Regional uniqueness of tree species composition and response to forest loss and climate change.

The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change.

Positive feedbacks and alternative stable states in forest leaf types.

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4-43% higher growth rates, 14-17% higher survival rates and 4-7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.

Multispecies deep learning using citizen science data produces more informative plant community models.

In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, using deep neural networks (DNNs) and ubiquitous citizen science data. Based on 6.7 M observations, we jointly model the distributions of 2477 plant species and species aggregates across Switzerland with an ensemble of DNNs built with different cost functions. We find that, compared to commonly-used approaches, multispecies DNNs predict species distributions and especially community composition more accurately. Moreover, their design allows investigation of understudied aspects of ecology. Including seasonal variations of observation probability explicitly allows approximating flowering phenology; reweighting predictions to mirror cover-abundance allows mapping potentially canopy-dominant tree species nationwide; and projecting DNNs into the future allows assessing how distributions, phenology, and dominance may change. Given their skill and their versatility, multispecies DNNs can refine our understanding of the distribution of plants and well-sampled taxa in general.

Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic.

The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models, and maps the geographic patterns of community-level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing toward conservation efforts for Arctic plant diversity in the Western Siberian Arctic. Western Siberian Arctic, Russia. We investigated the relative importance of environmental and anthropogenic predictors of community-level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non-vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. We found that the mean community-level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South-West to North-East, which can be well explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate predictors, potentially indicating a lasting impact of ancient climate on tundra plant species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. We suggest that while community-level plant species richness is mostly driven by environmental factors, an improved spatial sampling will be needed to robustly and more precisely assess the impact of human activities on community-level species richness patterns. Our approach and results can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions.

The Behavior of Planktonic Copepods Minimizes the Entry of Microplastics in Marine Food Webs.

The entry of microplastics (MPs) into marine food webs is a major environmental concern. We investigated how the behavior of planktonic copepods influences the risk of MPs to enter marine food webs by applying a trait-based approach and by combining experiments (bottle incubations and video observations) with biogeographical analyses. We aimed to evaluate which type of feeding behavior is most risky in terms of MP ingestion and which marine geographical areas are more susceptible to MP ingestion by planktonic copepods. We used different species as models of the main foraging behaviors in planktonic copepods: feeding-current, cruising, ambush, and mixed behavior feeding. All behaviors showed a similarly low risk of MP ingestion, up to 1 order of magnitude lower than for similar-sized microalgae. We did not observe any influence of the prey type or MP size (8 and 20 µm) on MP ingestion for any of the behaviors. By mapping the global distribution of feeding behaviors, we showed that feeding-current feeding is the most common behavior, but the risk of MP ingestion remains equally low across the global ocean, independently of the predominant behavior. Overall, our results suggest a low risk of MP ingestion by planktonic copepods and therefore a minimal risk of trophic transfer of MPs via marine pelagic copepods in marine ecosystems.

Soil-plant interactions modulated water availability of Swiss forests during the 2015 and 2018 droughts.

Central Europe has been experiencing unprecedented droughts during the last decades, stressing the decrease in tree water availability. However, the assessment of physiological drought stress is challenging, and feedback between soil and vegetation is often omitted because of scarce belowground data. Here we aimed to model Swiss forests' water availability during the 2015 and 2018 droughts by implementing the mechanistic soil-vegetation-atmosphere-transport (SVAT) model LWF-Brook90 taking advantage of regionalized depth-resolved soil information. We calibrated the model against soil matric potential data measured from 2014 to 2018 at 44 sites along a Swiss climatic and edaphic drought gradient. Swiss forest soils' storage capacity of plant-available water ranged from 53 mm to 341 mm, with a median of 137 ± 42 mm down to the mean potential rooting depth of 1.2 m. Topsoil was the primary water source. However, trees switched to deeper soil water sources during drought. This effect was less pronounced for coniferous trees with a shallower rooting system than for deciduous trees, which resulted in a higher reduction of actual transpiration (transpiration deficit) in coniferous trees. Across Switzerland, forest trees reduced the transpiration by 23% (compared to potential transpiration) in 2015 and 2018, maintaining annual actual transpiration comparable to other years. Together with lower evaporative fluxes, the Swiss forests did not amplify the blue water deficit. The 2018 drought, characterized by a higher and more persistent transpiration deficit than in 2015, triggered widespread early wilting across Swiss forests that was better predicted by the SVAT-derived mean soil matric potential in the rooting zone than by climatic predictors. Such feedback-driven quantification of ecosystem water fluxes in the soil-plant-atmosphere continuum will be crucial to predicting physiological drought stress under future climate extremes.

Unpalatable Plastic: Efficient Taste Discrimination of Microplastics in Planktonic Copepods.

Planktonic copepods are the most abundant animals in the ocean and key players in global biochemical processes. Recent modeling suggests that zooplankton ingestion of microplastics (MPs) can disrupt the biological carbon pump and accelerate a global loss of oceanic oxygen. Here we investigate the behavioral responses and ingestion rates of a model feeding-current generating copepod when exposed to microplastics of different characteristics by small-scale video observations and bottle incubations. We found that copepods rejected 80% of the microplastics after touching them with their mouth parts, in essence exhibiting a kind of taste discrimination. High rejection rates of microplastics were independent of polymer type, shape, presence of biofilms, or sorbed pollutant (pyrene), indicating that microplastics are unpalatable for feeding-current feeding copepods and that post-capture taste discrimination is a main sensorial mechanism in the rejection of microplastics. In an ecological context, taking into account the behaviors of planktonic copepods and the concentrations of microplastics found in marine waters, our results suggest a low risk of microplastic ingestion by zooplankton and a low impact of microplastics on the vertical exportation of fecal pellets.

