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1. The biases and shortcomings of stepwise multiple regression are well established within the statistical literature. However, an examination of papers published in 2004 by three leading ecological and behavioural journals suggested that the use of this technique remains widespread: of 65 papers in which a multiple regression approach was used, 57% of studies used a stepwise procedure. 2. The principal drawbacks of stepwise multiple regression include bias in parameter estimation, inconsistencies among model selection algorithms, an inherent (but often overlooked) problem of multiple hypothesis testing, and an inappropriate focus or reliance on a single best model. We discuss each of these issues with examples. 3. We use a worked example of data on yellowhammer distribution collected over 4 years to highlight the pitfalls of stepwise regression. We show that stepwise regression allows models containing significant predictors to be obtained from each year's data. In spite of the significance of the selected models, they vary substantially between years and suggest patterns that are at odds with those determined by analysing the full, 4-year data set. 4. An information theoretic (IT) analysis of the yellowhammer data set illustrates why the varying outcomes of stepwise analyses arise. In particular, the IT approach identifies large numbers of competing models that could describe the data equally well, showing that no one model should be relied upon for inference. [ABSTRACT FROM AUTHOR]

Keywords: accelerometer; animal movement; behaviour; biologging; GPS; modelling; sensor technology; tracking Technological solutions to record the movements, behaviour and physiology of animals, and associated methodological advancements for analysing the data collected, have revolutionized research in animal ecology and beyond (Brisson-Curadeau, Patterson, Whelan, Lazarus, & Elliott, [18]; Kenward, [56]; Ropert-Coudert, Beaulieu, Hanuise, & Kato, [91]; Ropert-Coudert & Wilson, [92]; Weimerskirch, [107]). The general term for this technological approach to study animals is called Biologging - 'the use of miniaturized animal-attached tags for logging and/or relaying data about an animal's movements, behaviour, physiology, and/or environment' (Rutz & Hays, [94]). Thanks to ever smaller loggers which can record an animal's behaviour for ever longer periods of time, biologging is now allowing researchers to study with unprecedented detail how behaviours develop in slow-maturing animals. While an increasing body of research has shown the impact of consistent individual differences in behavioural phenotypes, called animal personalities or behavioural syndromes (Réale et al., [89]; Sih, Bell, Johnson, & Ziemba, [96]), on foraging behaviour, exploratory movements and other spatial behaviours (Bijleveld et al., [12]; Boon, Réale, & Boutin, [15]; Minderman et al., [75]; van Overveld & Matthysen, [103]; Villegas-Ríos, Réale, Freitas, Moland, & Olsen, [105]; Wilson & McLaughlin, [112]), the important relationship between animal personality and foraging site fidelity has not been studied yet. [Extracted from the article]

During the last decade, there has been a proliferation of statistical methods for studying resource selection by animals. While statistical techniques are advancing at a fast pace, there is confusion in the conceptual understanding of the meaning of various quantities that these statistical techniques provide., Terms such as selection, choice, use, occupancy and preference often are employed as if they are synonymous. Many practitioners are unclear about the distinctions between different concepts such as 'probability of selection,' 'probability of use,' 'choice probabilities' and 'probability of occupancy'., Similarly, practitioners are not always clear about the differences between and relevance of 'relative probability of selection' vs. 'probability of selection' to effective management., Practitioners also are unaware that they are using only a single statistical model for modelling resource selection, namely the exponential probability of selection, when other models might be more appropriate. Currently, such multimodel inference is lacking in the resource selection literature., In this paper, we attempt to clarify the concepts and terminology used in animal resource studies by illustrating the relationships among these various concepts and providing their statistical underpinnings. [ABSTRACT FROM AUTHOR]

The article compares methods for predictive modelling of species geographical distributions and the modelling of habitat selection by animals. It states that the modelling of species geographical distribution and habitat selection are based on the environmental conditions and also analyses the selection of resources by animals. It discusses utilization distributions (UDs) and utilization functions (RUF) that play an important role in the modelling of habitat selection.

