open‐top chambers and assessed the effect of warming on leaf physical and chemical traits, and how trait changes affect caterpillar performance.Natural herbivory and caterpillar performance were associated with plant physical traits, including specific leaf area, and with ordination axes representing dimensions of the plant chemical profile. We found that the warming treatment independently decreased the number of distinct chemical compounds per species, and marginally increased specific leaf area. Changes in leaf functional traits were not systematically associated with changes in caterpillar performance.Synthesis. Plant physical traits and chemical profiles are both related to natural herbivory and plant resistance against Spodoptera littoralis. While leaf physical and chemical traits of high elevation plants were modified by the warming treatment, these changes did not result in predictable effects on plant resistance against herbivores. [ABSTRACT FROM AUTHOR]

Abstract: Invasive alien plants (IAP) are a threat to biodiversity worldwide. Understanding and anticipating invasions allow for more efficient management. In this regard, predicting potential invasion risks by IAPs is essential to support conservation planning into areas of high conservation value (AHCV) such as sites exhibiting exceptional botanical richness, assemblage of rare, and threatened and/or endemic plant species. Here, we identified AHCV in Georgia, a country showing high plant richness, and assessed the susceptibility of these areas to colonization by IAPs under present and future climatic conditions. We used actual protected areas and areas of high plant endemism (identified using occurrences of 114 Georgian endemic plant species) as proxies for AHCV. Then, we assessed present and future potential distribution of 27 IAPs using species distribution models under four climate change scenarios and stacked single‐species potential distribution into a consensus map representing IAPs richness. We evaluated present and future invasion risks in AHCV using IAPs richness as a metric of susceptibility. We show that the actual protected areas cover only 9.4% of the areas of high plant endemism in Georgia. IAPs are presently located at lower elevations around the large urban centers and in western Georgia. We predict a shift of IAPs toward eastern Georgia and higher altitudes and an increased susceptibility of AHCV to IAPs under future climate change. Our study provides a good baseline for decision makers and stakeholders on where and how resources should be invested in the most efficient way to protect Georgia's high plant richness from IAPs. [ABSTRACT FROM AUTHOR]

Coral reefs and their associated fauna are largely impacted by ongoing climate change. Unravelling species responses to past climatic variations might provide clues on the consequence of ongoing changes. Here, we tested the relationship between changes in sea surface temperature and sea levels during the Quaternary and present-day distributions of coral reef fish species. We investigated whether species-specific responses are associated with life-history traits. We collected a database of coral reef fish distribution together with life-history traits for the Indo-Pacific Ocean. We ran species distribution models ( SDMs) on 3,725 tropical reef fish species using contemporary environmental factors together with a variable describing isolation from stable coral reef areas during the Quaternary. We quantified the variance explained independently by isolation from stable areas in the SDMs and related it to a set of species traits including body size and mobility. The variance purely explained by isolation from stable coral reef areas on the distribution of extant coral reef fish species largely varied across species. We observed a triangular relationship between the contribution of isolation from stable areas in the SDMs and body size. Species, whose distribution is more associated with historical changes, occurred predominantly in the Indo-Australian archipelago, where the mean size of fish assemblages is the lowest. Our results suggest that the legacy of habitat changes of the Quaternary is still detectable in the extant distribution of many fish species, especially those with small body size and the most sedentary. Because they were the least able to colonize distant habitats in the past, fish species with smaller body size might have the most pronounced lags in tracking ongoing climate change. [ABSTRACT FROM AUTHOR]

Identifying the main determinants of tropical marine biodiversity is essential for devising appropriate conservation measures mitigating the ongoing degradation of coral reef habitats. Based on a gridded distribution database and phylogenetic information, we compared the phylogenetic structure of assemblages for three tropical reef fish families (Labridae: wrasses, Pomacentridae: damselfishes and Chaetodontidae: butterflyfishes) using the net relatedness (NRI) and nearest taxon (NTI) indices. We then related these indices to contemporary and historical environmental conditions of coral reefs using spatial regression analyses. Higher levels of phylogenetic clustering were found for fish assemblages in the Indo-Australian Archipelago (IAA), and more particularly when considering the NTI index. The phylogenetic structure of the Pomacentridae, and to a lower extent of the Chaeotodontidae and Labridae, was primarily associated with the location of refugia during the Quaternary period. Phylogenetic clustering in the IAA may partly result from vicariance events associated with coral reef fragmentation during the glacial periods of the Quaternary. Variation in the patterns among fish families further suggest that dispersal abilities may have interacted with past habitat availability in shaping the phylogenetic structure of tropical reef fish assemblages. [ABSTRACT FROM AUTHOR]

Species currently track suitable abiotic and biotic conditions under ongoing climate change. Adjustments of trophic interactions may provide a mechanism for population persistence, an option that is rarely included in model projections. Here, we model the future distribution, of butterflies in the western Alps of Switzerland under climate change, simulating potential diet expansion resulting from adaptive behavior or new host opportunities. We projected the distribution of 60 butterfly and 298 plant species with species distribution models (SDMs) under three climate change scenarios. From known host plants, we allowed a potential diet expansion based on phylogenetic constraints. We assessed whether diet expansion could reduce the rate of expected regional species extinction under climate change. We found that the risk of species extinctions decreased with a concave upward decreasing shape when expanding the host plant range. A diet expansion to even a few phylogenetically closely related host plants would significantly decrease extinction rates. Yet, even when considering expansion toward all plant species available in the study area, the overall regional extinction risk would remain high. Ecological or evolutionary shifts to new host plants may attenuate extinction risk, but the severe decline of suitable abiotic conditions is still expected to drive many species to local extinction. [ABSTRACT FROM AUTHOR]

Coral bleaching events threaten coral reef habitats globally and cause severe declines of local biodiversity and productivity. Related to high sea surface temperatures (SST), bleaching events are expected to increase as a consequence of future global warming. However, response to climate change is still uncertain as future low-latitude climatic conditions have no present-day analogue. Sea surface temperatures during the Eocene epoch were warmer than forecasted changes for the coming century, and distributions of corals during the Eocene may help to inform models forecasting the future of coral reefs. We coupled contemporary and Eocene coral occurrences with information on their respective climatic conditions to model the thermal niche of coral reefs and its potential response to projected climate change. We found that under the RCP8.5 climate change scenario, the global suitability for coral reefs may increase up to 16% by 2100, mostly due to improved suitability of higher latitudes. In contrast, in its current range, coral reef suitability may decrease up to 46% by 2100. Reduction in thermal suitability will be most severe in biodiversity hotspots, especially in the Indo-Australian Archipelago. Our results suggest that many contemporary hotspots for coral reefs, including those that have been refugia in the past, spatially mismatch with future suitable areas for coral reefs posing challenges to conservation actions under climate change. [ABSTRACT FROM AUTHOR]

The article provides insights into the diversity of metabolites produced by plants and how this metabolome varies across different plant species. It explores the concept of plant functional traits and suggests that integrating measurements of the plant metabolome into this concept can offer a better understanding of plant form, function, and ecological context.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes., (© 2020 John Wiley & Sons Ltd.)

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity-productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity-insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape-scale. Here, we provide a landscape-scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape-scale grassland productivity., Competing Interests: The authors declare no competing interests., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns., Competing Interests: We have no competing interests.