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Understanding how variance in environmental factors affects physiological performance, population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors, (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms.
This is a publication-based dissertation comprising three original research stud-ies (one published, one submitted and one ready for submission; status March 2019). The dissertation introduces a generic computer model as a tool to investigate the behaviour and population dynamics of animals in cyclic environments. The model is further employed for analysing how migratory birds respond to various scenarios of altered food supply under global change. Here, ecological and evolutionary time-scales are considered, as well as the biological constraints and trade-offs the individual faces, which ultimately shape response dynamics at the population level. Further, the effect of fine-scale temporal patterns in re-source supply are studied, which is challenging to achieve experimentally. My findings predict population declines, altered behavioural timing and negative carry-over effects arising in migratory birds under global change. They thus stress the need for intensified research on how ecological mechanisms are affected by global change and for effective conservation measures for migratory birds. The open-source modelling software created for this dissertation can now be used for other taxa and related research questions. Overall, this thesis improves our mechanistic understanding of the impacts of global change on migratory birds as one prerequisite to comprehend ongoing global biodiversity loss. The research results are discussed in a broader ecological and scientific context in a concluding synthesis chapter.
Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.
Global change has complex eco-evolutionary consequences for organisms and ecosystems, but related concepts (e.g., novel ecosystems) do not cover their full range. Here we propose an umbrella concept of "ecological novelty" comprising (1) a site-specific and (2) an organism-centered, eco-evolutionary perspective. Under this umbrella, complementary options for studying and communicating effects of global change on organisms, ecosystems, and landscapes can be included in a toolbox. This allows researchers to address ecological novelty from different perspectives, e.g., by defining it based on (a) categorical or continuous measures, (b) reference conditions related to sites or organisms, and (c) types of human activities. We suggest striving for a descriptive, non-normative usage of the term "ecological novelty" in science. Normative evaluations and decisions about conservation policies or management are important, but require additional societal processes and engagement with multiple stakeholders.
Specialisation and diversity of multiple trophic groups are promoted by different forest features
(2019)
While forest management strongly influences biodiversity, it remains unclear how the structural and compositional changes caused by management affect different community dimensions (e.g. richness, specialisation, abundance or completeness) and how this differs between taxa. We assessed the effects of nine forest features (representing stand structure, heterogeneity and tree composition) on thirteen above- and belowground trophic groups of plants, animals, fungi and bacteria in 150 temperate forest plots differing in their management type. Canopy cover decreased light resources, which increased community specialisation but reduced overall diversity and abundance. Features increasing resource types and diversifying microhabitats (admixing of oaks and conifers) were important and mostly affected richness. Belowground groups responded differently to those aboveground and had weaker responses to most forest features. Our results show that we need to consider forest features rather than broad management types and highlight the importance of considering several groups and community dimensions to better inform conservation.
Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
This PhD thesis presents the spatio-temporal distribution of terrestrial carbon fluxes for the time period of 1982 to 2002 simulated by a combination of the process-based dynamic global vegetation model LPJ and a 21-year time series of global AVHRR-fPAR data (fPAR – fraction of photosynthetically active radiation). Assimilation of the satellite data into the model allows improved simulations of carbon fluxes on global as well as on regional scales. As it is based on observed data and includes agricultural regions, the model combined with satellite data produces more realistic carbon fluxes of net primary production (NPP), soil respiration, carbon released by fire and the net land-atmosphere flux than the potential vegetation model. It also produces a good fit to the interannual variability of the CO2 growth rate. Compared to the original model, the model with satellite data constraint produces generally smaller carbon fluxes than the purely climate-based stand-alone simulation of potential natural vegetation, now comparing better to literature estimates. The lower net fluxes are a result of a combination of several effects: reduction in vegetation cover, consideration of human influence and agricultural areas, an improved seasonality, changes in vegetation distribution and species composition. This study presents a way to assess terrestrial carbon fluxes and elucidates the processes contributing to interannual variability of the terrestrial carbon exchange. Process-based terrestrial modelling and satellite-observed vegetation data are successfully combined to improve estimates of vegetation carbon fluxes and stocks. As net ecosystem exchange is the most interesting and most sensitive factor in carbon cycle modelling and highly uncertain, the presented results complementary contribute to the current knowledge, supporting the understanding of the terrestrial carbon budget.
Aim: Across the planet, grass-dominated biomes are experiencing shrub encroachment driven by atmospheric CO2 enrichment and land-use change. By altering resource structure and availability, shrub encroachment may have important impacts on vertebrate communities. We sought to determine the magnitude and variability of these effects across climatic gradients, continents, and taxa, and to learn whether shrub thinning restores the structure of vertebrate communities. Location: Worldwide. Time period: Contemporary. Major taxa studied: Terrestrial vertebrates. Methods: We estimated relationships between percentage shrub cover and the structure of terrestrial vertebrate communities (species richness, Shannon diversity and community abundance) in experimentally thinned and unmanipulated shrub-encroached grass-dominated biomes using systematic review and meta-analyses of 43 studies published from 1978 to 2016. We modelled the effects of continent, biome, mean annual precipitation, net primary productivity and the normalized difference vegetation index (NDVI) on the relationship between shrub cover and vertebrate community structure. Results: Species richness, Shannon diversity and total abundance had no consistent relationship with shrub encroachment and experimental thinning did not reverse encroachment effects on vertebrate communities. However, some effects of shrub encroachment on vertebrate communities differed with net primary productivity, amongst vertebrate groups, and across continents. Encroachment had negative effects on vertebrate diversity at low net primary productivity. Mammalian and herpetofaunal diversity decreased with shrub encroachment. Shrub encroachment also had negative effects on species richness and total abundance in Africa but positive effects in North America. Main conclusions: Biodiversity conservation and mitigation efforts responding to shrub encroachment should focus on low-productivity locations, on mammals and herpetofauna, and in Africa. However, targeted research in neglected regions such as central Asia and India will be needed to fill important gaps in our knowledge of shrub encroachment effects on vertebrates. Additionally, our findings provide an impetus for determining the mechanisms associated with changes in vertebrate diversity and abundance in shrub-encroached grass-dominated biomes.
Aim To understand the role and significance of the reindeer, Rangifer tarandus (Linnaeus, 1758), as a specific indicator in terms of late Quaternary biogeography and to determine the effects of global climate change on its range and local extinction dynamics at the end of the Ice Age.
Location Late Pleistocene/early Holocene range of reindeer over all of central and western Europe, including southern Scandinavia and northern Iberia, but excluding Russia, Belarus and the Ukraine.
Methods Radiocarbon-dated subfossil records of R. tarandus from both archaeological and natural deposits younger than 25,000 years were assembled in a database. The distribution area was divided into six representative regions. The C-14 dates were calibrated and plotted chronologically in maps in order to compare presence and absence and regional extinction patterns from one region to another.
Main conclusions The late Quaternary record for reindeer in Europe during the last 25 kyr shows a climate-driven dispersal and retreat in response to climate change, with regional variations. The collapse of the mammoth steppe biome did not lead to the local extinction in Europe, as in the case of other megafaunal species. Rangifer tarandus co-existed for about 3000 years during the Late Glacial and early Holocene with typical temperate species such as red deer and roe deer in non-analogue faunal communities. The regional extinction at the end of the Pleistocene coincides with the transition from light open birch/pine forests to pine/deciduous forests.
At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies. A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM. This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21<sup>st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.