Visibility (viewshed) plays a significant and diverse role in animals' behaviour and fitness. Understanding how visibility influences animal behaviour requires the measurement of habitat visibility at spatial scales commensurate to individual animal choices. However, measuring habitat visibility at a fine spatial scale over a landscape is a challenge, particularly in highly heterogeneous landscapes (e.g. forests). As a result, our ability to model the influence of fine‐scale visibility on animal behaviour has been impeded or limited.In this study, we demonstrate the application of the concept of three‐dimensional (3D) cumulative viewshed in the study of animal spatial behaviour at a landscape level. Specifically, we employed a newly described approach that combines terrestrial and airborne light detection and ranging (LiDAR) to measure fine‐scale habitat visibility (3D cumulative viewshed) on a continuous scale in forested landscapes. We applied the LiDAR‐derived visibility to investigate how visibility in forests affects the summer habitat selection and the movement of 20 GPS‐collared female red deer Cervus elaphus in a temperate forest in Germany. We used integrated step selection analysis to determine whether red deer show any preference for fine‐scale habitat visibility and whether visibility is related to the rate of movement of red deer.We found that red deer selected intermediate habitat visibility. Their preferred level of visibility during the day was substantially lower than that of night and twilight, whereas the preference was not significantly different between night and twilight. In addition, red deer moved faster in high‐visibility areas, possibly mainly to avoid predation and anthropogenic risk. Furthermore, red deer moved most rapidly between locations in the twilight.For the first time, the preference for intermediate habitat visibility and the adaption of movement rate to fine‐scale visibility by a forest‐dwelling ungulate species at a landscape scale was revealed. The LiDAR technique used in this study offers fine‐scale habitat visibility at the landscape level in forest ecosystems, which would be of broader interest in the fields of animal ecology and behaviour. [ABSTRACT FROM AUTHOR]

Behaviour is the interface between an organism and its environment, and behavioural plasticity is important for organisms to cope with environmental change. Social behaviour is particularly important because sociality is a dynamic process, where environmental variation influences group dynamics and social plasticity can mediate resource acquisition. Heterogeneity in the ecological environment can therefore influence the social environment. The combination of the ecological and social environments may be interpreted collectively as the 'socioecological environment,' which could explain variation in fitness., Our objective was to outline a framework through which individual social and spatial phenotypes can be integrated and interpreted as phenotypes that covary as a function of changes in the socioecological environment. We propose the socioecological environment is composed of individual behavioural traits, including sociality and habitat selection, both of which are repeatable, potentially heritable and may reflect animal personality traits. We also highlight how ecological and social niche theory can be applied to the socioecological environment framework, where individuals occupy different socioecological niches. Individual sociality and habitat selection are also density-dependent, and theory predicts that density-dependent traits should affect reproduction, survival, and therefore fitness and population dynamics., We then illustrate the proximate links between sociality, habitat selection and fitness as well as the ultimate, and possibly adaptive, consequences associated with changes in population density. The ecological, evolutionary and applied implications of our proposed socioecological environment framework are broad and changes in density could influence individual fitness and population dynamics. For instance, human-induced environmental changes can influence population density, which can affect the distribution of social and spatial phenotypes within a population. In summary, we outline a conceptual framework that incorporates individual social and spatial behavioural traits with fitness and we highlight a range of ecological and evolutionary processes that are likely associated with the socioecological environment. [ABSTRACT FROM AUTHOR]

Interspecific social information transfer can play a key role in many aspects of animal ecology from foraging to habitat selection to predator avoidance., Within scavenging communities, avian scavengers often act as producers and mammalian scavengers act as scroungers, but we predict that species-specific cueing will allow for mammalian scavengers to utilize particular avian scavenger species using preferred food sources similar to their own preferences., We use empirical and theoretic approaches to assess interactions between mammalian and avian scavengers in one of the most diverse scavenging guilds in Masai Mara National Reserve, Kenya., Using a spatially explicit model and data from experimental carcasses, we found evidence that mammals benefit from local enhancement provided by vultures and that mammalian-avian following patterns are consistent with the idea that species-specific cueing is occurring., Results suggest that ongoing population declines in avian scavengers may have significant impacts on mammalian scavengers and potentially create trophic cascades. [ABSTRACT FROM AUTHOR]

