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BACKGROUND: Spatial behavior, including home-ranging behaviors, habitat selection, and movement, can be extremely informative in estimating how animals respond to landscape heterogeneity. Responses in these spatial behaviors to features such as human land modification and resources can highlight a species' spatial strategy to maximize fitness and minimize mortality. These strategies can vary on spatial, temporal, and individual scales, and the combination of behaviors on these scales can lead to very different strategies among species. METHODS: Harnessing the variation present at these scales, we characterized how species may respond to stimuli in their environments ranging from broad- to fine-scale spatial responses to human modification in their environment. Using 15 bobcat-years and 31 coyote-years of GPS data from individuals inhabiting a landscape encompassing a range of human land modification, we evaluated the complexity of both species' responses to human modification on the landscape through their home range size, habitat selection, and functional response behaviors, accounting for annual, seasonal, and diel variation. RESULTS: Bobcats and coyotes used different strategies in response to human modification in their home ranges, with bobcats broadly expanding their home range with increases in human modification and displaying temporal consistency in functional response in habitat selection across both season and time of day. Meanwhile, coyotes did not expand their home ranges with increased human modification, but instead demonstrated fine-scale responses to human modification with habitat selection strategies that sometimes varied by time of day and season, paired with functional responses in selection behaviors. CONCLUSIONS: These differences in response to habitat, resources, and human modification between the two species highlighted the variation in spatial behaviors animals can use to exist in anthropogenic environments. Categorizing animal spatial behavior based on these spatiotemporal responses and individual variation can help in predicting how a species will respond to future change based on their current spatial behavior.
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Encounters between animals occur when animals are close in space and time. Encounters are important in many ecological processes including sociality, predation and disease transmission. Despite this, there is little theory regarding the spatial distribution of encounters and no formal framework to relate environmental characteristics to encounters. The probability of encounter could be estimated with resource selection functions (RSFs) by comparing locations where encounters occurred to available locations where they may have occurred, but this estimate is complicated by the hierarchical nature of habitat selection. We developed a method to relate resources to the relative probability of encounter based on a scale-integrated habitat selection framework. This framework integrates habitat selection at multiple scales to obtain an appropriate estimate of availability for encounters. Using this approach, we related encounter probabilities to landscape resources. The RSFs describe habitat associations at four scales, home ranges within the study area, areas of overlap within home ranges, locations within areas of overlap, and encounters compared to other locations, which can be combined into a single scale-integrated RSF. We apply this method to intraspecific encounter data from two species: white-tailed deer (Odocoileus virginianus) and elk (Cervus elaphus) and interspecific encounter data from a two-species system of caribou (Rangifer tarandus) and coyote (Canis latrans). Our method produced scale-integrated RSFs that represented the relative probability of encounter. The predicted spatial distribution of encounters obtained based on this scale-integrated approach produced distributions that more accurately predicted novel encounters than a naïve approach or any individual scale alone. Our results highlight the importance of accounting for the conditional nature of habitat selection in estimating the habitat associations of animal encounters as opposed to 'naïve' comparisons of encounter locations with general availability. This method has direct relevance for testing hypotheses about the relationship between habitat and social or predator-prey behaviour and generating spatial predictions of encounters. Such spatial predictions may be vital for understanding the distribution of encounters driving disease transmission, predation rates and other population and community-level processes.
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Ciervos , Ecosistema , Animales , Ciervos/fisiología , Modelos Biológicos , Coyotes/fisiología , Reno/fisiología , Conducta AnimalRESUMEN
SNAPSHOT USA is a multicontributor, long-term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application (https://www.snapshot-usa.org/). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights (https://www.wildlifeinsights.org/), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22-5.9 arrays per 100,000 km2), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.
