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Ongoing climate change is a major threat to biodiversity and impacts on species distributions and abundances are already evident. Heterogenous responses of species due to varying abiotic tolerances and dispersal abilities have the potential to further amplify or ameliorate these impacts through changes in species assemblages. Here we investigate the impacts of climate change on terrestrial bird distributions and, subsequently, on species richness as well as on different aspects of phylogenetic diversity of species assemblages across the globe. We go beyond previous work by disentangling the potential impacts on assemblage phylogenetic diversity of species gains vs. losses under climate change and compare the projected impacts to randomized assemblage changes.
We show that climate change might not only affect species numbers and composition of global species assemblages but could also have profound impacts on assemblage phylogenetic diversity, which, across extensive areas, differ significantly from random changes. Both the projected impacts on phylogenetic diversity and on phylogenetic structure vary greatly across the globe. Projected increases in the evolutionary history contained within species assemblages, associated with either increasing phylogenetic diversification or clustering, are most frequent at high northern latitudes. By contrast, projected declines in evolutionary history, associated with increasing phylogenetic over-dispersion or homogenisation, are projected across all continents.
The projected widespread changes in the phylogenetic structure of species assemblages show that changes in species richness do not fully reflect the potential threat from climate change to ecosystems. Our results indicate that the most severe changes to the phylogenetic diversity and structure of species assemblages are likely to be caused by species range shifts rather than range reductions and extinctions. Our findings highlight the importance of considering diverse measures in climate impact assessments and the value of integrating species-specific responses into assessments of entire community changes.
The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model.
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.
The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols
(2016)
The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over two decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. Here we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copy-right work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce, or limit each other.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.
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.