Genomic evidence for the widespread presence of GH45 cellulases among soil invertebrates.

Lignocellulose is a major component of vascular plant biomass. Its decomposition is crucial for the terrestrial carbon cycle. Microorganisms are considered primary decomposers, but evidence increases that some invertebrates may also decompose lignocellulose. We investigated the taxonomic distribution and evolutionary origins of GH45 hydrolases, important enzymes for the decomposition of cellulose and hemicellulose, in a collection of soil invertebrate genomes. We found that these genes are common in springtails and oribatid mites. Phylogenetic analysis revealed that cellulase genes were acquired early in the evolutionary history of these groups. Domain architectures and predicted 3D enzyme structures indicate that these cellulases are functional. Patterns of presence and absence of these genes across different lineages prompt further investigation into their evolutionary and ecological benefits. The ubiquity of cellulase genes suggests that soil invertebrates may play a role in lignocellulose decomposition, independently or in synergy with microorganisms. Understanding the ecological and evolutionary implications might be crucial for understanding soil food webs and the carbon cycle.

Climate regulation processes are linked to the functional composition of plant communities in European forests, shrublands, and grasslands.

Terrestrial ecosystems affect climate by reflecting solar irradiation, evaporative cooling, and carbon sequestration. Yet very little is known about how plant traits affect climate regulation processes (CRPs) in different habitat types. Here, we used linear and random forest models to relate the community-weighted mean and variance values of 19 plant traits (summarized into eight trait axes) to the climate-adjusted proportion of reflected solar irradiation, evapotranspiration, and net primary productivity across 36,630 grid cells at the European extent, classified into 10 types of forest, shrubland, and grassland habitats. We found that these trait axes were more tightly linked to log evapotranspiration (with an average of 6.2% explained variation) and the proportion of reflected solar irradiation (6.1%) than to net primary productivity (4.9%). The highest variation in CRPs was explained in forest and temperate shrubland habitats. Yet, the strength and direction of these relationships were strongly habitat-dependent. We conclude that any spatial upscaling of the effects of plant communities on CRPs must consider the relative contribution of different habitat types.

Projected climate change impacts on the phylogenetic diversity of the world's terrestrial birds: more than species numbers.

Ongoing climate change is a major threat to biodiversity. As abiotic tolerances and dispersal abilities vary, species-specific responses have the potential to further amplify or ameliorate the ensuing impacts on species assemblages. Here, we investigate the effects of climate change on species distributions across non-marine birds, quantifying its projected impact on species richness (SR) as well as on different aspects of phylogenetic diversity globally. Going beyond previous work, we disentangle the potential impacts of species gains versus losses on assemblage-level phylogenetic diversity under climate change and compare the projected impacts to randomized assemblage changes. We show that beyond its effects on SR, climate change could have profound impacts on assemblage-level phylogenetic diversity and composition, which differ significantly from random changes and among regions. Though marked species losses are most frequent in tropical and subtropical areas in our projections, phylogenetic restructuring of species communities is likely to occur all across the globe. Furthermore, our results indicate that the most severe changes to the phylogenetic diversity of local assemblages are likely to be caused by species range shifts and local species gains rather than range reductions and extinctions. Our findings highlight the importance of considering diverse measures in climate impact assessments.

Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last century.

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.

Combined impacts of future climate-driven vegetation changes and socioeconomic pressures on protected areas in Africa.

