Resource manipulation reveals interactive phenotype-dependent foraging in free-ranging lizards.

Recent evidence suggests that individuals differ in foraging tactics and this variation is often linked to an individual's behavioural type (BT). Yet, while foraging typically comprises a series of search and handling steps, empirical investigations have rarely considered BT-dependent effects across multiple stages of the foraging process, particularly in natural settings. In our long-term sleepy lizard (Tiliqua rugosa) study system, individuals exhibit behavioural consistency in boldness (measured as an individual's willingness to approach a novel food item in the presence of a threat) and aggressiveness (measured as an individual's response to an 'attack' by a conspecific dummy). These BTs are only weakly correlated and have previously been shown to have interactive effects on lizard space use and movement, suggesting that they could also affect lizard foraging performance, particularly in their search behaviour for food. To investigate how lizards' BTs affect their foraging process in the wild, we supplemented food in 123 patches across a 120-ha study site with three food abundance treatments (high, low and no-food controls). Patches were replenished twice a week over the species' entire spring activity season and feeding behaviours were quantified with camera traps at these patches. We tracked lizards using GPS to determine their home range (HR) size and repeatedly assayed their aggressiveness and boldness in designated assays. We hypothesised that bolder lizards would be more efficient foragers while aggressive ones would be less attentive to the quality of foraging patches. We found an interactive BT effect on overall foraging performance. Individuals that were both bold and aggressive ate the highest number of food items from the foraging array. Further dissection of the foraging process showed that aggressive lizards in general ate the fewest food items in part because they visited foraging patches less regularly, and because they discriminated less between high and low-quality patches when revisiting them. Bolder lizards, in contrast, ate more tomatoes because they visited foraging patches more regularly, and ate a higher proportion of the available tomatoes at patches during visits. Our study demonstrates that BTs can interact to affect different search and handling components of the foraging process, leading to within-population variation in foraging success. Given that individual differences in foraging and movement will influence social and ecological interactions, our results highlight the potential role of BT's in shaping individual fitness strategies and population dynamics.

Robust Time-of-Arrival Location Estimation Algorithms for Wildlife Tracking.

Time-of-arrival transmitter localization systems, which use measurements from an array of sensors to estimate the location of a radio or acoustic emitter, are now widely used for tracking wildlife. Outlier measurements can severely corrupt estimated locations. This article describes a new suite of location estimation algorithms for such systems. The new algorithms detect and discard outlier time-of-arrival observations, which can be caused by non-line-of-sight propagation, radio interference, clock glitches, or an overestimation of the signal-to-noise ratio. The new algorithms also detect cases in which two locations are equally consistent with measurements and can usually select the correct one. The new algorithms can also infer approximate altitude information from a digital elevation map to improve location estimates close to one of the sensors. Finally, the new algorithms approximate the covariance matrix of location estimates in a simpler and more reliable way than the baseline algorithm. Extensive testing on real-world data involving mobile transmitters attached to wild animals demonstrates the efficacy of the new algorithms. Performance testing also shows that the new algorithms are fast and that they can easily cope with high-throughput real-time loads.

A telemetry study shows that an endangered nocturnal avian species roosts in extremely dry habitats to avoid predation.

