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Migration can influence dynamics of pathogen-host interactions. However, it is not clearly known how migration pattern, in terms of the configuration of the migration network and the synchrony of migration, affects infection prevalence. We therefore applied a discrete-time SIR model, integrating environmental transmission and migration, to various migration networks, including networks with serial, parallel, or both serial and parallel stopover sites, and with various levels of migration synchrony. We applied the model to the infection of avian influenza virus in a migratory geese population. In a network with only serial stopover sites, increasing the number of stopover sites reduced infection prevalence, because with every new stopover site, the amount of virus in the environment was lower than that in the previous stopover site, thereby reducing the exposure of the migratory population. In a network with parallel stopover sites, both increasing the number and earlier appearance of the stopover sites led to an earlier peak of infection prevalence in the migratory population, because the migratory population is exposed to larger total amount of virus in the environment, speeding-up the infection accumulation. Furthermore, higher migration synchrony reduced the average number of cumulative infection, because the majority of the population can fly to a new stopover site where the amount of virus is still relatively low and has not been increased due to virus shedding of infected birds. Our simulations indicate that a migration pattern with multiple serial stopover sites and with highly synchronized migration reduces the infection prevalence.
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Gansos , Vírus da Influenza A , Migração Animal , Animais , Prevalência , Estações do AnoRESUMO
Wildlife management to reduce the impact of wildlife on their habitat can be done in several ways, among which removing animals (by either culling or translocation) is most often used. There are, however, alternative ways to control wildlife densities, such as opening or closing water points. The effects of these alternatives are poorly studied. In this paper, we focus on manipulating large herbivores through the closure of water points (WPs). Removal of artificial WPs has been suggested in order to change the distribution of African elephants, which occur in high densities in national parks in Southern Africa and are thought to have a destructive effect on the vegetation. Here, we modeled the long-term effects of different scenarios of WP closure on the spatial distribution of elephants, and consequential effects on the vegetation and other herbivores in Kruger National Park, South Africa. Using a dynamic ecosystem model, SAVANNA, scenarios were evaluated that varied in availability of artificial WPs; levels of natural water; and elephant densities. Our modeling results showed that elephants can indirectly negatively affect the distributions of meso-mixed feeders, meso-browsers, and some meso-grazers under wet conditions. The closure of artificial WPs hardly had any effect during these natural wet conditions. Under dry conditions, the spatial distribution of both elephant bulls and cows changed when the availability of artificial water was severely reduced in the model. These changes in spatial distribution triggered changes in the spatial availability of woody biomass over the simulation period of 80 years, and this led to changes in the rest of the herbivore community, resulting in increased densities of all herbivores, except for giraffe and steenbok, in areas close to rivers. The spatial distributions of elephant bulls and cows showed to be less affected by the closure of WPs than most of the other herbivore species. Our study contributes to ecologically informed decisions in wildlife management. The results from this modeling exercise imply that long-term effects of this intervention strategy should always be investigated at an ecosystem scale.
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Conservação dos Recursos Naturais/métodos , Ecossistema , Elefantes , Modelos Biológicos , Água , Animais , Simulação por Computador , Plantas/classificação , Densidade Demográfica , Dinâmica PopulacionalRESUMO
BACKGROUND: Animal movement arises from complex interactions between animals and their heterogeneous environment. To better understand the movement process, it can be divided into behavioural, temporal and spatial components. Although methods exist to address those various components, it remains challenging to integrate them in a single movement analysis. METHODS: We present an analytic workflow that integrates the behavioural, temporal and spatial components of the movement process and their interactions, which also allows for the assessment of the relative importance of those components. We construct a daily cyclic covariate to represent temporally cyclic movement patterns, such as diel variation in activity, and combine the three components in a multi-modal Hidden Markov Model framework using existing methods and R functions. We compare the trends and statistical fits of models that include or exclude any of the behavioural, spatial and temporal components, and perform variance partitioning on the model predictions that included all components to assess their relative importance to the movement process, both in isolation and in interaction. RESULTS: We apply our workflow to a case study on the movements of plains zebra, blue wildebeest and eland antelope in a South African reserve. Behavioural modes impacted movement the most, followed by diel rhythms and then the spatial environment (viz. tree cover and terrain slope). Interactions between the components often explained more of the movement variation than the marginal effect of the spatial environment did on its own. Omitting components from the analysis led either to the inability to detect relationships between input and response variables, resulting in overgeneralisations when drawing conclusions about the movement process, or to detections of questionable relationships that appeared to be spurious. CONCLUSIONS: Our analytic workflow can be used to integrate the behavioural, temporal and spatial components of the movement process and quantify their relative contributions, thereby preventing incomplete or overly generic ecological interpretations. We demonstrate that understanding the drivers of animal movement, and ultimately the ecological phenomena that emerge from it, critically depends on considering the various components of the movement process, and especially the interactions between them.
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Modern sensor technologies increasingly enrich studies in wildlife behavior and ecology. However, constraints on weight, connectivity, energy and memory availability limit their implementation. With the advent of edge computing, there is increasing potential to mitigate these constraints, and drive major advancements in wildlife studies.