An extensive body of theory suggests that density-dependent habitat selection drives many fundamental ecological processes. The ideal free distribution and the ideal despotic distribution make contrasting predictions about the effect of total population size on relative abundances among habitats. Empirical assessment of these habitat selection models is uncommon because data must be collected over large temporal and spatial scales., I ask whether fluctuation in Chinook salmon ( Oncorhynchus tshawytscha) spawner population size through time leads to different relative densities over space., Twenty-six years of monitoring data on spawning Chinook salmon across the entire coast of Oregon, USA, were used to evaluate models that make contrasting statements about the interactions of a latent population abundance parameter with physical habitat characteristics., There is strong information-theoretic support for models that include terms that allow the spatial variation in density to change as population size changes through time. Analysis of the best model reveals nonlinear isodars, which suggests a 'despotic' or 'preemptive' distribution of individuals across habitats, indicating that dominant or early-arriving individuals exclude others from breeding sites., This finding has implications for genetic dynamics, population dynamics and conservation metrics of these highly valued fish. The novel application of modelling techniques used here to assess mechanisms of habitat selection from observational data can be used in the emerging field of eco-evolutionary dynamics. [ABSTRACT FROM AUTHOR]

Analyses based on utilization distributions (UDs) have been ubiquitous in animal space use studies, largely because they are computationally straightforward and relatively easy to employ. Conventional applications of resource utilization functions (RUFs) suggest that estimates of UDs can be used as response variables in a regression involving spatial covariates of interest., It has been claimed that contemporary implementations of RUFs can yield inference about resource selection, although to our knowledge, an explicit connection has not been described., We explore the relationships between RUFs and resource selection functions from a hueristic and simulation perspective. We investigate several sources of potential bias in the estimation of resource selection coefficients using RUFs (e.g. the spatial covariance modelling that is often used in RUF analyses)., Our findings illustrate that RUFs can, in fact, serve as approximations to RSFs and are capable of providing inference about resource selection, but only with some modification and under specific circumstances., Using real telemetry data as an example, we provide guidance on which methods for estimating resource selection may be more appropriate and in which situations. In general, if telemetry data are assumed to arise as a point process, then RSF methods may be preferable to RUFs; however, modified RUFs may provide less biased parameter estimates when the data are subject to location error. [ABSTRACT FROM AUTHOR]

If animals moved randomly in space, the use of different habitats would be proportional to their availability. Hence, deviations from proportionality between use and availability are considered the tell-tale sign of preference. This principle forms the basis for most habitat selection and species distribution models fitted to use-availability or count data (e.g. MaxEnt and Resource Selection Functions)., Yet, once an essential habitat type is sufficiently abundant to meet an individual's needs, increased availability of this habitat type may lead to a decrease in the use/availability ratio. Accordingly, habitat selection functions may estimate negative coefficients when habitats are superabundant, incorrectly suggesting an apparent avoidance. Furthermore, not accounting for the effects of availability on habitat use may lead to poor predictions, particularly when applied to habitats that differ considerably from those for which data have been collected., Using simulations, we show that habitat use varies non-linearly with habitat availability, even when individuals follow simple movement rules to acquire food and avoid risk. The results show that the impact of availability strongly depends on the type of habitat (e.g. whether it is essential or substitutable) and how it interacts with the distribution and availability of other habitats., We demonstrate the utility of a variety of existing and new methods that enable the influence of habitat availability to be explicitly estimated. Models that allow for non-linear effects (using b-spline smoothers) and interactions between environmental covariates defining habitats and measures of their availability were best able to capture simulated patterns of habitat use across a range of environments., An appealing aspect of some of the methods we discuss is that the relative influence of availability is not defined a priori, but directly estimated by the model. This feature is likely to improve model prediction, hint at the mechanism of habitat selection, and may signpost habitats that are critical for the organism's fitness. [ABSTRACT FROM AUTHOR]