Describing animal space use is essential for understanding their ecological needs and for planning effective conservation schemes. Notably, certain biomes and life histories are understudied due to methodological challenges in tracking animals in their natural habitats. Specifically, both arid environments and nocturnal species are not sufficiently researched compared to diurnal species and to other biomes. This knowledge gap hinders our ability to properly prioritize habitats for species protection in areas undergoing human-related development. Here, we investigate the movement ecology of the Egyptian Nightjar (Caprimulgus aegyptius) in the arid Dead-sea region of Israel, the Palestinian Authority (the West Bank) and Jordan. This nocturnal insectivore is a cryptic desert-dweller and was considered locally extinct until it was rediscovered in 2016. For this work we tracked twelve individuals using GPS tags to determine how this resource-poor environment affects their home range, (predicting large areas), habitat use, and day-roost ecology. We found that the tracked Egyptian Nightjars had a much larger home range area than other Nightjar species, commuting nightly between foraging grounds and day-roosts. We found, as expected, intensive foraging activity at agricultural fields, where artificial irrigation likely supports higher resource (insect) density. Additionally, we found that individuals showed very high roosting site fidelity, often returning to the same specific site, located in extremely dry and exposed habitats, presumably for predator avoidance. This finding highlights the ecological value of these barren habitats that are often considered "lifeless" and therefore of lower priority for conservation. Consequently, our research demonstrates the importance of describing the space-use of nocturnal animals in arid habitats for conservation efforts.

ViewShedR: a new open-source tool for cumulative, subtractive and elevated line-of-sight analysis.

Many environmental and ecological studies require line of sight (LOS) and/or viewshed analyses. While tools for performing these analyses from digital elevation models (DEMs) are widespread, they are either too restrictive, inaccessible or pricey and difficult to use. This methodological gap is potentially imperative for scholars using solutions like telemetry tracking systems or spatial ecology landscape mapping. Here we present ViewShedR-a free, open-source and intuitive graphical user-interface application for performing LOS calculations, including cumulative, subtractive (areas covered by towers A + B or by A but not by B, respectively), and elevated-target analyses. ViewShedR is implemented in the widely used R environment, thus facilitating usage and further modification by end-users. We provide two working examples for ViewShedR in the context of permanent animal-tracking systems requiring simultaneous tag-detection by multiple towers (receivers): first, the ATLAS system for terrestrial animals in the Harod Valley, Israel; and second, an acoustic telemetry array for marine animals in the Dry Tortugas, Florida. ViewShedR allowed effective tower deployment and finding partially detected tagged animals in the ATLAS system. Similarly, it allowed us to identify reception shadows cast by islands in the marine array. We hope ViewShedR will facilitate deployment of tower arrays for tracking, communication networks and other ecological applications.

Social situations differ in their contribution to population-level social structure in griffon vultures.

Social relationships among animals emerge from interactions in multiple ecological and social situations. However, we seldom ask how each situation contributes to the global structure of a population, and whether different situations contribute different information about social relationships and the position of individuals within the social fabric. Griffon vultures (Gyps fulvus) interact socially in multiple situations, including communal roosting, joint flights, and co-feeding. These social interactions can influence population-level outcomes, such as disease transmission and information sharing that determine survival and response to changes. We examined the unique contribution of each social and ecological situation to the social structure of the population and individuals' positions within the overall social network using high-resolution GPS tracking. We found that the number of individuals each vulture interacted with (degree) was best predicted by diurnal interactions-both during flights and on the ground (such as when feeding). However, the strength of social bonds, that is, the number of interactions an individual had (strength), was best predicted by interactions on the ground-both during the day (e.g., while feeding) and at night (e.g., while roosting) but not by interactions while flying. Thus, social situations differ in their impact on the relationships that individuals form. By incorporating the ecological situations in which social interactions occur we gain a more complete view of how social relationships are formed and which situations are important for different types of interactions.

Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking.