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Fotograbar , Estados Unidos , Animales , Mamíferos , EcosistemaRESUMEN
Invasive alien species are among the most pervasive threats to biodiversity. Invasive species can cause catastrophic reductions in populations of native and endemic species and the collapse of ecosystem function. A second major global conservation concern is the extirpation of large-bodied mobile animals, including long-distance migrants, which often have keystone ecological roles over extensive spatial extents. Here, we report on a potentially catastrophic synergy between these phenomena that threatens the endemic biota of the Galapagos Archipelago. We used GPS telemetry to track 140 migratory journeys by 25 Western Santa Cruz Island Galapagos tortoises. We plotted the spatial interaction between tortoise migrations and recently established non-native forest dominated by the invasive tree Cedrela odorata (Cedrela forest). We qualified (a) the proportion of migratory journeys that traversed Cedrela forest, and (b) the probability that this observed pattern occurred by chance. Tortoise migrations were overwhelmingly restricted to small corridors between Cedrela forest blocks, indicating clear avoidance of those blocks. Just eight of 140 migrations traversed extensive Cedrela stands. Tortoises avoid Cedrela forest during their migrations. Further expansion of Cedrela forest threatens long-distance migration and population viability of critically endangered Galapagos tortoises. Applied research to determine effective management solutions to mitigate Cedrela invasion is a high priority.
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Raccoon rabies virus (RRV) has been managed using multiple vaccination strategies, including oral rabies vaccination and trap-vaccinate-release (TVR). Identifying a rabies vaccination strategy for an area is a nontrivial task. Vaccination strategies differ in the amount of effort and monetary costs required to achieve a particular level of vaccine seroprevalence (efficiency). Simulating host movement relative to different vaccination strategies in silico can provide a useful tool for exploring the efficiency of different vaccination strategies. We refined a previously developed individual-based model of raccoon movement to evaluate vaccination strategies for urban Hamilton, Ontario, Canada. We combined different oral rabies vaccination baiting (hand baiting, helicopter, and bait stations) with TVR strategies and used GPS data to parameterize and simulate raccoon movement in Hamilton. We developed a total of 560 vaccination strategies, in consultation with the Ontario Ministry of Natural Resources and Forestry, for RRV control in Hamilton. We documented the monetary costs of each vaccination strategy and estimated the population seroprevalence. Intervention costs and seroprevalence estimates were used to calculate the efficiency of each strategy to meet targets set for the purpose of RRV control. Estimated seroprevalence across different strategies varied widely, ranging from less than 5% to more than 70%. Increasing bait densities (distributed using by hand or helicopter) led to negligible increase in seroprevalence. Helicopter baiting was the most efficient and TVR was the least efficient, but helicopter-based strategies led to lower levels of seroprevalence (6-12%) than did TVR-based strategies (17-70%). Our simulations indicated that a mixed strategy including at least some TVR may be the most efficient strategy for a local urban RRV control program when seroprevalence levels >30% may be required. Our simulations provide information regarding the efficiency of different vaccination strategies for raccoon populations, to guide local RRV control in urban settings.
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Vacunas Antirrábicas , Virus de la Rabia , Rabia , Animales , Rabia/epidemiología , Rabia/prevención & control , Rabia/veterinaria , Mapaches , Estudios Seroepidemiológicos , Administración Oral , Vacunación/veterinaria , Ontario/epidemiologíaRESUMEN
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.
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Migración Animal , Animales Salvajes , COVID-19 , Mamíferos , Cuarentena , Animales , Humanos , Animales Salvajes/fisiología , Animales Salvajes/psicología , COVID-19/epidemiología , Mamíferos/fisiología , Mamíferos/psicología , MovimientoRESUMEN
Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an 'epidemiological landscape' connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a 'movement-pathogen pace of life' heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.
