Search

Rapid development of tracking technologies allow the collection of high-quality data on multiple simultaneously moving individuals. This, in turn, initiated the development of several methods to infer interactions among moving animals. However, the performance of these methods has not been studied systematically, especially with regard to the factors that are highly relevant for field ecologists, such as duration of the tracking period, its temporal resolution and the proportion of the tracked community.Here, we assessed the performance of three dynamic interaction indices (Coefficient of sociality, Correlation coefficient and Dynamic interaction) and two novel approaches based on step selection functions (SSF-occurrence-distribution and SSF-distance). We tested these methods on the data simulated with a predator–prey system, reflecting three common types of interactions while on the move: avoidance (prey individuals fleeing from the predator), attraction (predator following and chasing prey) and neutral movement (no interactions between predator and prey). We assessed the ability of each method to correctly detect the modelled interaction type by manipulating the perceptual range of the predator, the proportion of tracked prey individuals, the temporal resolution and the duration of the tracking period.We found that the ability to correctly infer interactions increased for all methods with an increase in the perceptual range of the predator and the proportion of tracked prey individuals. In contrast, the duration of the tracking period affected the methods' performance differently: some methods (Cs and SSF-distance) were insensitive to it, whereas the performance of other methods improved (DI and SSF-occurrence-distribution) and worsened (Cr) with the duration of the tracking period. The three dynamic interaction indices and SSF-distance were rather robust to changes in data resolution.Despite using the predator–prey system as our study case, our findings are appli

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals’ 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animal’s home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals.

17 juni 2022, Contains fulltext : 252380.pdf (Publisher’s version ) (Open Access), In our paper "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data" (Global Ecology and Biogeography) we use GPS tracking data from 1,498 from 49 different species to evaluate the expert-based habitat suitability data from the International Union for Conservation of Nature (IUCN). Therefore, we used the GPS tracking data to estimate two measures of habitat suitability for each individual animal and habitat type: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN’s classification into suitable, marginal and unsuitable habitat types. Our results showed that IUCN habitat suitability data were in accordance with the GPS data (>95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a >50% probability of agreement based on proportional habitat use and selection ratios, respectively. These findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, our study shows that GPS tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. In this dataset we provide the measures of habitat suitability for each individual and each habitat type, calculated using different methods. In addition, we provide data on the body mass and IUCN Red List category of the species, as well as whether the species can be considered a habitat specialist or habitat generalist.

17 juni 2022, Contains fulltext : 252380.pdf (Publisher’s version ) (Open Access), In our paper "Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data" (Global Ecology and Biogeography) we use GPS tracking data from 1,498 from 49 different species to evaluate the expert-based habitat suitability data from the International Union for Conservation of Nature (IUCN). Therefore, we used the GPS tracking data to estimate two measures of habitat suitability for each individual animal and habitat type: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN’s classification into suitable, marginal and unsuitable habitat types. Our results showed that IUCN habitat suitability data were in accordance with the GPS data (>95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a >50% probability of agreement based on proportional habitat use and selection ratios, respectively. These findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, our study shows that GPS tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. In this dataset we provide the measures of habitat suitability for each individual and each habitat type, calculated using different methods. In addition, we provide data on the body mass and IUCN Red List category of the species, as well as whether the species can be considered a habitat specialist or habitat generalist.

Studies investigating the effect of aboveground herbivory on plants often use clipping to simulate the effects of herbivores, for practical reasons. However, herbivore movements and transfer of oral secretions during herbivory may cause a different response in plant physiology and morphology compared to clipping. While studies have compared effects of real herbivory vs. clipping on biomass production, plant physiology, and shoot morphology, no study has compared such effects on root morphology. Therefore, we investigated the effect of herbivory by grasshoppers, herbivory simulated by clipping, and no herbivory on root morphological traits of ten grassland plant species. Root morphological traits were differently affected by the two herbivory treatments. Grasshopper herbivory significantly changed root morphology toward thinner roots with increased specific root length and root area, and decreased root tissue density compared to untreated control plants. Clipping had mostly similar, but weaker effects on root morphology than grasshopper herbivory. On the species level, grasshopper herbivory led to strongest changes in root morphology in almost all cases. In contrast, depending on the species, clipping resulted in varying root morphological trait values similar to grasshopper-damaged plants, or in some cases, more closely aligned with control plants. Though clipping was partly able to mimic the effects of herbivory by grasshoppers, results also indicate that, depending on the species, grasshopper herbivory had different but mostly stronger effects. We, therefore, recommend that future studies apply herbivory with real herbivores to better reflect natural responses in plants and related processes that root morphological traits mediate.