BACKGROUND: Movement is central to understanding the ecology of animals. The most robustly definable segments of an individual's lifetime track are its diel activity routines (DARs). This robustness is due to fixed start and end points set by a 24-h clock that depends on the individual's quotidian schedule. An analysis of day-to-day variation in the DARs of individuals, their comparisons among individuals, and the questions that can be asked, particularly in the context of lunar and annual cycles, depends on the relocation frequency and spatial accuracy of movement data. Here we present methods for categorizing the geometry of DARs for high frequency (seconds to minutes) movement data. METHODS: Our method involves an initial categorization of DARs using data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four scalar "whole-path metrics" of trajectory geometry: 1. net displacement (distance between start and end points), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in north-eastern Israel. We conducted a principle components analysis (PCA) to obtain a factor, PC1, that essentially captures the scale of movement. We then used a generalized linear mixed model with PC1 as the dependent variable to assess the effects of age and sex on movement. RESULTS: We clustered 6230 individual DARs into 7 categories representing different shapes and scale of the owls nightly routines. Five categories based on size and elongation were classified as closed (i.e. returning to the same roost), one as partially open (returning to a nearby roost) and one as fully open (leaving for another region). Our PCA revealed that the DAR scale factor, PC1, accounted for 86.5% of the existing variation. It also showed that PC2 captures the openness of the DAR and accounted for another 8.4% of the variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal quadrimester, as well as identify some idiosyncratic behavior of individuals within family groups in relation to location. Finally, we showed in two ways that DARs were significantly larger in young than adults and in males than females. CONCLUSION: Our study offers a new method for using high-frequency movement data to classify animal diel movement routines. Insights into the types and distributions of the geometric shape and size of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis.

Plasma cholinesterase activity: A benchmark for rapid detection of pesticide poisoning in an avian scavenger.

Poisoning due to exposure to organophosphate and carbamate pesticides is a common threat for many wildlife species, especially for scavengers such as vultures. The Griffon vulture population (Gyps fulvus), for instance, is deteriorating in the Eastern Mediterranean, and is considered to be critically endangered in Israel, where 48 out of 107 (45 %) known injury/mortality cases in 2010-2021 were caused by poisoning. Lack of specific clinical indications, together with levels of organophosphate or carbamate pesticides too low to detect, challenge the ability to diagnose and treat such poisoning events. The activity of cholinesterase (ChE) in plasma has the potential to serve as an effective biomarker for monitoring exposure to anticholinesterase pesticides in live vultures. Yet, the applicability of this approach has been limited by intra- and inter-species variations in ChE basal levels. The present study aims to provide a benchmark for ChE activity levels in healthy Griffons and their intra-species variation. Blood samples from free-roaming (n = 231) and captive (n = 63) Griffons were collected during routine monitoring, and ChE levels were determined using a colorimetric method. We established that the ChE in the plasma of Griffons reflects mostly acetylcholinesterase as the dominant form. ChE levels in healthy Griffons are 0.601 ± 0.011 U/ml (mean ± SE), while Griffons with suspected or confirmed pesticide poisoning display much lower levels of ChE activity (typically <0.3 U/ml). We also characterized the age dependence of ChE activity, as well as differences among groups from different locations or origins. Our study provides a rapid diagnostic tool for the detection of exposure to organophosphate and carbamate pesticides that should facilitate the lifesaving treatment and the conservation of this species. Moreover, our protocols can be adapted to other species and geographical areas, addressing pesticide poisoning worldwide and contributing to the protection of endangered species and their ecological functions (e.g. sanitation by scavengers).

Movement predictability of individual barn owls facilitates estimation of home range size and survival.