Analyses of animal resource selection functions ( RSF) using data collected from relocations of individuals via remote telemetry devices have become commonplace. Increasing technological advances, however, have produced statistical challenges in analysing such highly autocorrelated data. Weighted distribution methods have been proposed for analysing RSFs with telemetry data. However, they can be computationally challenging due to an intractable normalizing constant and cannot be aggregated (i.e. collapsed) over time to make space-only inference., In this study, we take a conceptually different approach to modelling animal telemetry data for making RSF inference. We consider the telemetry data to be a realization of a space-time point process. Under the point process paradigm, the times of the relocations are also considered to be random rather than fixed., We show the point process models we propose are a generalization of the weighted distribution telemetry models. By generalizing the weighted model, we can access several numerical techniques for evaluating point process likelihoods that make use of common statistical software. Thus, the analysis methods can be readily implemented by animal ecologists., In addition to ease of computation, the point process models can be aggregated over time by marginalizing over the temporal component of the model. This allows a full range of models to be constructed for RSF analysis at the individual movement level up to the study area level., To demonstrate the analysis of telemetry data with the point process approach, we analysed a data set of telemetry locations from northern fur seals ( Callorhinus ursinus) in the Pribilof Islands, Alaska. Both a space-time and an aggregated space-only model were fitted. At the individual level, the space-time analysis showed little selection relative to the habitat covariates. However, at the study area level, the space-only model showed strong selection relative to the covariates. [ABSTRACT FROM AUTHOR]

1. Several methods have been developed to assess habitat selection, most of which are based on a comparison between habitat attributes in used vs. unused or random locations, such as the popular resource selection functions (RSFs). Spatial evaluation of residency time has been recently proposed as a promising avenue for studying habitat selection. Residency-time analyses assume a positive relationship between residency time within habitat patches and selection. We demonstrate that RSF and residency-time analyses provide different information about the process of habitat selection. Further, we show how the consideration of switching rate between habitat patches (interpatch movements) together with residency-time analysis can reveal habitat-selection strategies. 2. Spatially explicit, individual-based modelling was used to simulate foragers displaying one of six foraging strategies in a heterogeneous environment. The strategies combined one of three patch-departure rules (fixed-quitting-harvest-rate, fixed-time and fixed-amount strategy), together with one of two interpatch-movement rules (random or biased). Habitat selection of simulated foragers was then assessed using RSF, residency-time and interpatch-movement analyses. 3. Our simulations showed that RSFs and residency times are not always equivalent. When foragers move in a non-random manner and do not increase residency time in richer patches, residency-time analysis can provide misleading assessments of habitat selection. This is because the overall time spent in the various patch types not only depends on residency times, but also on interpatch-movement decisions. 4. We suggest that RSFs provide the outcome of the entire selection process, whereas residency-time and interpatch-movement analyses can be used in combination to reveal the mechanisms behind the selection process. 5. We showed that there is a risk in using residency-time analysis alone to infer habitat selection. Residency-time analyses, however, may enlighten the mechanisms of habitat selection by revealing central components of resource-use strategies. Given that management decisions are often based on resource-selection analyses, the evaluation of resource-use strategies can be key information for the development of efficient habitat-management strategies. Combining RSF, residency-time and interpatch-movement analyses is a simple and efficient way to gain a more comprehensive understanding of habitat selection. [ABSTRACT FROM AUTHOR]