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animal’s home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals.

Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animal’s home range, and many methods of estimating home ranges have arisen over the past half century. Most of these methods fall into two distinct categories of estimators that have only recently been described in statistical detail: those that measure range distributions (methods such as Kernel Density Estimation that quantify the long-run behavior of a movement process that features restricted space use) and those that measure occurrence distributions (methods such as Brownian Bridge Movement Models and the Correlated Random Walk Library that quantify uncertainty in an animal movement path during a specific period of observation). In this paper, we use theory, simulations, and empirical analysis to demonstrate the importance of applying these two classes of space use estimators appropriately and distinctly. Conflating range and occurrence distributions can have serious consequences for ecological inference and conservation practice. For example, in most situations, home-range estimates quantified using occurrence estimators are too small, and this problem is exacerbated by ongoing improvements in tracking technology that enable more frequent and more accurate data on animal movements. We encourage researchers to use range estimators to estimate the area of home ranges and occurrence estimators to answer other questions in movement ecology, such as when and where an animal crosses a linear feature, visits a location of interest, or interacts with other animals.

Contains fulltext : 226766.pdf (publisher's version ) (Open Access)

Contains fulltext : 226766.pdf (publisher's version ) (Open Access)

Organismal movement is ubiquitous and facilitates important ecological mechanisms that drive community and metacommunity composition and hence biodiversity. In most existing ecological theories and models in biodiversity research, movement is represented simplistically, ignoring the behavioural basis of movement and consequently the variation in behaviour at species and individual levels. However, as human endeavours modify climate and land use, the behavioural processes of organisms in response to these changes, including movement, become critical to understanding the resulting biodiversity loss. Here, we draw together research from different subdisciplines in ecology to understand the impact of individual‐level movement processes on community‐level patterns in species composition and coexistence. We join the movement ecology framework with the key concepts from metacommunity theory, community assembly and modern coexistence theory using the idea of micro–macro links, where various aspects of emergent movement behaviour scale up to local and regional patterns in species mobility and mobile‐link‐generated patterns in abiotic and biotic environmental conditions. These in turn influence both individual movement and, at ecological timescales, mechanisms such as dispersal limitation, environmental filtering, and niche partitioning. We conclude by highlighting challenges to and promising future avenues for data generation, data analysis and complementary modelling approaches and provide a brief outlook on how a new behaviour‐based view on movement becomes important in understanding the responses of communities under ongoing environmental change.

Understanding the drivers underlying disease dynamics is still a major challenge in disease ecology, especially in the case of long‐term disease persistence. Even though there is a strong consensus that density‐dependent factors play an important role for the spread of diseases, the main drivers are still discussed and, more importantly, might differ between invasion and persistence periods.Here, we analysed long‐term outbreak data of classical swine fever, an important disease in both wild boar and livestock, prevalent in the wild boar population from 1993 to 2000 in Mecklenburg‐Vorpommern, Germany. We report outbreak characteristics and results from generalized linear mixed models to reveal what factors affected infection risk on both the landscape and the individual level.Spatiotemporal outbreak dynamics showed an initial wave‐like spread with high incidence during the invasion period followed by a drop of incidence and an increase in seroprevalence during the persistence period. Velocity of spread increased with time during the first year of outbreak and decreased linearly afterwards, being on average 7.6 km per quarter. Landscape‐ and individual‐level analyses of infection risk indicate contrasting seasonal patterns. During the persistence period, infection risk on the landscape level was highest during autumn and winter seasons, probably related to spatial behaviour such as increased long‐distance movements and contacts induced by rutting and escaping movements. In contrast, individual‐level infection risk peaked in spring, probably related to the concurrent birth season leading to higher densities, and was significantly higher in piglets than in reproductive animals.Our findings highlight that it is important to investigate both individual‐ and landscape‐level patterns of infection risk to understand long‐term persistence of wildlife diseases and to guide respective management actions. Furthermore, we highlight that exploring different temporal aggre

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint.We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.

Agricultural intensification (AI) negatively affects biodiversity due to e.g. high-input farming. Organic farming can counteract this negative trend. Here, we studied movement behavior of the European brown hare (Lepus europaeus), which frequently occurs in agricultural landscapes but also suffers from AI with declining population densities. We measured home range sizes in relation to local field management (organic vs. conventional farming) in Upper Bavarian, Germany. Results showed that home ranges sizes decreased with increasing amount of organically managed area, while there was no relationship between conventional farmed area and hares’ movement behavior. Higher resource availability in organic fields decrease home range sizes and may therefore positively influences individual fitness and possibly boosts hare densities.