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Transmisión de Enfermedad Infecciosa , Ecología , Epidemiología , Movimiento , GeografíaRESUMEN
Individual variation in habitat selection and movement behaviour is receiving growing attention, but primarily with respect to characterizing behaviours in different contexts as opposed to decomposing structure in behaviour within populations. This focus may be limiting advances in understanding the diversity of individual behaviour and its influence on population organization. We propose a framework for characterizing variation in space-use behaviour with the aim of advancing interpretation of its form and function. Using outputs from integrated step-selection analyses of 20 years of telemetry data from African elephants Loxodonta Africana, we developed four metrics characterizing differentiation in resource selection behaviour within a population (specialization [magnitude of the response independent of direction], heterogeneity [inter-individual variation], consistency [temporal shift in response] and reversal [frequency of directional changes in the response]). We contrasted insight from the developed metrics relative to the mean population response using an example focused on two covariates. We then expanded this contrast by evaluating if the metrics identify structurally important information on seasonal shifts in resource selection behaviours in addition to that provided by mean selection coefficients through principal component analyses (PCAs) and a random forest classification. The simplified example highlighted that for some covariates focusing on the population average failed to capture complex individual variation in behaviours. The PCAs revealed that the developed metrics provided additional information in explaining the patterns in elephant selection beyond that offered by population average covariate values. For elephants, specialization and heterogeneity were informative, with specialization often being a better descriptor of differences in seasonal resource selection behaviour than population average responses. Summarizing these metrics spatially and temporally, we illustrate how these metrics can provide insights on overlooked aspects of animal behaviour. Our work offers a new approach in how we conceptualize variation in space-use behaviour (i.e. habitat selection and movement) by providing ways of encapsulating variation that enables diagnoses of the drivers of individual-level variability in a population. The developed metrics explicitly distil how variation in a behaviour is structured among individuals and over time which could facilitate comparative work across time, populations or strata within populations.
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Benchmarking , Elefantes , Animales , Conducta Animal , Ecosistema , Conducta EspacialRESUMEN
Oral baiting is used to deliver vaccines to wildlife to prevent, control, and eliminate infectious diseases. A central challenge is how to spatially distribute baits to maximize encounters by target animal populations, particularly in urban and suburban areas where wildlife such as raccoons (Procyon lotor) are abundant and baits are delivered along roads. Methods from movement ecology that quantify movement and habitat selection could help to optimize baiting strategies by more effectively targeting wildlife populations across space. We developed a spatially explicit, individual-based model of raccoon movement and oral rabies vaccine seroconversion to examine whether and when baiting strategies that match raccoon movement patterns perform better than currently used baiting strategies in an oral rabies vaccination zone in greater Burlington, Vermont, USA. Habitat selection patterns estimated from locally radio-collared raccoons were used to parameterize movement simulations. We then used our simulations to estimate raccoon population rabies seroprevalence under currently used baiting strategies (actual baiting) relative to habitat selection-based baiting strategies (habitat baiting). We conducted simulations on the Burlington landscape and artificial landscapes that varied in heterogeneity relative to Burlington in the proportion and patch size of preferred habitats. We found that the benefits of habitat baiting strongly depended on the magnitude and variability of raccoon habitat selection and the degree of landscape heterogeneity within the baiting area. Habitat baiting improved seroprevalence over actual baiting for raccoons characterized as habitat specialists but not for raccoons that displayed weak habitat selection similar to radiocollared individuals, except when baits were delivered off roads where preferred habitat coverage and complexity was more pronounced. In contrast, in artificial landscapes with either more strongly juxtaposed favored habitats and/or higher proportions of favored habitats, habitat baiting performed better than actual baiting, even when raccoons displayed weak habitat preferences and where baiting was constrained to roads. Our results suggest that habitat selection-based baiting could increase raccoon population seroprevalence in urban-suburban areas, where practical, given the heterogeneity and availability of preferred habitat types in those areas. Our novel simulation approach provides a flexible framework to test alternative baiting strategies in multiclass landscapes to optimize bait-distribution strategies.
