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The present thesis aims to introduce process-based model for species range dynamics that can be fitted to abundance data. For this purpose, the well-studied Proteaceae species of the South African Cape Floristic Region (CFR) offer a great data set to fit process-based models. These species are subject to wildflower harvesting and environmental threats like habitat loss and climate change. The general introduction of this thesis presents shortly the available models for species distribution modelling. Subsequently, it presents the feasibility of process-based modelling. Finally, it introduces the study system as well as the objectives and layout. In Chapter 1, I present the process-based model for range dynamics and a statistical framework to fit it to abundance distribution data. The model has a spatially-explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) and an observation submodel (describing imperfect detection of individuals). The demographic submodel links species-specific habitat models describing the suitable habitat and process-based demographic models that consider local dynamics and anemochoric seed dispersal between populations. After testing the fitting framework with simulated data, I applied it to eight Proteaceae species with different demographic properties. Moreover, I assess the role of two other demographic mechanisms: positive (Allee effects) and negative density-dependence. Results indicate that Allee effects and overcompensatory local dynamics (including chaotic behaviour) seem to be important for several species. Most parameter estimates quantitatively agreed with independent data. Hence, the presented approach seemed to suit the demand of investigating non-equilibrium scenarios involving wildflower harvesting (Chapter 2) and environmental change (Chapter 3). The Chapter 2 addresses the impacts of wildflower harvesting. The chapter includes a sensitivity analysis over multiple spatial scales and demographic properties (dispersal ability, strength of Allee effects, maximum reproductive rate, adult mortality, local extinction probability and carrying capacity). Subsequently, harvesting effects are investigated on real case study species. Plant response to harvesting showed abrupt threshold behavior. Species with short-distance seed dispersal, strong Allee effects, low maximum reproductive rate, high mortality and high local extinction are most affected by harvesting. Larger spatial scales benefit species response, but the thresholds become sharper. The three case study species supported very low to moderate harvesting rates. Summarizing, demographic knowledge about the study system and careful identification of the spatial scale of interest should guide harvesting assessments and conservation of exploited species. The sensitivity analysis’ results can be used to qualitatively assess harvesting impacts for poorly studied species. I investigated in Chapter 3 the consequences of past habitat loss, future climate change and their interaction on plant response. I use the species-specific estimates of the best model describing local dynamics obtained in Chapter 1. Both habitat loss and climate change had strong negative impacts on species dynamics. Climate change affected mainly range size and range filling due to habitat reductions and shifts combined with low colonization. Habitat loss affected mostly local abundances. The scenario with both habitat loss and climate change was the worst for most species. However, this impact was better than expected by simple summing of separate effects of habitat loss and climate change. This is explained by shifting ranges to areas less affected by humans. Range size response was well predicted by the strength of environmental change, whereas range filling and local abundance responses were better explained by demographic properties. Hence, risk assessments under global change should consider demographic properties. Most surviving populations were restricted to refugia, serving as key conservation focus.The findings obtained for the study system as well as the advantages, limitations and potentials of the model presented here are further discussed in the General Discussion. In summary, the results indicate that 1) process-based demographic models for range dynamics can be fitted to data; 2) demographic processes improve species distribution models; 3) different species are subject to different processes and respond differently to environmental change and exploitation; 4) density regulation type and Allee effects should be considered when investigating range dynamics of species; 5) the consequences of wildflower harvesting, habitat loss and climate change could be disastrous for some species, but impacts vary depending on demographic properties; 6) wildflower harvesting impacts varies over spatial scale; 7) The effects of habitat loss and climate change are not always additive.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Human-induced alterations of the environment are causing biotic changes worldwide, including the extinction of species and a mixing of once disparate floras and faunas. One type of biological communities that is expected to be particularly affected by environmental alterations are herb layer plant communities of fragmented forests such as those in the west European lowlands. However, our knowledge about current changes in species diversity and composition in these communities is limited due to a lack of adequate long-term studies. In this thesis, I resurveyed the herb layer communities of ancient forest patches in the Weser-Elbe region (NW Germany) after two decades using 175 semi-permanent plots. The general objectives were (i) to quantify changes in plant species diversity considering also between-community (β) and functional diversity, (ii) to determine shifts in species composition in terms of species’ niche breadth and functional traits and (iii) to find indications on the most likely environmental drivers for the observed changes. These objectives were pursued with four independent research papers (Chapters 1-4) whose results were brought together in a General Discussion. Alpha diversity (species richness) increased by almost four species on average, whereas β diversity tended to decrease (Chapter 1). The latter is interpreted