BACKGROUND: There is growing attention to individuality in movement, its causes and consequences. Similarly to other well-established personality traits (e.g., boldness or sociability), conspecifics also differ repeatedly in their spatial behaviors, forming behavioral types ("spatial-BTs"). These spatial-BTs are typically described as the difference in the mean-level among individuals, and the intra-individual variation (IIV, i.e., predictability) is only rarely considered. Furthermore, the factors determining predictability or its ecological consequences for broader space-use patterns are largely unknown, in part because predictability was mostly tested in captivity (e.g., with repeated boldness assays). Here we test if (i) individuals differ in their movement and specifically in their predictability. We then investigate (ii) the consequences of this variation for home-range size and survival estimates, and (iii) the factors that affect individual predictability. METHODS: We tracked 92 barn owls (Tyto alba) with an ATLAS system and monitored their survival. From these high-resolution (every few seconds) and extensive trajectories (115.2 ± 112.1 nights; X̅ ± SD) we calculated movement and space-use indices (e.g., max-displacement and home-range size, respectively). We then used double-hierarchical and generalized linear mix-models to assess spatial-BTs, individual predictability in nightly max-displacement, and its consistency across time. Finally, we explored if predictability levels were associated with home-range size and survival, as well as the seasonal, geographical, and demographic factors affecting it (e.g., age, sex, and owls' density). RESULTS: Our dataset (with 74 individuals after filtering) revealed clear patterns of individualism in owls' movement. Individuals differed consistently both in their mean movement (e.g., max-displacement) and their IIV around it (i.e., predictability). More predictable individuals had smaller home-ranges and lower survival rates, on top and beyond the expected effects of their spatial-BT (max-displacement), sex, age and ecological environments. Juveniles were less predictable than adults, but the sexes did not differ in their predictability. CONCLUSION: These results demonstrate that individual predictability may act as an overlooked axis of spatial-BT with potential implications for relevant ecological processes at the population level and individual fitness. Considering how individuals differ in their IIV of movement beyond the mean-effect can facilitate understanding the intraspecific diversity, predicting their responses to changing ecological conditions and their population management.

Behavioural ecology at the spatial-social interface.

Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the 'spatial-social interface' as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial-social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density-dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial-social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial-social interface.

Beyond simple habituation: Anthropogenic habitats influence the escape behaviour of spur-winged lapwings in response to both human and non-human threats.

Habitat development may affect wildlife behaviour, favouring individuals or behaviours that cope better with perceived threats (predators). Bolder behaviours in human-dominated habitats (HDH; e.g. urban and rural settlements) may represent habituation specifically to humans, or a general reduction in predator-avoidance response. However, such carry-over effects across threat types (i.e. beyond humans) and phases of the escape sequence have not been well studied to date. Here we investigated escape behaviours of a locally common wader species, the spur-winged lapwing Vanellus spinosus. We assayed their flight initiation distance (FID) and subsequent escape behaviours in agricultural areas and in HDH. We found that lapwings in HDH were bolder, and that the difference was manifested in several phases of the predator-avoidance sequence (shorter FIDs, shorter distances fled, and a higher probability of escape by running vs. flying). When re-approached (by an observer) after landing, lapwings in HDH were also more repetitive in their FID than those in other habitats. To determine whether this apparent bolder behaviour in HDH areas is merely a consequence of habituation to humans or represents a broader behavioural change, we introduced an additional threat type-a remotely-operated taxidermic jackal ('Jack-Truck'). Finding bolder responses in the HDH to the human threat alone (and not to the Jack-Truck) could have supported the habituation hypothesis. In contrast, however, we found a bolder response in the HDH to both threat types, as well as a correlation between their FIDs across different sites. These bolder behaviours suggest that HDH impose a broader behavioural change on lapwings, rather than just simple habituation. Overall, our findings demonstrate how FID trials can reveal strong behavioural carry-over effects of HDH following human and non-human threats, including effects on the subsequent phases of escaping the predator. Further, FID assays may reveal consistent behavioural types when assessed under field conditions, and offer a direct way to differentiate among the various poorly understood and non-mutually exclusive mechanisms that lead to behavioural differences among organisms in HDH. The mechanistic perspective is essential for understanding how rapid urbanization impacts wildlife behaviour, populations, and the range of behaviours within them, even in species apparently resilient to such environmental changes.

Personality, spatiotemporal ecological variation and resident/explorer movement syndromes in the sleepy lizard.