Africa's protected areas (PAs) are the last stronghold of the continent's unique biodiversity, but they appear increasingly threatened by climate change, substantial human population growth, and land-use change. Conservation planning is challenged by uncertainty about how strongly and where these drivers will interact over the next few decades. We investigated the combined future impacts of climate-driven vegetation changes inside African PAs and human population densities and land use in their surroundings for 2 scenarios until the end of the 21st century. We used the following 2 combinations of the shared socioeconomic pathways (SSPs) and representative greenhouse gas concentration pathways (RCPs): the "middle-of-the-road" scenario SSP2-RCP4.5 and the resource-intensive "fossil-fueled development" scenario SSP5-RCP8.5. Climate change impacts on tree cover and biome type (i.e., desert, grassland, savanna, and forest) were simulated with the adaptive dynamic global vegetation model (aDGVM). Under both scenarios, most PAs were adversely affected by at least 1 of the drivers, but the co-occurrence of drivers was largely region and scenario specific. The aDGVM projections suggest considerable climate-driven tree cover increases in PAs in today's grasslands and savannas. For PAs in West Africa, the analyses revealed climate-driven vegetation changes combined with hotspots of high future population and land-use pressure. Except for many PAs in North Africa, future decreases in population and land-use pressures were rare. At the continental scale, SSP5-RCP8.5 led to higher climate-driven changes in tree cover and higher land-use pressure, whereas SSP2-RCP4.5 was characterized by higher future population pressure. Both SSP-RCP scenarios implied increasing challenges for conserving Africa's biodiversity in PAs. Our findings underline the importance of developing and implementing region-specific conservation responses. Strong mitigation of future climate change and equitable development scenarios would reduce ecosystem impacts and sustain the effectiveness of conservation in Africa.

Las áreas protegidas (AP) de África son el último bastión de la biodiversidad distintiva del continente, pero cada vez están más amenazadas por el cambio climático, crecimiento sustancial de la población humana y cambio de uso de suelo. La planificación de la conservación enfrenta el reto de la incertidumbre de cuan fuerte y donde interactuarán estos factores a lo largo de las siguientes décadas. Investigamos los impactos futuros combinados de los cambios en la vegetación impulsados por el clima dentro de AP africanas y las densidades de población humana y el uso de suelo en sus alrededores en 2 escenarios hasta el final del siglo 21. Utilizamos las siguientes 2 combinaciones de las trayectorias socioeconómicas compartidas (SSP) y las trayectorias representativas de concentración de gases de invernadero (RCP): el escenario de "mitad del camino" SSP2-RCP4.5 y el escenario recurso intensivo "desarrollo impulsado por combustibles fósiles" SSP5-RCP8.5. Los impactos del cambio climático sobre la cobertura de árboles y el tipo de bioma (i. e., desierto, pastizal, sabana y bosque) fueron simulados con el modelo vegetación global dinámica adaptativo (aDGVM). En ambos escenarios, la mayoría de las AP fueron afectadas adversamente por lo menos por 1 de los factores, pero la coocurrencia de los factores fue mayoritariamente específica por región y escenario. Las proyecciones de MVGDa sugieren incrementos considerables en la cobertura de árboles impulsados por el clima en las AP en pastizales y sabanas actuales. Para AP en África Occidental, los análisis revelaron cambios en la vegetación impulsados por el clima combinados con sitios clave con numerosa población y gran presión de uso de suelo en el futuro. Excepto en muchos PA de África del Norte, los decrementos en la población y presiones de uso de suelo en el futuro fueron raros. A escala continental, SSP5-RCP8.5 condujo a mayores cambios impulsados por el clima en la cobertura arbórea y en la presión de cambio de uso de suelo, mientras que SSP5-RCP8.5 se caracterizó por una mayor presión demográfica en el futuro. Ambos escenarios SSP-RCP implicaron mayores retos para la conservación de la biodiversidad en AP africanas. Nuestros hallazgos subrayan la importancia de desarrollar e implementar respuestas de conservación específicas para cada región. Medidas sólidas para la mitigación del cambio climático así como escenarios de desarrollo equitativo podrían reducir los impactos en el ecosistema y sustentar la efectividad de la conservación en África.

Forest responses to last-millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity.

Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under-constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial-scale hydroclimate variability, by comparing dendroclimatic and pollen-inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model-data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world.

Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot.

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61-72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies.

Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high-resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant-physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between -8 to 11% (RCP 4.5) and -22 to -6% (RCP8.5). Simulated biome changes lacked consistent large-scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.

A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems.

Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projections how they respond to environmental changes challenging. A suitable way are trait-based approaches, by distinguishing between response traits that determine the resistance of species to environmental changes and effect traits that are relevant for species' interactions, biotic processes, and ecosystem functions. The combination of those approaches with land surface models (LSM) linking the functional community composition to ecosystem functions provides new ways to project the response of ecosystems to environmental changes. With the interdisciplinary project RESPECT, we propose a research framework that uses a trait-based response-effect-framework (REF) to quantify relationships between abiotic conditions, the diversity of functional traits in communities, and associated biotic processes, informing a biodiversity-LSM. We apply the framework to a megadiverse tropical mountain forest. We use a plot design along an elevation and a land-use gradient to collect data on abiotic drivers, functional traits, and biotic processes. We integrate these data to build the biodiversity-LSM and illustrate how to test the model. REF results show that aboveground biomass production is not directly related to changing climatic conditions, but indirectly through associated changes in functional traits. Herbivory is directly related to changing abiotic conditions. The biodiversity-LSM informed by local functional trait and soil data improved the simulation of biomass production substantially. We conclude that local data, also derived from previous projects (platform Ecuador), are key elements of the research framework. We specify essential datasets to apply this framework to other mountain ecosystems.

Bioenergy cropland expansion may offset positive effects of climate change mitigation for global vertebrate diversity.

Climate and land-use change interactively affect biodiversity. Large-scale expansions of bioenergy have been suggested as an important component for climate change mitigation. Here we use harmonized climate and land-use projections to investigate their potential combined impacts on global vertebrate diversity under a low- and a high-level emission scenario. We combine climate-based species distribution models for the world's amphibians, birds, and mammals with land-use change simulations and identify areas threatened by both climate and land-use change in the future. The combined projected effects of climate and land-use change on vertebrate diversity are similar under the two scenarios, with land-use change effects being stronger under the low- and climate change effects under the high-emission scenario. Under the low-emission scenario, increases in bioenergy cropland may cause severe impacts in biodiversity that are not compensated by lower climate change impacts. Under this low-emission scenario, larger proportions of species distributions and a higher number of small-range species may become impacted by the combination of land-use and climate change than under the high-emission scenario, largely a result of bioenergy cropland expansion. Our findings highlight the need to carefully consider both climate and land-use change when projecting biodiversity impacts. We show that biodiversity is likely to suffer severely if bioenergy cropland expansion remains a major component of climate change mitigation strategies. Our study calls for an immediate and significant reduction in energy consumption for the benefit of both biodiversity and to achieve the goals of the Paris Agreement.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Cross-taxa generalities in the relationship between population abundance and ambient temperatures.

Identifying patterns in the effects of temperature on species' population abundances could help develop a general framework for predicting the consequences of climate change across different communities and realms. We used long-term population time series data from terrestrial, freshwater, and marine species communities within central Europe to compare the effects of temperature on abundance across a broad range of taxonomic groups. We asked whether there was an average relationship between temperatures in different seasons and annual abundances of species in a community, and whether species attributes (temperature range of distribution, range size, habitat breadth, dispersal ability, body size, and lifespan) explained interspecific variation in the relationship between temperature and abundance. We found that, on average, warmer winter temperatures were associated with greater abundances in terrestrial communities (ground beetles, spiders, and birds) but not always in aquatic communities (freshwater and marine invertebrates and fish). The abundances of species with large geographical ranges, larger body sizes, and longer lifespans tended to be less related to temperature. Our results suggest that climate change may have, in general, positive effects on species' abundances within many terrestrial communities in central Europe while the effects are less predictable in aquatic communities.

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO2 in individual models.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m-2  yr-1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2 -induced water savings to extend the growing season length. Observed interactive (CO2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites.

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.

Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies.

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2 ] (eCO2 ) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)-nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground-below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C-N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2 , given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections.

The influence of interspecific interactions on species range expansion rates.

Ongoing and predicted global change makes understanding and predicting species' range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.

High economic costs of reduced carbon sinks and declining biome stability in Central American forests.

Tropical forests represent important supporting pillars for society, supplying global ecosystem services (ES), e.g., as carbon sinks for climate regulation and as crucial habitats for unique biodiversity. However, climate change impacts including implications for the economic value of these services have been rarely explored before. Here, we derive monetary estimates for the effect of climate change on climate regulation and habitat services for the forests of Central America. Our results projected ES declines in 24-62% of the study region with associated economic costs of $51-314 billion/year until 2100. These declines particularly affected montane and dry forests and had strong economic implications for Central America's lower-middle income countries (losses of up to 335% gross domestic product). In addition, economic losses were mostly higher for habitat services than for climate regulation. This highlights the need to expand the focus from mere maximization of CO2 sequestration and avoid false incentives from carbon markets.