Agricultural intensification (AI) negatively affects biodiversity due to e.g. high-input farming. Organic farming can counteract this negative trend. Here, we studied movement behavior of the European brown hare (Lepus europaeus), which frequently occurs in agricultural landscapes but also suffers from AI with declining population densities. We measured home range sizes in relation to local field management (organic vs. conventional farming) in Upper Bavarian, Germany. Results showed that home ranges sizes decreased with increasing amount of organically managed area, while there was no relationship between conventional farmed area and hares’ movement behavior. Higher resource availability in organic fields decrease home range sizes and may therefore positively influences individual fitness and possibly boosts hare densities.

Agricultural intensification (AI) negatively affects biodiversity due to e.g. high-input farming. Organic farming can counteract this negative trend. Here, we studied movement behavior of the European brown hare (Lepus europaeus), which frequently occurs in agricultural landscapes but also suffers from AI with declining population densities. We measured home range sizes in relation to local field management (organic vs. conventional farming) in Upper Bavarian, Germany. Results showed that home ranges sizes decreased with increasing amount of organically managed area, while there was no relationship between conventional farmed area and hares’ movement behavior. Higher resource availability in organic fields decrease home range sizes and may therefore positively influences individual fitness and possibly boosts hare densities.

Agricultural intensification (AI) negatively affects biodiversity due to e.g. high-input farming. Organic farming can counteract this negative trend. Here, we studied movement behavior of the European brown hare (Lepus europaeus), which frequently occurs in agricultural landscapes but also suffers from AI with declining population densities. We measured home range sizes in relation to local field management (organic vs. conventional farming) in Upper Bavarian, Germany. Results showed that home ranges sizes decreased with increasing amount of organically managed area, while there was no relationship between conventional farmed area and hares’ movement behavior. Higher resource availability in organic fields decrease home range sizes and may therefore positively influences individual fitness and possibly boosts hare densities.

Agricultural intensification (AI) negatively affects biodiversity due to e.g. high-input farming. Organic farming can counteract this negative trend. Here, we studied movement behavior of the European brown hare (Lepus europaeus), which frequently occurs in agricultural landscapes but also suffers from AI with declining population densities. We measured home range sizes in relation to local field management (organic vs. conventional farming) in Upper Bavarian, Germany. Results showed that home ranges sizes decreased with increasing amount of organically managed area, while there was no relationship between conventional farmed area and hares’ movement behavior. Higher resource availability in organic fields decrease home range sizes and may therefore positively influences individual fitness and possibly boosts hare densities.

The abandonment of military areas leads to succession processes affecting valuable open-land habitats and is considered to be a major threat for European butterflies. We assessed the ability of hyper spectral remote sensing data to spatially predict the occurrence of one of the most endangered butterfly species (Hipparchia statilinus) in Brandenburg (Germany) on the basis of habitat characteristics at a former military training area. Presence–absence data were sampled on a total area of 36 km2, and N = 65 adult individuals of Hipparchia statilinus could be detected. The floristic composition within the study area was modeled in a three-dimensional ordination space. Occurrence probabilities for the target species were predicted as niches between ordinated floristic gradients by using Regression Kriging of Indicators. Habitat variance could be explained by up to 81 % with spectral variables at a spatial resolution of 2 × 2 m by transferring PLSR models to imagery. Ordinated ecological niche of Hipparchia statilinus was tested against environmental predictor variables. N = 6 variables could be detected to be significantly correlated with habitat preferences of Hipparchia statilinus. They show that Hipparchia statilinus can serve as a valuable indicator for the evaluation of the conservation status of Natura 2000 habitat type 2330 (inland dunes with open Corynephorus and Agrostis grasslands) protected by the Habitat Directive (Council Directive 92/43/EEC). The authors of this approach, conducted in August 2013 at Döberitzer Heide Germany, aim to increase the value of remote sensing as an important tool for questions of biodiversity research and conservation.

Climate change and land use management practices are major drivers of biodiversity in terrestrial ecosystems. To understand and predict resulting changes in community structures, individual-based and spatially explicit population models are a useful tool but require detailed data sets for each species. More generic approaches are thus needed. Here we present a trait-based functional type approach to model savanna birds. The aim of our model is to explore the response of different bird functional types to modifications in habitat structure. The functional types are characterized by different traits, in particular body mass, which is related to life-history traits (reproduction and mortality) and spatial scales (home range area and dispersal ability), as well as the use of vegetation structures for foraging and nesting, which is related to habitat quality and suitability. We tested the performance of the functional types in artificial landscapes varying in shrub:grass ratio and clumping intensity of shrub patches. We found that an increase in shrub encroachment and a decrease in habitat quality caused by land use mismanagement and climate change endangered all simulated bird functional types. The strength of this effect was related to the preferred habitat. Furthermore, larger-bodied insectivores and omnivores were more prone to extinction due to shrub encroachment compared to small-bodied species. Insectivorous and omnivorous birds were more sensitive to clumping intensity of shrubs whereas herbivorous and carnivorous birds were most affected by a decreasing amount of grass cover. From an applied point of view, our findings emphasize that policies such as woody plant removal and a reduction in livestock stocking rates to prevent shrub encroachment should prioritize the enlargement of existing grassland patches. Overall, our results show that the combination of an individual-based modelling approach with carefully defined functional types can provide a powerful tool f