Individual variation in movement is profoundly important for fitness and offers key insights into the spatial and temporal dynamics of populations and communities. Nonetheless, individual variation in fine-scale movement behaviours is rarely examined even though animal tracking devices offer the long-term, high-resolution, repeatable data in natural conditions that are ideal for studying this variation. Furthermore, of the few studies that consider individual variation in movement, even fewer also consider the internal traits and environmental factors that drive movement behaviour which are necessary for contextualising individual differences in movement patterns. In this study, we GPS tracked a free-ranging population of sleepy lizards Tiliqua rugosa, each Austral spring over 5 years to examine consistent among-individual variation in movement patterns, as well as how these differences were mediated by key internal and ecological factors. We found that individuals consistently differed in a suite of weekly movement traits, and that these traits strongly covaried among-individuals, forming movement syndromes. Lizards fell on a primary movement continuum, from 'residents' that spent extended periods of time residing within smaller core areas of their home range, to 'explorers' that moved greater distances and explored vaster areas of the environment. Importantly, we also found that these consistent differences in lizard movement were related to two ecologically important animal personality traits (boldness and aggression), their sex, key features of the environment (including food availability, and a key water resource), habitat type and seasonal variation (cool/moist vs. hot/drier) in environmental conditions. Broadly, these movement specialisations likely reflect variation in life-history tactics including foraging and mating tactics that ultimately underlie key differences in space use. Such information can be used to connect phenotypic population structure to key ecological and evolutionary processes, for example social networks and disease-transmission pathways, further highlighting the value of examining individual variation in movement behaviour.

A guide to pre-processing high-throughput animal tracking data.

Modern, high-throughput animal tracking increasingly yields 'big data' at very fine temporal scales. At these scales, location error can exceed the animal's step size, leading to mis-estimation of behaviours inferred from movement. 'Cleaning' the data to reduce location errors is one of the main ways to deal with position uncertainty. Although data cleaning is widely recommended, inclusive, uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is relatively scarce. A pipeline for cleaning massive high-throughput datasets must balance ease of use and computationally efficiency, in which location errors are rejected while preserving valid animal movements. Another useful feature of a pre-processing pipeline is efficiently segmenting and clustering location data for statistical methods while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time-consuming, and to boost reproducibility, pre-processing pipelines must be automated. We provide guidance on building pipelines for pre-processing high-throughput animal tracking data to prepare it for subsequent analyses. We apply our proposed pipeline to simulated movement data with location errors, and also show how large volumes of cleaned data can be transformed into biologically meaningful 'residence patches', for exploratory inference on animal space use. We use tracking data from the Wadden Sea ATLAS system (WATLAS) to show how pre-processing improves its quality, and to verify the usefulness of the residence patch method. Finally, with tracks from Egyptian fruit bats Rousettus aegyptiacus, we demonstrate the pre-processing pipeline and residence patch method in a fully worked out example. To help with fast implementation of standardised methods, we developed the R package atlastools, which we also introduce here. Our pre-processing pipeline and atlastools can be used with any high-throughput animal movement data in which the high data-volume combined with knowledge of the tracked individuals' movement capacity can be used to reduce location errors. atlastools is easy to use for beginners while providing a template for further development. The common use of simple yet robust pre-processing steps promotes standardised methods in the field of movement ecology and leads to better inferences from data.

Gulls foraging in landfills: Does atmospheric exposure to halogenated flame retardants result in bioaccumulation?

Several bird species have adapted to foraging in landfills, although these sites are known to represent significant sources of emissions of toxic semi-volatile chemicals including the halogenated flame retardants (HFRs) (e.g., polybrominated diphenyl ethers (PBDEs) and emerging compounds). The objective of this study was to investigate the association between atmospheric exposure to PBDEs and selected emerging HFRs and their bioaccumulation in landfill-foraging birds. We determined HFR concentrations in liver of 58 GPS-tagged ring-billed gulls (Larus delawarensis) breeding in a colony near Montreal (Canada) as well as their atmospheric exposure determined using a miniature bird-borne passive air sampler. PBDE mixtures were the most abundant HFRs determined in passive air samplers (daily exposure rates of ∑9PentaBDE: 47.4 ± 6.5 pg/day; DecaBDE: 36.0 ± 6.3 pg/day, and ∑3OctaBDE: 3.4 ± 0.5 pg/day) and liver (∑9PentaBDE: 68.1 ± 8.9 ng/g ww; DecaBDE: 52.3 ± 8.1 ng/g ww, and ∑3OctaBDE: 12.8 ± 2.1 ng/g ww), and their concentrations increased with the presence probability of gulls in landfills. We found a spatial relationship between the local sources of atmospheric exposure to PBDEs and the sites associated with greatest PBDE concentrations in liver. Specifically, the atmospheric exposure index was correlated with the bioaccumulation index (Pearson r for ∑9PentaBDE: r = 0.63, p < 0.001; DecaBDE: r = 0.66, p < 0.001, and ∑3OctaBDE: r = 0.42, p < 0.001). However, we found no correlation at the individual level between daily exposure rates of HFRs in passive air samplers and their liver concentrations. This suggests that complex exposure pathways combined with toxicokinetic factors shaped HFR profiles in gull liver, potentially confounding the relationships with atmospheric exposure.