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Vacunas Antirrábicas , Rabia , Administración Oral , Animales , Animales Salvajes , Rabia/epidemiología , Rabia/prevención & control , Rabia/veterinaria , Mapaches , Estudios Seroepidemiológicos , Vacunación/métodos , Vacunación/veterinariaRESUMEN
BACKGROUND: Lethal removal of invasive species, such as wild pigs (Sus scrofa), is often the most efficient approach for reducing their negative impacts. Wild pigs are one of the most widespread and destructive invasive mammals in the USA. Lethal management techniques are a key approach for wild pigs and can alter wild pig spatial behavior, but it is unclear how wild pigs respond to the most common removal technique, trapping. We investigated the spatial behavior of wild pigs following intensive removal of conspecifics via trapping at three sites within the Savannah River Site, SC, USA. We evaluated changes in wild pig densities, estimated temporal shifts in home-range properties, and evaluated fine-scale movement responses of wild pigs to removal. RESULTS: We observed a significant reduction in the density of wild pigs in one site following removal via trapping while a qualitative reduction was observed in another site. We found little evidence of shifts in pig home-ranging behavior following removal. However, we did observe a nuanced response in movement behavior of wild pigs to the removal at the scale of the GPS locations (4 h), including increased movement speed and reduced selection for vegetation rich areas. CONCLUSION: Our work provides a better understanding of the impact of removal via trapping on wild pig movement and its implications for management. The lack of shift in home-range characteristics observed illustrates how targeted trapping could be used to provide temporary relief for species sensitive to wild pig consumption such as ground nesting birds or agricultural crops.
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Especies Introducidas , Sus scrofa , Animales , Productos Agrícolas , Movimiento , PorcinosRESUMEN
Landscape planning that ensures the ecological integrity of ecosystems is critical in the face of rapid human-driven habitat conversion and development pressure. Wildlife tracking data provide unique and valuable information on animal distribution and location-specific behaviors that can serve to increase the efficacy of such planning. Given the spatiotemporal complexity inherent to animal movements, the interaction between movement behavior and a location is often oversimplified in commonly applied analyses of tracking data. We analyzed GPS-tracking-derived metrics of intensity of use, structural properties (based on network theory), and properties of the movement path (speed and directionality) with machine learning to define homogeneous spatial movement types. We applied our approach to a long-term tracking data set of over 130 African elephants (Loxodonta africana) in an area under pressure from infrastructure development. We identified 5 unique location-specific movement categories displayed by elephants, generally defined as high, medium, and low use intensity, and 2 types of connectivity corridors associated with fast and slow movements. High-use and slow-movement corridors were associated with similar landscape characteristics associated with productive areas near water, whereas low-use and fast corridors were characterized by areas of low productivity farther from water. By combining information on intensity of use, properties of movement paths, and structural aspects of movement across the landscape, our approach provides an explicit definition of the functional role of areas for movement across the landscape that we term the movescape. This combined, high-resolution information regarding wildlife space use offers mechanistic information that can improve landscape planning.
Caracterización del Paisaje de Movimiento para Identificar Hábitats y Corredores de Fauna Importantes Resumen La planeación de paisajes que asegura la integridad ecológica de los ecosistemas es muy importante de cara a la rápida conversión de hábitats llevada por la acción humana y la presión del desarrollo. Los datos de rastreo de fauna proporcionan información única y valiosa sobre la distribución animal y el comportamiento específico por localidad que puede servir para incrementar la eficiencia de dicha planeación. Dada la complejidad espaciotemporal inherente al movimiento animal, la interacción entre la conducta de movimiento y la ubicación con frecuencia se ve sobre simplificada en los análisis de información de rastreos aplicados comúnmente. Analizamos las medidas derivadas de rastreos por GPS de la intensidad de uso, las propiedades estructurales (basadas en la teoría de redes) y las propiedades de la vía de movimiento (velocidad y direccionalidad) con aprendizaje automatizado para definir los tipos de movimiento espacial homogéneo. Aplicamos nuestra estrategia a un conjunto de datos de rastreo a largo plazo de más de 130 elefantes africanos (Loxodonta africana) en un área bajo presión ocasionada por el desarrollo de infraestructura. Identificamos cinco categorías de movimiento específico por localidad exhibidas por los elefantes, definidas en términos generales como intensidad de uso alta, media y baja. También identificamos dos tipos de corredores de conectividad asociados con movimientos rápidos y lentos. Los corredores de intensidad de uso alta y movimiento lento estuvieron asociados con las características similares de paisaje asociadas a las áreas productivas cercanas a cuerpos de agua, mientras que los corredores de intensidad baja y movimiento rápido estuvieron caracterizados por áreas de baja productividad alejadas de los cuerpos de agua. Con la combinación de la información sobre la intensidad de uso, las propiedades de las vías de movimiento y los aspectos estructurales del movimiento a lo largo del paisaje, nuestra estrategia proporciona una definición explícita del papel funcional que tienen las áreas de movimiento en el paisaje, la cual denominamos paisaje de movimiento (movescape). Esta información combinada y de alta resolución con respecto al uso espacial por la fauna ofrece información mecánica que puede mejorar la planeación del paisaje.