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels., Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs.

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of 'movement ecology'. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide 'mobile links' between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through 'equalizing' and 'stabilizing' mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels., Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Dispersal greatly determines genetic structure of populations, although it is influenced by landscape heterogeneity, quality of the matrix, resource distribution and local population densities and dynamics. To get insights into some of those processes we analysed the genetic structure of the hairy-footed gerbil Gerbillurus paeba (Rodentia, Murinae, Gerbillinae) in the southern Kalahari (South Africa). Samples were taken from 20 populations covering an area of about 2200 km2. Genetic data were related to landscape characters and population dynamics. We used newly developed microsatellites and found at all loci some indication for the presence of null alleles. However, null alleles seem to have little influence on the general results of our analyses. Altogether we found even nearby populations of G. paeba to be significantly differentiated, although assignment tests revealed 24% of individuals as immigrants. Genetic structure was independent of landscape heterogeneities at all spatial scales. Autocorrelation analyses (range 50-90 km) revealed significant genetic structure within populations on distances <3 km. We found some indication for female-biased dispersal. Our study suggests that dispersing individuals have little influence on the long-term genetic structure and that drift is the major cause of genetic diversity. The observed genetic pattern likely derives from strong population fluctuations of G. paeba. The landscape structure has little influence on the genetic differentiation between populations.

In population viability analysis we are often faced with a lack of knowledge of survival rates in animal populations. In particular, survival of recruits is usually hard to assess. However, data on population structure might be considered as patterns that contain valuable information to estimate missing parameters indirectly. As an example for this pattern-oriented modelling and parameterization, pre-breeding survival rate of the endangered Lesser Spotted Woodpecker (Picoides minor) was determined here using data on population structure (e.g. sex ratio) and reproductive success at the population level (e.g. nesting success). Therefore, an individual-based model was developed simulating the population dynamics for two different populations that had been empirically studied at Lake Möckeln, Sweden, and Taunus, Germany. For both populations, a small range for pre-breeding survival rates could be identified wherein all simulated patterns corresponded best to the empirical values. Pre-breeding survival rate was found to be higher in the German scenario than in the Swedish and geographical variation in life-history traits is discussed as a possible reason. It is concluded that the pattern-oriented approach is a valuable method for estimating missing demographic parameters, even when using weak patterns from empirical investigations. Furthermore, it was shown that the use of multiple patterns is necessary for this purpose.

1. In most stochastic models addressing the persistence of small populations, environmental noise is included by imposing a synchronized effect of the environment on all individuals. However, buffer mechanisms are likely to exist that may counteract this synchronization to some degree.2. We have studied whether the flexibility in the mating system, which has been observed in some bird species, is a potential mechanism counteracting the synchronization of environmental fluctuations. Our study organism is the lesser spotted woodpecker Picoides minor (Linnaeus), a generally monogamous species. However, facultative polyandry, where one female mates with two males with separate nests, was observed in years with male-biased sex ratio.3. We constructed an individual-based model from data and observations of a population in Taunus, Germany. We tested the impact of three behavioural scenarios on population persistence: (1) strict monogamy; (2) polyandry without costs; and (3) polyandry assuming costs in terms of lower survival and reproductive success for secondary males. We assumed that polyandry occurs only in years with male-biased sex ratio and only for females with favourable breeding conditions.4. Even low rates of polyandry had a strong positive effect on population persistence. The increase of persistence with carrying capacity was slower in the monogamous scenario, indicating strong environmental noise. In the polyandrous scenarios, the increase of persistence was stronger, indicating a buffer mechanism. In the polyandrous scenarios, populations had a higher mean population size, a lower variation in number of individuals, and recovered faster after a population breakdown. Presuming a realistic polyandry rate and costs for polyandry, there was still a strong effect of polyandry on persistence.5. The results show that polyandry and in general flexibility in mating systems is a buffer mechanism that can significantly reduce the impact of environmental and demographic