Social interactions in striped hyena inferred from camera trap data: is it more social than previously thought?

Understanding the drivers promoting sociality over solitariness in animal species is imperative for predicting future population trends and informing conservation and management. In this study we investigate the social structure of a desert dwelling population of striped hyena Hyaena hyaena. This species is historically regarded as strictly solitary albeit being the least studied of the extant Hyaenids. Accumulating evidence regarding the frequency of social interactions suggests a revision of striped hyena social structure is required. We hypothesized that striped hyena has a social structure that is more complex than expected for a strictly solitary species. For that end, we deployed an array of camera-traps in a remote desert region in Israel, and compared observed frequencies of striped hyena co-occurrence against null models to test whether hyena co-occurred more than expected by chance. Seven adults were (re)captured by our camera-traps in 49 different instances over 83 tracking days. Of these, 6 exhibited shared space-use around a scarce, isolated perennial water source. Five of them, co-occurred with other hyena (in 3 instances) significantly more frequent than expected by chance (and that timing suggests reproduction is unlikely to be the driving factor). Our findings substantiate evidence of complex social structure in striped hyena, highlight the importance of a scarce resource in space-use and sociality, and provide a baseline for future research of striped hyena social structure. We suggest that similar methods be employed to evaluate social structure in other "solitary species" to better understand their social dynamics.

Disturbance modifies payoffs in the explore-exploit trade-off.

Decision-making agents face a fundamental trade-off between exploring new opportunities with risky outcomes versus exploiting familiar options with more certain but potentially suboptimal outcomes. Although mediation of this trade-off is essential to adaptive behavior and has for decades been assumed to modulate performance, the empirical consequences of human exploratory strategies are unknown beyond laboratory or theoretical settings. Leveraging 540,000 vessel position records from 2494 commercial fishing trips along with corresponding revenues, here we find that during undisturbed conditions, there was no relationship between exploration and performance, contrary to theoretical predictions. However, during a major disturbance event which closed the most-utilized fishing grounds, explorers benefited significantly from less-impacted revenues and were also more likely to continue fishing. We conclude that in stochastic natural systems characterized by non-stationary rewards, the role of exploration in buffering against disturbance may be greater than previously thought in humans.

Vectors with autonomy: what distinguishes animal-mediated nutrient transport from abiotic vectors?