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Ecosistema , Elefantes , Distribución Animal , Animales , Animales Salvajes , Conservación de los Recursos Naturales , MovimientoRESUMEN
Wildlife tracking is one of the most frequently employed approaches to monitor and study wildlife populations. To date, the application of tracking data to applied objectives has focused largely on the intensity of use by an animal in a location or the type of habitat. While this has provided valuable insights and advanced spatial wildlife management, such interpretation of tracking data does not capture the complexity of spatio-temporal processes inherent to animal behaviour and represented in the movement path. Here, we discuss current and emerging approaches to estimate the behavioural value of spatial locations using movement data, focusing on the nexus of conservation behaviour and movement ecology that can amplify the application of animal tracking research to contemporary conservation challenges. We highlight the importance of applying behavioural ecological approaches to the analysis of tracking data and discuss the utility of comparative approaches, optimization theory and economic valuation to gain understanding of movement strategies and gauge population-level processes. First, we discuss innovations in the most fundamental movement-based valuation of landscapes, the intensity of use of a location, namely dissecting temporal dynamics in and means by which to weight the intensity of use. We then expand our discussion to three less common currencies for behavioural valuation of landscapes, namely the assessment of the functional (i.e. what an individual is doing at a location), structural (i.e. how a location relates to use of the broader landscape) and fitness (i.e. the return from using a location) value of a location. Strengthening the behavioural theoretical underpinnings of movement ecology research promises to provide a deeper, mechanistic understanding of animal movement that can lead to unprecedented insights into the interaction between landscapes and animal behaviour and advance the application of movement research to conservation challenges. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.
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Conservación de los Recursos Naturales/métodos , Ecología/métodos , Ecosistema , Etología/métodos , Movimiento , Animales , Conducta AnimalRESUMEN
Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.
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Conducta Animal , Ecosistema , Elefantes , Actividad Motora , Animales , Sistemas de Información Geográfica , KeniaRESUMEN
To understand how migratory behavior evolved and to predict how migratory species will respond to global environmental change it is important to quantify the fitness consequences of intra- and inter-individual variation in migratory behavior. Intra-individual variation includes behavioral responses to changing environmental conditions and hence behavioral plasticity in the context of novel or variable conditions. Inter-individual variation determines the degree of variation on which selection can act and the rate of evolutionary responses to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of giant Galápagos tortoises (Chelonoidis spp.) and its energetic consequences. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, and integrate movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter-individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by average expectations estimated from multi-annual averaged conditions. This variation is associated with an average annual loss in efficiency of ~15% relative to optimal timing based on year-specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more by past "normal" conditions than responses to prevailing, changing conditions. Our work offers insights into the level of environmental-tuning in migratory behavior and a general framework for future research across taxa.
