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BIOfid is a specialized information service currently being developed to mobilize biodiversity data dormant in printed historical and modern literature and to offer a platform for open access journals on the science of biodiversity. Our team of librarians, computer scientists and biologists produce high-quality text digitizations, develop new text-mining tools and generate detailed ontologies enabling semantic text analysis and semantic search by means of user-specific queries. In a pilot project we focus on German publications on the distribution and ecology of vascular plants, birds, moths and butterflies extending back to the Linnaeus period about 250 years ago. The three organism groups have been selected according to current demands of the relevant research community in Germany. The text corpus defined for this purpose comprises over 400 volumes with more than 100,000 pages to be digitized and will be complemented by journals from other digitization projects, copyright-free and project-related literature. With TextImager (Natural Language Processing & Text Visualization) and TextAnnotator (Discourse Semantic Annotation) we have already extended and launched tools that focus on the text-analytical section of our project. Furthermore, taxonomic and anatomical ontologies elaborated by us for the taxa prioritized by the project’s target group - German institutions and scientists active in biodiversity research - are constantly improved and expanded to maximize scientific data output. Our poster describes the general workflow of our project ranging from literature acquisition via software development, to data availability on the BIOfid web portal (http://biofid.de/), and the implementation into existing platforms which serve to promote global accessibility of biodiversity data.
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.
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 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.
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.
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.
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.
Die Bestände des in Deutschland stark gefährdeten Sand-Zwerggrases Mibora minima, für deren Erhalt das Land Hessen eine besondere Verantwortung trägt, gehen seit vielen Jahren zurück. In dieser Arbeit wurden als Beitrag zum Artenhilfsprogramm der Botanischen Vereinigung für Naturschutz in Hessen (BVNH) die noch vorhandenen Populationen erfasst sowie die botanischen und edaphischen Gegebenheiten an den Standorten untersucht. Dabei wurde durch Vergleich von Flächen mit und ohne Bewuchs des Zwerggrases der Frage nachgegangen, ob und inwieweit die Verbreitung der Art durch die Beschaffenheit und Nährstoffversorgung des Bodens bestimmt wird. Es wurde ein weiterer deutlicher Rückgang der südhessischen Populationen um etwa 60 % seit 1999 festgestellt, der am stärksten die Standorte um Mörfelden-Walldorf betrifft. Dagegen haben sich die Bestände bei Rüsselsheim-Königstädten möglicherweise durch Pflegemaßnahmen stabilisiert. Ein bestimmender Einfluss edaphischer Parameter auf die Verteilung der Art innerhalb der kalkfreien Flugsande konnte nicht festgestellt werden. Der indigene floristische Status der Art wird in Frage gestellt und stattdessen ihre Einstufung als Epökophyt westmediterraner Herkunft angenommen.
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.
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.
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.
Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in “normal” and “hosing” experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The “hosing” experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the “normal” experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems.
Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used.
Location: Global land, excluding Antarctica.
Taxon: Amphibians, birds and mammals.
Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning.
Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type.
Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.
Tree migration-rates : narrowing the gap between inferred post-glacial rates and projected rates
(2013)
Faster-than-expected post-glacial migration rates of trees have puzzled ecologists for a long time. In Europe, post-glacial migration is assumed to have started from the three southern European peninsulas (southern refugia), where large areas remained free of permafrost and ice at the peak of the last glaciation. However, increasing palaeobotanical evidence for the presence of isolated tree populations in more northerly microrefugia has started to change this perception. Here we use the Northern Eurasian Plant Macrofossil Database and palaeoecological literature to show that post-glacial migration rates for trees may have been substantially lower (60–260 m yr–1) than those estimated by assuming migration from southern refugia only (115–550 m yr–1), and that early-successional trees migrated faster than mid- and late-successional trees. Post-glacial migration rates are in good agreement with those recently projected for the future with a population dynamical forest succession and dispersal model, mainly for early-successional trees and under optimal conditions. Although migration estimates presented here may be conservative because of our assumption of uniform dispersal, tree migration-rates clearly need reconsideration. We suggest that small outlier populations may be a key factor in understanding past migration rates and in predicting potential future range-shifts. The importance of outlier populations in the past may have an analogy in the future, as many tree species have been planted beyond their natural ranges, with a more beneficial microclimate than their regional surroundings. Therefore, climate-change-induced range-shifts in the future might well be influenced by such microrefugia.
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.