Animal movements are important drivers of nutrient redistribution that can affect primary productivity and biodiversity across various spatial scales. Recent work indicates that incorporating these movements into ecosystem models can enhance our ability to predict the spatio-temporal distribution of nutrients. However, the role of animal behaviour in animal-mediated nutrient transport (i.e. active subsidies) remains under-explored. Here we review the current literature on active subsidies to show how the behaviour of active subsidy agents makes them both ecologically important and qualitatively distinct from abiotic processes (i.e. passive subsidies). We first propose that animal movement patterns can create similar ecological effects (i.e. press and pulse disturbances) in recipient ecosystems, which can be equal in magnitude to or greater than those of passive subsidies. We then highlight three key behavioural features distinguishing active subsidies. First, organisms can transport nutrients counter-directionally to abiotic forces and potential energy gradients (e.g. upstream). Second, unlike passive subsidies, organisms respond to the patterns of nutrients that they generate. Third, animal agents interact with each other. The latter two features can form positive- or negative-feedback loops, creating patterns in space or time that can reinforce nutrient hotspots in places of mass aggregations and/or create lasting impacts within ecosystems. Because human-driven changes can affect both the space-use of active subsidy species and their composition at both population (i.e. individual variation) and community levels (i.e. species interactions), predicting patterns in nutrient flows under future modified environmental conditions depends on understanding the behavioural mechanisms that underlie active subsidies and variation among agents' contributions. We conclude by advocating for the integration of animal behaviour, animal movement data, and individual variation into future conservation efforts in order to provide more accurate and realistic assessments of changing ecosystem function.

Predicting Habitat Choice after Rapid Environmental Change.

Decisions made while searching for settlement sites (e.g., nesting, oviposition) often have major fitness implications. Despite numerous case studies, we lack theory to explain why some species are thriving while others are making poor habitat choices after environmental change. We develop a model to predict (1) which kinds of environmental change have larger, negative effects on fitness, (2) how evolutionary history affects susceptibility to environmental change, and (3) how much lost fitness can be recovered via readjustment after environmental change. We model the common scenario where animals search an otherwise inhospitable matrix, encountering habitats of varying quality and settling when finding a habitat better than a threshold quality level. We consider decisions and fitness before environmental change, immediately following change (assuming that animals continue to use their previously adaptive decision rules), and after optimal readjustment (e.g., via learning or evolution). We find that decreases in survival per time step searching and declines in habitat quality or availability generally have stronger negative effects than reduced season duration. Animals that were adapted to good conditions remained choosy after conditions declined and thus suffered more from environmental change than those adapted to poor conditions. Readjustment recovered much of the fitness lost through a reduction in average habitat quality but recovered much less following reductions in habitat availability or survival while searching. Our model offers novel predictions for empiricists to test as well as suggestions for prioritizing alternative mitigation steps.

Synergistic effect of land-use and vegetation greenness on vulture nestling body condition in arid ecosystems.

Climate-driven environmental change and land-use change often interact in their impact on biodiversity, but these interactions have received little scientific attention. Here we study the effects of climate-driven environmental variation (i.e. vegetation greenness) and land-use (protected versus unprotected areas) on body condition of vulture nestlings in savannah landscapes. We combine ringing data on nestling measurements of two vultures (lappet-faced and African white-backed vulture) with land-use and environmental variables. We show that body condition of white-backed vulture nestlings decreased through the study period and was lowest inside protected areas. For the lappet-faced vulture, nestling condition was improved during harsh years with lower than average vegetation greenness assumed to result in increased ungulate mortality, but only within protected areas. Such interaction was not tested for the white-backed vulture due to collinearity. The species-specific effects of land-use and vegetation greenness on nestling condition of the two sympatric vulture species likely stem from their different life-histories, diet preferences and foraging behaviour. While translation of current findings on nestling conditions to their possible influence on population demography and species persistence require further studies, our findings demonstrate how environmental change may trigger selective bottom-up ecosystem responses in arid environments under global change.

Social Information Links Individual Behavior to Population and Community Dynamics.

When individual animals make decisions, they routinely use information produced intentionally or unintentionally by other individuals. Despite its prevalence and established fitness consequences, the effects of such social information on ecological dynamics remain poorly understood. Here, we synthesize results from ecology, evolutionary biology, and animal behavior to show how the use of social information can profoundly influence the dynamics of populations and communities. We combine recent theoretical and empirical results and introduce simple population models to illustrate how social information use can drive positive density-dependent growth of populations and communities (Allee effects). Furthermore, social information can shift the nature and strength of species interactions, change the outcome of competition, and potentially increase extinction risk in harvested populations and communities.