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Tortugas , Migración Animal , Animales , Evolución Biológica , Herbivoria , MovimientoRESUMEN
Defining the relationship between nutrients and parasitism is complicated by shifts in host physiology and population density, which can both mediate the effects of host diet on parasites and vice versa. We examined the relationship between nutrient availability and an abundant parasite capable of both horizontal and vertical transmission (Hamiltosporidium tvaerminnensis) of a planktonic crustacean, Daphnia magna, in rock pools on Baltic Sea Skerry islands. We found that the relative availability of nutrients directly affected infection prevalence; parasite prevalence was higher in pools with higher particulate N:P ratios. Infection prevalence was not related to Daphnia population densities. A complementary experiment that examined host responses to an N:P gradient in mesocosms indicated that high N:P ratios can increase spore load in the hosts. We surmise that high N:P food increases Daphnia feeding rate, which increases their contact with parasite spores and leads to higher prevalence and more intense infections. We found no direct evidence that parasite-induced changes in host nutrient use affected nutrient dynamics in pools. However, the relationship between diet N:P and the parasite's prevalence and load is consistent with previously documented patterns of this parasite's effect on host nutrient use. Taken together, this study suggests that high N:P ratios in food may benefit the parasite in multiple ways and could create environments that favour horizontal transmission over vertical transmission for parasites capable of both transmission routes. If so, nutrient limitation could have long-term consequences for host-parasite evolution.
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Microsporidios , Parásitos , Animales , Daphnia , Interacciones Huésped-Parásitos , Nutrientes , PrevalenciaRESUMEN
Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a framework for conservationists to analyze movement data. Functions created for the analyses are available within the R package moveNT.
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Ecología/métodos , Conducta Espacial , Distribución Animal , Animales , Ciervos , Elefantes , Movimiento , TortugasRESUMEN
Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator-prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability and predator space use, we examined patterns of black bear (Ursus americanus) predation of caribou (Rangifer tarandus) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per-capita rate at which bears killed calves followed a type-I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time-scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator-prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore.
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Cadena Alimentaria , Conducta Predatoria , Reno/fisiología , Ursidae/fisiología , Animales , Animales Recién Nacidos/fisiología , Ambiente , Femenino , Terranova y Labrador , Dinámica Poblacional , Análisis Espacio-TemporalRESUMEN
For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.
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Cambio Climático , Ecosistema , Animales , Canadá , Bovinos , Dinámica Poblacional , Conducta PredatoriaRESUMEN
The reasons that lead some animals to seasonally migrate, and others to remain in the same area year-round, are poorly understood. Associations between traits, such as body size, and migration provide clues. For example, larger species and individuals are more likely to migrate. One explanation for this size bias in migration is that larger animals are capable of moving faster (movement hypothesis). However, body size is linked to many other biological processes. For instance, the energetic balances of larger animals are generally more sensitive to variation in food density because of body size effects on foraging and metabolism and this sensitivity could drive migratory decisions (forage hypothesis). Identifying the primary selective forces that drive migration ultimately requires quantifying fitness impacts over the full annual migratory cycle. Here, we develop a full annual migratory cycle model from metabolic and foraging theory to compare the importance of the forage and movement hypotheses. We parameterize the model for Galapagos tortoises, which were recently discovered to be size-dependent altitudinal migrants. The model predicts phenomena not included in model development including maximum body sizes, the body size at which individuals begin to migrate, and the seasonal timing of migration and these predictions generally agree with available data. Scenarios strongly support the forage hypothesis over the movement hypothesis. Furthermore, male Galapagos tortoises on Santa Cruz Island would be unable to grow to their enormous sizes without access to both highlands and lowlands. Whereas recent research has focused on links between traits and the migratory phases of the migratory cycle, we find that effects of body size on the non-migratory phases are far more important determinants of the propensity to migrate. Larger animals are more sensitive to changing forage conditions than smaller animals with implications for maintenance of migration and body size in the face of environmental change.
Asunto(s)
Migración Animal , Tortugas , Animales , Tamaño Corporal , Femenino , Masculino , Movimiento , Estaciones del AñoRESUMEN
BACKGROUND: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises (Chelonoidis sp.) using a multi-year (2009-2014) GPS dataset from three different Galapagos Islands. RESULTS: With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as "exploratory residence". CONCLUSIONS: Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.