as a beginning floristic homogenization. The observed changes were primarily the result of a spread of native habitat generalists that are able to tolerate broad pH and moisture ranges. The changes in α and β diversity were only significant when species abundances were neglected (Chapters 1 and 2), demonstrating that the diversity changes resulted mainly from gains and losses of low-abundance species. This study is one of the first studies in temperate Europe that demonstrates floristic homogenization of forest plant communities at a larger than local scale. The diversity changes found at the taxonomic level did not result in similar changes at the functional level (Chapter 2). The likely reason is that these communities are functionally “buffered”. Single communities involve most of the functional diversity of the regional pool, i.e., they are already functionally rich, while they are functionally redundant among each other, i.e., they are already homogeneous. Independent of taxonomic homogenization, the abundance of 30 species decreased significantly (Chapter 4). These species included 12 ancient forest species (i.e., species closely tied to forest patches with a habitat continuity > 200 years) and seven species listed on the Red List of endangered plant species in NW Germany. If these decreases continue over the next decades, local extinctions may result. This biotic impoverishment would seriously conflict with regional conservation goals. Community assembly mechanisms changed at the local level particularly at sites that experienced disturbance by forest management activities between the sampling periods (Chapter 3). Disturbance altered community assembly mechanisms in two ways: (i) it relaxed environmental filters and allowed the coexistence of different reproduction strategies, as reflected by a higher diversity of reproductive traits at the time of the resurvey, and (ii) it enhanced light availability and tightened competitive filters. These limited the functional diversity with respect to canopy height and selected for taller species. Thirty-one winner and 30 loser species, which had significantly increased or decreased in abundance, respectively, were characterized by various functional traits and ecological performances to find indications on the most likely environmental drivers for the observed floristic changes (Chapter 4). Winner species had higher seed longevity, flowered later in the season and had more often an oceanic distribution compared to loser species. Loser species tended to have a higher specific leaf area, to be more susceptible to deer browsing and to have a performance optimum at higher soil pH values compared to winner species. Multiple logistic regression analyses indicated that disturbances due to forest management interventions were the primary cause of the species shifts. As one of the first European resurvey studies, this study provides indications that an enhanced browsing pressure due to increased deer densities and increasingly warmer winters are important drivers. The study failed to demonstrate that eutrophication and acidification due to atmospheric deposition substantially drive herb layer changes. The restriction of the sample to the most base-rich sites in the region is discussed as a likely reason. Furthermore, the decline of several ancient forest species is discussed as an indication that the forest patches are still paying off their “extinction debt”, i.e., exhibit a delayed response to forest fragmentation.
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.
Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties.
Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation.
Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.
It has been proposed that growth and reproduction of animals is frequently limited by multiple nutrients simultaneously. To improve our understanding of the consequences of multiple nutrient limitations (i.e. co-limitation) for the performance of animals, we conducted standardized population growth experiments using an important aquatic consumer, the rotifer Brachionus calyciflorus. We compared nutrient profiles (sterols, fatty acids and amino acids) of rotifers and their diets to reveal consumerdiet imbalances and thus potentially limiting nutrients. In concomitant growth experiments, we directly supplemented potentially limiting substances (sterols, fatty acids, amino acids) to a nutrient-deficient diet, the cyanobacterium Synechococcus elongatus, and recorded population growth rates. The results from the supplementation experiments corroborated the nutrient limitations predicted by assessing consumerdiet imbalances, but provided more detailed information on co-limiting nutrients. While the fatty acid deficiency of the cyanobacterium appeared to be of minor importance, the addition of both cholesterol and certain amino acids (leucine and isoleucine) improved population growth rates of rotifers, indicating a simultaneous limitation by sterols and amino acids. Our results add to growing evidence that consumers frequently face multiple nutrient limitations and suggest that the concept of co-limitation has to be considered in studies assessing nutrient-limited growth responses of consumers.
The distribution of poikilotherms is determined by the thermal structure of the marine environment that they are exposed to. Recent research has indicated that changes in migration phenology of beluga whales in the Arctic are triggered by changes in the thermal structure of the marine environment in their summering area. If sea temperatures reflect the spatial distribution of food resources, then changes in the thermal regime will affect how homogeneous or clumped food is distributed. We explore, by individual-based modelling, the hypothesis that changes in migration phenology are not necessarily or exclusively triggered by changes in food abundance, but also by changes in the spatial aggregation of food. We found that the level of food aggregation can significantly affect the relationship between the timing of the start of migration to the winter grounds and the total prey capture of individuals. Our approach strongly indicates that changes in the spatial distribution of food resources should be considered for understanding and quantitatively predicting changes in the phenology of animal migration.