Historically, the expansion of soy plantations has been a major driver of land-use/cover change (LUCC) in Brazil. While a series of recent public actions and supply-chain commitments reportedly curbed the replacement of forests by soy, the expansion of the agricultural commodity still poses a considerable threat to the Amazonian and Cerrado biomes. Identification of areas under high risk of soy expansion is thus paramount to assist conservation efforts in the region. We mapped the areas suitable for undergoing transition to soy plantations in the Legal Amazon with a machine-learning approach adopted from the ecological modeling literature. Simulated soy expansion for the year 2014 exhibited favorable validation scores compared to other LUCC models. We then used our model to simulate how potential future infrastructure improvements would affect the 2014 probabilities of soy occurrence in the region. In addition to the 2.3 Mha of planted soy in the Legal Amazon in 2014, our model identified another 14.7 Mha with high probability of soy conversion in the region given the infrastructure conditions at that time. Out of those, pastures and forests represented 9.8 and 0.4 Mha, respectively. Under the new infrastructure scenarios simulated, the Legal Amazonian area under high risk of soy conversion increased by up to 2.1 Mha (14.6%). These changes led to up to 11.4 and 51.4% increases in the high-risk of conversion areas of pastures and forests, respectively. If conversion occurs in the identified high-risk areas, at least 4.8 Pg of CO2 could be released into the atmosphere, a value that represents 10 times the total CO2 emissions of Brazil in 2014. Our results highlight the importance of targeting conservation policies and enforcement actions, including the Soy Moratorium, to mitigate future forest cover loss associated with infrastructure improvements in the region.
In old and heavily weathered soils, the availability of P might be so small that the primary production of plants is limited. However, plants have evolved several mechanisms to actively take up P from the soil or mine it to overcome this limitation. These mechanisms involve the active uptake of P mediated by mycorrhiza, biotic de-occlusion through root clusters, and the biotic enhancement of weathering through root exudation. The objective of this paper is to investigate how and where these processes contribute to alleviate P limitation on primary productivity. To do so, we propose a process-based model accounting for the major processes of the carbon, water, and P cycle including chemical weathering at the global scale. We use simulation experiments to assess the relative importance of the different uptake mechanisms to alleviate P limitation on biomass production. Implementing P limitation on biomass synthesis allows the assessment of the efficiencies of biomass production across different ecosystems.
We find that active P-uptake is an essential mechanism for sustaining P availability on long time scales, whereas biotic de-occlusion might serve as a buffer on time scales shorter than 10 000 yr. Although active P uptake is essential for reducing P losses by leaching, humid lowland soils reach P limitation after around 100 000 yr of soil evolution. Given the generalized modeling framework, our model results compare reasonably with observed or independently estimated patterns and ranges of P concentrations in soils and vegetation. Furthermore, our simulations suggest that P limitation might be an important driver of biomass production efficiency (the fraction of the gross primary productivity used for biomass growth), and that vegetation on older soils becomes P-limited leading to a smaller biomass production efficiency.
With this study, we provide a theoretical basis for investigating the responses of terrestrial ecosystems to P availability linking geological and ecological time scales under different environmental settings.
In old and heavily weathered soils, the availability of P might be so small that the primary production of plants is limited. However, plants have evolved several mechanisms to actively take up P from the soil or mine it to overcome this limitation. These mechanisms involve the active uptake of P mediated by mycorrhiza, biotic de-occlusion through root clusters, and the biotic enhancement of weathering through root exudation. The objective of this paper is to investigate how and where these processes contribute to alleviate P limitation on primary productivity. To do so, we propose a process-based model accounting for the major processes of the carbon, water, and P cycles including chemical weathering at the global scale. Implementing P limitation on biomass synthesis allows the assessment of the efficiencies of biomass production across different ecosystems. We use simulation experiments to assess the relative importance of the different uptake mechanisms to alleviate P limitation on biomass production. We find that active P uptake is an essential mechanism for sustaining P availability on long timescales, whereas biotic de-occlusion might serve as a buffer on timescales shorter than 10 000 yr. Although active P uptake is essential for reducing P losses by leaching, humid lowland soils reach P limitation after around 100 000 yr of soil evolution. Given the generalized modelling framework, our model results compare reasonably with observed or independently estimated patterns and ranges of P concentrations in soils and vegetation. Furthermore, our simulations suggest that P limitation might be an important driver of biomass production efficiency (the fraction of the gross primary productivity used for biomass growth), and that vegetation on old soils has a smaller biomass production rate when P becomes limiting. With this study, we provide a theoretical basis for investigating the responses of terrestrial ecosystems to P availability linking geological and ecological timescales under different environmental settings.