1. Habitat selection models usually assume that the spatial distributions of animals depend positively on the distributions of resources and negatively on interference. However, the presence of conspecifics at a given location also signals safety and the availability of resources. This may induce followers to select contiguous patches and causes animals to cluster. Resource availability, interference and attraction therefore jointly lead to self-organized patterns in foraging animals. 2. We analyse the distribution of foraging shorebirds at landscape level on the basis of a resource-based model to establish, albeit indirectly, the importance of conspecific attraction and interference. 3. At 23 intertidal sites with a mean area of 170 ha spread out over the Dutch Wadden Sea, the spatial distribution of six abundant shorebird species was determined. The location of individuals and groups was mapped using a simple method based on projective geometry, enabling fast mapping of low-tide foraging shorebird distributions. We analysed the suitability of these 23 sites in terms of food availability and travel distances to high tide roosts. 4. We introduce an interference sensitivity scale which maps interference as a function of inter-individual distance. We thus obtain interference-insensitive species, which are only sensitive to interference at short inter-individual distances (and may thus pack densely) and interference-sensitive species which interfere over greater inter-individual distances (and thus form sparse flocks). 5. We found that interference-insensitive species like red knot ( Calidris canutus) and dunlins ( Calidris alpina) are more clustered than predicted by the spatial distribution of their food resources. This suggests that these species follow each other when selecting foraging patches. In contrast, curlew ( Numenius arquata) and grey plover ( Pluvialis squatarola), known to be sensitive to interference, form sparse flocks. Hence, resource-based models have better predictive power for interference-sensitive species than for interference-insensitive species. 6. It follows from our analysis that monitoring programmes, habitat selection models and statistical analyses should also consider the mechanisms of self-organization. [ABSTRACT FROM AUTHOR]

1. Non-consumptive effects of predators are increasingly recognized as important drivers of community assembly and structure. Specifically, habitat selection responses to top predators during colonization and oviposition can lead to large differences in aquatic community structure, composition and diversity. 2. These differences among communities due to predators may develop as communities assemble, potentially altering the relative quality of predator vs. predator-free habitats through time. If so, community assembly would be expected to modify the subsequent behavioural responses of colonists to habitats containing top predators. Here, we test this hypothesis by manipulating community assembly and the presence of fish in experimental ponds and measuring their independent and combined effects on patterns of colonization by insects and amphibians. 3. Assembly modified habitat selection of dytscid beetles and hylid frogs by decreasing or even reversing avoidance of pools containing blue-spotted sunfish ( Enneacanthus gloriosus). However, not all habitat selection responses to fish depended on assembly history. Hydrophilid beetles and mosquitoes avoided fish while chironomids were attracted to fish pools, regardless of assembly history. 4. Our results show that community assembly causes taxa-dependent feedbacks that can modify avoidance of habitats containing a top predator. Thus, non-consumptive effects of a top predator on community structure change as communities assemble and effects of competitors and other predators combine with the direct effects of top predators to shape colonization. 5. This work reinforces the importance of habitat selection for community assembly in aquatic systems, while illustrating the range of factors that may influence colonization rates and resulting community structure. Directly manipulating communities both during colonization and post-colonization is critical for elucidating how sequential processes interact to shape communities. [ABSTRACT FROM AUTHOR]

1. Researchers often use the spatial distribution of insect offspring as a measure of adult oviposition preferences, and then make conclusions about the consequences of these preferences for population growth and the relationship between life-history traits (e.g. oviposition preference and offspring performance). However, several processes other than oviposition preference can generate spatial patterns of offspring density (e.g. dispersal limitations, spatially heterogeneous mortality rates). Incorrectly assuming that offspring distributions reflect oviposition preferences may therefore compromise our ability to understand the mechanisms determining population distributions and the relationship between life-history traits. 2. The purpose of this study was to perform an empirical study at the whole-system scale to examine the movement and oviposition behaviours of the eastern tree hole mosquito Ochlerotatus triseriatus (Say) and test the importance of these behaviours in determining population distribution relative to other mechanisms. 3. A mark–release–recapture experiment was performed to distinguish among the following alternative hypotheses that may explain a previously observed aggregated distribution of tree hole mosquito offspring: (H1) mosquitoes prefer habitats with particular vegetation characteristics and these preferences determine the distribution of their offspring; (H2) mosquitoes distribute their eggs randomly or evenly throughout their environment, but spatial differences in developmental success generate an aggregated pattern of larval density; (H3) mosquitoes randomly colonize habitats, but have limited dispersal capability causing them to distribute offspring where founder populations were established; (H4) wind or other environmental factors may lead to passive aggregation, or spatial heterogeneity in adult mortality (H5), rather than dispersal, generates clumped offspring distributions. 4. Results indicate that the distribution of tree hole mosquito larvae is determined in part by adult habitat selection (H1), but do not exclude additional effects from passive aggregation (H4), or spatial patterns in adult mortality (H5). 5. This research illustrates the importance of studying oviposition behaviour at the population scale to better evaluate its relative importance in determining population distribution and dynamics. Moreover, this study demonstrates the importance of linking behavioural and population dynamics for understanding evolutionary relationships among life-history traits (e.g. preference and offspring performance) and predicting when behaviour will be important in determining population phenomena. [ABSTRACT FROM AUTHOR]