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Animais Selvagens , Computação em Nuvem , Animais , EcologiaRESUMO
Surface water is one of the constraining resources for herbivore populations in semi-arid regions. Artificial waterpoints are constructed by wildlife managers to supplement natural water supplies, to support herbivore populations. The aim of this paper is to analyse how a landowner may realize his ecological and economic goals by manipulating waterpoints for the management of an elephant population, a water-dependent species in the presence of water-independent species. We develop a theoretical bio-economic framework to analyse the optimization of wildlife management objectives (in this case revenue generation from both consumptive and non-consumptive use and biodiversity conservation), using waterpoint construction as a control variable. The model provides a bio-economic framework for analysing optimization problems where a control has direct effects on one herbivore species but indirect effects on the other. A landowner may be interested only in maximization of profits either from elephant offtake and/or tourism revenue, ignoring the negative effects that could be brought about by elephants to biodiversity. If the landowner does not take the indirect effects of waterpoints into consideration, then the game reserve management, as the authority entrusted with the sustainable management of the game reserve, might use economic instruments such as subsidies or taxes to the landowners to enforce sound waterpoint management.
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Conservação dos Recursos Naturais , Elefantes , Modelos Econômicos , Abastecimento de Água , Animais , Antílopes , EcossistemaRESUMO
Highly pathogenic avian influenza viruses' (HPAIVs) transmission from wild birds to poultry occurs globally, threatening animal and public health. To predict the HPAI outbreak risk in relation to wild bird densities and land cover variables, we performed a case-control study of 26 HPAI outbreaks (cases) on Dutch poultry farms, each matched with four comparable controls. We trained machine learning classifiers to predict outbreak risk with predictors analyzed at different spatial scales. Of the 20 best explaining predictors, 17 consisted of densities of water-associated bird species, 2 of birds of prey, and 1 represented the surrounding landscape, i.e., agricultural cover. The spatial distribution of mallard (Anas platyrhynchos) contributed most to risk prediction, followed by mute swan (Cygnus olor), common kestrel (Falco tinnunculus) and brant goose (Branta bernicla). The model successfully distinguished cases from controls, with an area under the receiver operating characteristic curve of 0.92, indicating accurate prediction of HPAI outbreak risk despite the limited numbers of cases. Different classification algorithms led to similar predictions, demonstrating robustness of the risk maps. These analyses and risk maps facilitate insights into the role of wild bird species and support prioritization of areas for surveillance, biosecurity measures and establishments of new poultry farms to reduce HPAI outbreak risks.
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1. Understanding and accurately predicting the spatial patterns of habitat use by organisms is important for ecological research, biodiversity conservation and ecosystem management. However, this understanding is complicated by the effects of spatial scale, because the scale of analysis affects the quantification of species-environment relationships. 2. We therefore assessed the influence of environmental context (i.e. the characteristics of the landscape surrounding a site), varied over a large range of scales (i.e. ambit radii around focal sites), on the analysis and prediction of habitat selection by African elephants in Kruger National Park, South Africa. 3. We focused on the spatial scaling of the elephants' response to their main resources, forage and water, and found that the quantification of habitat selection strongly depended on the scales at which environmental context was considered. Moreover, the inclusion of environmental context at characteristic scales (i.e. those at which habitat selectivity was maximized) increased the predictive capacity of habitat suitability models. 4. The elephants responded to their environment in a scale-dependent and perhaps hierarchical manner, with forage characteristics driving habitat selection at coarse spatial scales, and surface water at fine spatial scales. 5. Furthermore, the elephants exhibited sexual habitat segregation, mainly in relation to vegetation characteristics. Male elephants preferred areas with high tree cover and low herbaceous biomass, whereas this pattern was reversed for female elephants. 6. We show that the spatial distribution of elephants can be better understood and predicted when scale-dependent species-environment relationships are explicitly considered. This demonstrates the importance of considering the influence of spatial scale on the analysis of spatial patterning in ecological phenomena.
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Ecossistema , Elefantes/fisiologia , Animais , Demografia , Feminino , Masculino , Modelos Biológicos , África do SulRESUMO
In savannas, the tree-grass balance is governed by water, nutrients, fire and herbivory, and their interactions. We studied the hypothesis that herbivores indirectly affect vegetation structure by changing the availability of soil nutrients, which, in turn, alters the competition between trees and grasses. Nine abandoned livestock holding-pen areas (kraals), enriched by dung and urine, were contrasted with nearby control sites in a semi-arid savanna. About 40 years after abandonment, kraal sites still showed high soil concentrations of inorganic N, extractable P, K, Ca and Mg compared to controls. Kraals also had a high plant production potential and offered high quality forage. The intense grazing and high herbivore dung and urine deposition rates in kraals fit the accelerated nutrient cycling model described for fertile systems elsewhere. Data of a concurrent experiment also showed that bush-cleared patches resulted in an increase in impala dung deposition, probably because impala preferred open sites to avoid predation. Kraal sites had very low tree densities compared to control sites, thus the high impala dung deposition rates here may be in part driven by the open structure of kraal sites, which may explain the persistence of nutrients in kraals. Experiments indicated that tree seedlings were increasingly constrained when competing with grasses under fertile conditions, which might explain the low tree recruitment observed in kraals. In conclusion, large herbivores may indirectly keep existing nutrient hotspots such as abandoned kraals structurally open by maintaining a high local soil fertility, which, in turn, constrains woody recruitment in a negative feedback loop. The maintenance of nutrient hotspots such as abandoned kraals by herbivores contributes to the structural heterogeneity of nutrient-poor savanna vegetation.
