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Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C–N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.
Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C–N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.
Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m−2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m−2 y−1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.
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 establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
The establishment and maintenance of protected areas(PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values.
Establishing and maintaining protected areas (PAs) is a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting PAs based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences as well as real-time comparison of the outcome. Applying the tool across 1,346 terrestrial PAs, we demonstrate that decision makers frequently face trade-offs among conflicting objectives, e.g., between species protection and ecosystem integrity. Nevertheless, we show that transparent decision support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
(2015)
The vegetation–atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997–2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund–Potsdam–Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of −10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model–data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
(2015)
The vegetation–atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997–2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund–Potsdam–Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of −10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model–data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.
Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species.
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.
The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10 %; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.
The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C–N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C–N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.
Ecological networks are more sensitive to plant than to animal extinction under climate change
(2016)
Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.
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.
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.
Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψww describing the typical ‘well-watered’ leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
Background: The European beech is arguably the most important climax broad-leaved tree species in Central Europe, widely planted for its valuable wood. Here, we report the 542 Mb draft genome sequence of an up to 300-year-old individual (Bhaga) from an undisturbed stand in the Kellerwald-Edersee National Park in central Germany.
Findings: Using a hybrid assembly approach, Illumina reads with short- and long-insert libraries, coupled with long Pacific Biosciences reads, we obtained an assembled genome size of 542 Mb, in line with flow cytometric genome size estimation. The largest scaffold was of 1.15 Mb, the N50 length was 145 kb, and the L50 count was 983. The assembly contained 0.12% of Ns. A Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis retrieved 94% complete BUSCO genes, well in the range of other high-quality draft genomes of trees. A total of 62,012 protein-coding genes were predicted, assisted by transcriptome sequencing. In addition, we are reporting an efficient method for extracting high-molecular-weight DNA from dormant buds, by which contamination by environmental bacteria and fungi was kept at a minimum.
Conclusions: The assembled genome will be a valuable resource and reference for future population genomics studies on the evolution and past climate change adaptation of beech and will be helpful for identifying genes, e.g., involved in drought tolerance, in order to select and breed individuals to adapt forestry to climate change in Europe. A continuously updated genome browser and download page can be accessed from beechgenome.net, which will include future genome versions of the reference individual Bhaga, as new sequencing approaches develop.
The Eastern Steppe of Mongolia is one of the world's largest mostly intact grassland ecosystems and is characterised by a close coupling of societal and natural processes. In this ecosystem, mobility is one of the key characteristics of wildlife and human societies alike. The current economic development of Mongolia is accompanied by extensive societal transformation and changes in nomadic lifestyles, which potentially affects the unique steppe ecosystem and its biodiversity. The changing lifestyles are mainly characterised by rural-urban migration, resulting in reduced mobility of herders and their livestock, and presumably affecting wildlife. The question is how mobility can be fostered under these transformation processes. Time is pressing as a new generation is born which is growing up in urban environments and with new skill sets but a potential loss of the tight connection to nature and the nomadic lifestyle.