1. Long-term effects of conditions during early development on fitness are important for life history evolution and population ecology. Using multistrata mark–recapture models on 20 years of data, we quantified the relation between rearing conditions and lifetime fitness in a long-lived shorebird, the oystercatcher ( Haematopus ostralegus). We addressed specifically the relative contribution of short- and long-term effects of rearing conditions to overall fitness consequences. 2. Rearing conditions were defined by differences in natal habitat quality, in which there is a clear dichotomy in our study population. In the first year of life, fledglings from high-quality natal origin had a 1·3 times higher juvenile survival. Later in life (age 3–11), individuals of high-quality natal origin had a 1·6 times higher adult prebreeder survival. The most striking effect of natal habitat quality was that birds that were reared on high-quality territories had a higher probability of settling in high-quality habitat (44% vs. 6%). Lifetime reproductive success of individuals born in high-quality habitat was 2·2 times higher than that of individuals born in low-quality habitat. This difference increased further when fitness was calculated over several generations, due to a correlation between the quality of rearing conditions of parents and their offspring. 3. Long-term effects of early conditions contributed more to overall fitness differences as short-term consequences, contrary to common conceptions on this issue. 4. This study illustrates that investigating only short-term effects of early conditions can lead to the large underestimation of fitness consequences. We discuss how long-term consequences of early conditions may affect settlement decisions and source–sink population interactions. [ABSTRACT FROM AUTHOR]

1. Broad-scale telemetry studies have greatly improved our understanding of the ranging patterns and habitat-use of many large vertebrates. However, there often remains considerable uncertainty over the function of different areas or the factors influencing habitat selection. Further insights into these processes can be obtained through analyses of finer scale movement patterns. For example, search behaviour may be modified in response to prey distribution and abundance. 2. In this study, quantitative analysis techniques are applied to the movements of bottlenose dolphins, recorded from land using a theodolite, to increase our understanding of their foraging strategies. Movements were modelled as a correlated random walk (CRW) and a biased random walk (BRW) to identify movement types and using a first-passage time (FPT) approach, which quantifies the time allocated to different areas and identifies the location and spatial scale of intensive search effort. 3. Only a quarter of the tracks were classed as CRW movement. Turning angle and directionality appeared to be key factors in determining the type of movement adopted. A high degree of overlap in search effort between separate movement paths indicated that there were small key sites (0·3 km radius) within the study area (4 km2). Foraging behaviour occurred mainly within these intensive search areas, indicating that they were feeding sites. 4. This approach provides a quantitative method of identifying important foraging areas and their spatial scale. Such techniques could be applied to movement paths for a variety of species derived from telemetry studies and increase our understanding of their foraging strategies. [ABSTRACT FROM AUTHOR]