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Ecossistema , Gado/metabolismo , Necessidades Nutricionais , Poaceae/metabolismo , Solo/análise , Árvores/metabolismo , Animais , Cálcio/análise , Gado/crescimento & desenvolvimento , Magnésio/análise , Nitrogênio/análise , Fósforo/análise , Poaceae/crescimento & desenvolvimento , Dinâmica Populacional , Potássio/análise , Plântula/crescimento & desenvolvimento , Plântula/metabolismo , Solo/química , África do Sul , Fatores de Tempo , Árvores/crescimento & desenvolvimentoRESUMO
Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher early warning system that is based on the movement responses of non-targeted sentinel animals, which naturally respond to threats by fleeing and changing herd topology. We analyzed human-evasive movement patterns of 135 mammalian savanna herbivores of four different species, using an internet-of-things architecture with wearable sensors, wireless data transmission and machine learning algorithms. We show that the presence of human intruders can be accurately detected (86.1% accuracy) and localized (less than 500 m error in 54.2% of the experimentally staged intrusions) by algorithmically identifying characteristic changes in sentinel movement. These behavioral signatures include, among others, an increase in movement speed, energy expenditure, body acceleration, directional persistence and herd coherence, and a decrease in suitability of selected habitat. The key to successful identification of these signatures lies in identifying systematic deviations from normal behavior under similar conditions, such as season, time of day and habitat. We also show that the indirect costs of predation are not limited to vigilance, but also include (1) long, high-speed flights; (2) energetically costly flight paths; and (3) suboptimal habitat selection during flights. The combination of wireless biologging, predictive analytics and sentinel animal behavior can benefit wildlife conservation via early poacher detection, but also solve challenges related to surveillance, safety and health.
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Migração Animal , Crime , Algoritmos , Animais , Conservação dos Recursos Naturais , Espécies em Perigo de Extinção , HumanosRESUMO
The concentrations of resources in forage are not perfectly balanced to the needs of an animal, and food species differ in these concentrations. Under many circumstances, animals should thus forage on multiple food species to attain the maximum and most balanced intake of several resources. In this article we present a model to extend optimal foraging theory to incorporate concurrent foraging for multiple resources from several food species. A balancing of resources is achieved by representing the amount of a resource as the time during which it is used. Optimization is considered at two hierarchical levels: the time spent in a patch and the proportion of patches of each food species included in the foraging path. Our model results show that the balancing of resource intake can be achieved at the level of the foraging path, while the maximization of intake can be realized at the nested patch level. The choice for a food species should be dependent on the differences in intake and resource ratios between the food species. Under free choice of food species, the optimal patch residence time is subject not to differences between patches but to the local intake rate.
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Ecossistema , Cadeia Alimentar , Modelos Biológicos , AnimaisRESUMO
[This corrects the article DOI: 10.1186/s40462-016-0071-z.].
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BACKGROUND: Urbanization causes modification, fragmentation and loss of native habitats. Such landscape changes threaten many arboreal and gliding mammals by limiting their movements through treeless parts of a landscape and by making the landscape surrounding suitable habitat patches more inhospitable. Here, we investigate the effects of landscape structure and habitat availability on the home-range use and movement patterns of the Siberian flying squirrel (Pteromys volans) at different spatial and temporal scales. We followed radio-tagged individuals in a partly urbanized study area in Eastern Finland, and analysed how landscape composition and connectivity affected the length and speed of movement bursts, distances moved during one night, and habitat and nest-site use. RESULTS: The presence of urban habitat on movement paths increased both movement lengths and speed whereas nightly distances travelled by males decreased with increasing amount of urban habitat within the home range. The probability of switching from the present nest site to another nest site decreased with increasing distance among the nest sites, but whether the nest sites were connected or unconnected by forests did not have a clear effect on nest switching. Flying squirrels preferred to use mature forests for their movements at night. CONCLUSIONS: Our results suggest that the proximity to urban habitats modifies animal movements, possibly because animals try to avoid such habitats by moving faster through them. Urbanization at the scale of an entire home range can restrict their movements. Thus, maintaining a large enough amount of mature forests around inhabited landscape fragments will help protect forest specialists in urban landscapes. The effect of forested connections remains unclear, highlighting the difficulty of measuring and preserving connectivity in a species-specific way.