An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales.

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate. We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo-absence selections to map the species at a high spatial resolution and intersect it with the generated polygons. We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high-resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south-western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement. By efficiently producing high-resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.

Plant community impact on productivity: Trait diversity or key(stone) species effects?

Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species' individual effects on ecosystem functioning in complement to community-level measures.

Large-scale early-wilting response of Central European forests to the 2018 extreme drought.

The combination of drought and heat affects forest ecosystems by deteriorating the health of trees, which can lead to large-scale die-offs with consequences on biodiversity, the carbon cycle, and wood production. It is thus crucial to understand how drought events affect tree health and which factors determine forest susceptibility and resilience. We analyze the response of Central European forests to the 2018 summer drought with 10 × 10 m satellite observations. By associating time-series statistics of the Normalized Difference Vegetation Index (NDVI) with visually classified observations of early wilting, we show that the drought led to early leaf-shedding across 21,500 ± 2,800 km2 , in particular in central and eastern Germany and in the Czech Republic. High temperatures and low precipitation, especially in August, mostly explained these large-scale patterns, with small- to medium-sized trees, steep slopes, and shallow soils being important regional risk factors. Early wilting revealed a lasting impact on forest productivity, with affected trees showing reduced greenness in the following spring. Our approach reliably detects early wilting at the resolution of large individual crowns and links it to key environmental drivers. It provides a sound basis to monitor and forecast early-wilting responses that may follow the droughts of the coming decades.

The productivity-biodiversity relationship varies across diversity dimensions.

Understanding the processes that drive the dramatic changes in biodiversity along the productivity gradient remains a major challenge. Insight from simple, bivariate relationships so far has been limited. We combined >11,000 community plots in the French Alps with a molecular phylogeny and trait information for >1200 plant species to simultaneously investigate the relationships between all major biodiversity dimensions and satellite-sensed productivity. Using an approach that tests for differential effects of species dominance, species similarity and the interplay between phylogeny and traits, we demonstrate that unimodal productivity-biodiversity relationships only dominate for taxonomic diversity. In forests, trait and phylogenetic diversity typically increase with productivity, while in grasslands, relationships shift from unimodal to declining with greater land-use intensity. High productivity may increase trait/phylogenetic diversity in ecosystems with few external constraints (forests) by promoting complementary strategies, but under external constraints (managed grasslands) successful strategies are similar and thus the best competitors may be selected.

Climate change has altered zooplankton-fuelled carbon export in the North Atlantic.

Marine plankton have been conspicuously affected by recent climate change, responding with profound spatial relocations and shifts in the timing of their seasonal occurrence. These changes directly affect the global carbon cycle by altering the transport of organic material from the surface ocean to depth, with consequences that remain poorly understood. We investigated how distributional and abundance changes of copepods, the dominant group of zooplankton, have affected biogenic carbon cycling. We used trait-based, mechanistic models to estimate the magnitude of carbon transported downward through sinking faecal pellets, daily vertical migration and seasonal hibernation at depth. From such estimates for over 200,000 community observations in the northern North Atlantic we found carbon flux increased along the northwestern boundary of the study area and decreased in the open northern North Atlantic during the past 55 years. These changes in export were primarily associated with changes in copepod biomass, driven by shifting distributions of abundant, large-bodied species. Our findings highlight how recent climate change has affected downward carbon transport by altering copepod community structure and demonstrate how carbon fluxes through plankton communities can be mechanistically implemented in next-generation biogeochemical models with size-structured representations of zooplankton communities.

Trait biogeography of marine copepods - an analysis across scales.

Functional traits, rather than taxonomic identity, determine the fitness of individuals in their environment: traits of marine organisms are therefore expected to vary across the global ocean as a function of the environment. Here, we quantify such spatial and seasonal variations based on extensive empirical data and present the first global biogeography of key traits (body size, feeding mode, relative offspring size and myelination) for pelagic copepods, the major group of marine zooplankton. We identify strong patterns with latitude, season and between ocean basins that are partially (c. 50%) explained by key environmental drivers. Body size, for example decreases with temperature, confirming the temperature-size rule, but surprisingly also with productivity, possibly driven by food-chain length and size-selective predation. Patterns unrelated to environmental predictors may originate from phylogenetic clustering. Our maps can be used as a test-bed for trait-based mechanistic models and to inspire next-generation biogeochemical models.

The predictive skill of species distribution models for plankton in a changing climate.

Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real-world are rare. Here, we use data from the Continuous Plankton Recorder program, one of the longest running and most extensive marine biological monitoring programs, to investigate the reliability of predicted plankton distributions. We apply three commonly used SDMs to 20 representative plankton species, including copepods, diatoms, and dinoflagellates, all found in the North Atlantic and adjacent seas. We fit the models to decadal subsets of the full (1958-2012) dataset, and then use them to predict both forward and backward in time, comparing the model predictions against the corresponding observations. The probability of correctly predicting presence was low, peaking at 0.5 for copepods, and model skill typically did not outperform a null model assuming distributions to be constant in time. The predicted prevalence increasingly differed from the observed prevalence for predictions with more distance in time from their training dataset. More detailed investigations based on four focal species revealed that strong spatial variations in skill exist, with the least skill at the edges of the distributions, where prevalence is lowest. Furthermore, the scores of traditional single-value model performance metrics were contrasting and some implied overoptimistic conclusions about model skill. Plankton may be particularly challenging to model, due to its short life span and the dispersive effects of constant water movements on all spatial scales, however there are few other studies against which to compare these results. We conclude that rigorous model validation, including comparison against null models, is essential to assess the robustness of projections of marine planktonic species under climate change.