Global change, especially land-use intensification, affects human well-being by impacting the delivery of multiple ecosystem services (multifunctionality). However, whether biodiversity loss is a major component of global change effects on multifunctionality in real-world ecosystems, as in experimental ones, remains unclear. Therefore, we assessed biodiversity, functional composition and 14 ecosystem services on 150 agricultural grasslands differing in land-use intensity. We also introduce five multifunctionality measures in which ecosystem services were weighted according to realistic land-use objectives. We found that indirect land-use effects, i.e. those mediated by biodiversity loss and by changes to functional composition, were as strong as direct effects on average. Their strength varied with land-use objectives and regional context. Biodiversity loss explained indirect effects in a region of intermediate productivity and was most damaging when land-use objectives favoured supporting and cultural services. In contrast, functional composition shifts, towards fast-growing plant species, strongly increased provisioning services in more inherently unproductive grasslands.
Epigenetic modifications, of which DNA methylation is the best studied one, can convey environmental information through generations via parental germ lines. Past studies have focused on the maternal transmission of epigenetic information to the offspring of isogenic mice and rats in response to external changes, whereas heterogeneous wild mammals as well as paternal epigenetic effects have been widely neglected. In most wild mammal species, males are the dispersing sex and have to cope with differing habitats and thermal changes. As temperature is a major environmental factor we investigated if genetically heterogeneous Wild guinea pig (Cavia aperea) males can adapt epigenetically to an increase in temperature and if that response will be transmitted to the next generation(s). Five adult male guinea pigs (F0) were exposed to an increased ambient temperature for 2 months, i.e. the duration of spermatogenesis. We studied the liver (as the main thermoregulatory organ) of F0 fathers and F1 sons, and testes of F1 sons for paternal transmission of epigenetic modifications across generation(s). Reduced representation bisulphite sequencing revealed shared differentially methylated regions in annotated areas between F0 livers before and after heat treatment, and their sons’ livers and testes, which indicated a general response with ecological relevance. Thus, paternal exposure to a temporally limited increased ambient temperature led to an ‘immediate’ and ‘heritable’ epigenetic response that may even be transmitted to the F2 generation. In the context of globally rising temperatures epigenetic mechanisms may become increasingly relevant for the survival of species.
Warming and eutrophication are two of the most important global change stressors for natural ecosystems, but their interaction is poorly understood. We used a dynamic model of complex, size-structured food webs to assess interactive effects on diversity and network structure. We found antagonistic impacts: Warming increases diversity in eutrophic systems and decreases it in oligotrophic systems. These effects interact with the community size structure: Communities of similarly sized species such as parasitoid-host systems are stabilized by warming and destabilized by eutrophication, whereas the diversity of size-structured predator-prey networks decreases strongly with warming, but decreases only weakly with eutrophication. Nonrandom extinction risks for generalists and specialists lead to higher connectance in networks without size structure and lower connectance in size-structured communities. Overall, our results unravel interactive impacts of warming and eutrophication and suggest that size structure may serve as an important proxy for predicting the community sensitivity to these global change stressors.
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.
Recent research has shown that many cold-adapted species survived the last glacial maximum (LGM) in northern refugia. Whether this evolutionary history has had consequences for their genetic diversity and adaptive potential remains unknown. We sampled 14 populations of Carex limosa, a sedge specialized to bog ecosystems, along a latitudinal gradient from its Scandinavian core to the southern lowland range-margin in Germany. Using microsatellite and experimental common-garden data, we evaluated the impacts of global climate change along this gradient and assessed the conservation status of the southern marginal populations. Microsatellite data revealed two highly distinct genetic groups and hybrid individuals. In our common-garden experiment, the two groups showed divergent responses to increased nitrogen/phosphorus (N/P) availability, suggesting ecotypic differentiation. Each group formed genetically uniform populations at both northern and southern sampling areas. Mixed populations occurred throughout our sampling area, an area that was entirely glaciated during the LGM. The fragmented distribution implies allopatric divergence at geographically separated refugia that putatively differed in N/P availability. Molecular data and an observed low hybrid fecundity indicate the importance of clonal reproduction for hybrid populations. At the southern range-margin, however, all populations showed effects of clonality, lowered fecundity and low competitiveness, suggesting abiotic and biotic constraints to population persistence.
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.
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.
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.
Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.
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.