1. Few studies have related metrics of fitness to broad-scale, multivariate patterns of resource selection. 2. Our objective was to relate long-term predation-mortality patterns for adult woodland caribou [ Rangifer tarandus caribou (Banfield)] from Alberta, Canada (1991–2002), with patterns of multivariate habitat selection. 3. We first compared probabilities of radio-tracked caribou dying ( n = 55) from predation in habitats within the home range, controlling for habitat availability, with that expected from habitat selection probabilities for the same animals during life. We then compared survival rates of caribou ( n = 141) possessing dissimilar patterns of habitat selection using a Cox proportional hazards regression model. 4. Patterns in habitat-specific predation mortality differed significantly from expected given probabilities of habitat selection during life ( P < 0·0001). Cox regression indicated that mortality rates of caribou due to predation were affected significantly by and can be predicted from patterns of selection ( P = 0·02). 5. Our results strongly suggest that uplands (primarily mixed deciduous and coniferous forest) present caribou with higher than expected levels of predation risk, and that caribou can avoid predation by maximizing selection of peatlands (open, conifer-dominated bogs and fens). 6. Approaches presented in this study may be useful for ecologists interested in assessing the influence of mortality factors on broad-scale, multivariate resource selection. Linking metrics of fitness to multivariate resource selection will enable us to ask questions of evolutionary ecology once restricted to only the finest ecological scales. Journal of Animal Ecology (2005) 74, 701–707 doi: 10.1111/j.1365-2656.2005.00967.x [ABSTRACT FROM AUTHOR]

1. We used long-term radio-telemetry data to investigate how Serengeti lions (Panthera leo) distribute themselves with respect to hunting opportunities. Specifically, we investigate whether lions hunt in areas where prey are easy to capture or where prey are locally abundant.2. We used resource-selection functions (logistic regressions) to measure the location of kills/carcasses with respect to five different habitats: the view-sheds from large rocky outcrops, river confluences, woodland vegetation, erosion embankments and water sources.3. As expected for a sit-and-wait predator, resting lions spent more time in areas with good cover. On a broad-scale, lions shifted their ranges according to the seasonal movement of prey, but at a finer scale (< 100 m) lions fed in areas with high prey‘catchability’ rather than high prey density. Plains lions selected erosion embankments, view-sheds from rocky outcrops, and access to free water. Woodland lions tended to use erosion embankments, and woody vegetation.4. The results emphasize the importance of fine-scale landscape and habitat features when assessing predator–prey theory and conservation.Journal of Animal Ecology(2005)74, 559 –566doi: 10.1111/j.1365-2656.2005.00955.x [ABSTRACT FROM AUTHOR]

Dispersal contributes to spatio-temporal variation in population size and is a key process in studies of life history evolution and studies with conservation implications. However, dispersal is still one of the major gaps in our knowledge of ecological dynamics. The very large literature on metapopulation dynamics lacks empirical bases on dispersal and relevant behavioral parameters. We used multistate capture­ recapture models (data from 1988 to 2001) to address hypotheses about movement probability and habitat selection within a system of two breeding colonies in Audouin's gulls (Larus audouinii), an endemic species breeding in the Mediterranean and considered as threatened. Movement probability varied over time, and differed greatly between the colonies. We did not find evidence of an influence of colony size or density of predators on movement probability. In dispersers, our results did not support the hypotheses that movement probability between year t and t + 1 was influenced by mean breeding success in the colony of origin (i.e. an indicator of habitat quality) or the destination colony in year t or t + 1, or by the ratio of breeding success in these colonies in year t or t + 1 (i.e. quality gradient). Overall, movement probability was higher from the smaller colony to the larger, and from the colony with lower breeding success in year t to the more productive one. This provides slight support for two nonexclusive hypotheses about habitat selection (conspecific attraction and conspecific success attraction). Movement probability from the smaller, less productive colony was very high in some years, suggesting that the dynamics of both colonies were strongly influenced by adult dispersal. However, in absolute numbers, more individuals moved from the larger, more productive colony to the smaller one. This suggests that the system may function as a source­sink system. Use of multistate models to re-assess local survival showed that survival was lower in the less productive colony with higher emigration probability. This may reflect genuine differences in mortality between colonies, or more probably differences in permanent emigration from the study area. [ABSTRACT FROM AUTHOR]