Habitat preferences of adult Canada Jays Fuirst, Matthew; Norris, Joschka Mcleod, D. Ryan
Canadian journal of zoology,
06/2022, Letnik:
100, Številka:
6
Journal Article
Recenzirano
Habitat preferences in animals are often examined during the breeding period when individuals are easier to observe. However, habitat use may change once young become independent and if resource ...availability shifts with seasonality. While Canada Jays (Perisoreus canadensis (Linnaeus, 1766)) in Algonquin Provincial Park, Ontario, Canada, have been studied for several decades, there is no information on habitat use outside of the fall and late-winter nesting period, where they primarily used conifer forests. Using radio telemetry and resource selection functions comparing used versus available habitats, we estimated home-range size and habitat preferences of 12 adult Canada Jays (n = 334 locations) in the spring and summer. Mean (+ or -SD) home-range size from minimum convex polygons was 84 (+ or -48 ha) and ranged from 35 to 201 ha. Canada Jays strongly preferred forest-wetland edges, showed a weak preference for coniferous forests, a corresponding weak avoidance of shade-tolerant hardwood forests, and used mixed forest and wetlands in proportion to their availability. Our results suggest that, while adult Canada Jays use multiple types of habitat during the post-breeding period, they also key into forest-wetland edges, likely to take advantage of emergent prey while remaining near forested areas to maximize protection from predators.
The decreasing status of on IUCN of Koklass pheasant (Pucrasia macrolopha) belongs to the family Phasianidae and the order Galliform needs the attention of researchers. The species with habitats as ...low as 6,000 feet and as high as 11,000 feet certainly cover a broad variety of habitats, such a wide altitude range embraces a diverse range of habitats. Insufficient research has been conducted on the suitability of moist temperate forests as a potential habitat for the Koklass pheasant. Therefore, this study was carried out to explore habitat suitability in 15 different sites which were located in the 4 districts of Hazara Division using GIS data science and environmental variables. A random sampling technique was used for laying out the transect. Overall, 45 line transects (Length 2-4 km, Width 10-30 m) were laid out in study sites. The size of sample plots for trees was 10x10m, for shrubs (4 x4m), and herbs and grasses 1x1m. The other habitat parameters like elevation, slope, cover, and frequency of plant at each point were also considered. We found the uneven distribution of Koklass pheasant in the Hazara Division. There were 59 occurrence points identified and highlighted the distribution of Koklass pheasant in the study area. Although all environmental variables were preferred by Koklass pheasant in its habitat statistical analysis proved that slope, level of disturbance, tree and shrub frequency of habitat contributed mostly to the presence of Koklass in each study site except the contribution of soil and herbs. The potential suitable habitat of Koklass pheasant was estimated to be 439.6 km.sup.2 areas starting from Abbottabad to Mansehra in the Hazara division. Awareness and enforcing legal protection are recommended for the conservation of Koklass Pheasant in Moist temperate forest.
Habitat‐selection analyses allow researchers to link animals to their environment via habitat‐selection or step‐selection functions, and are commonly used to address questions related to wildlife ...management and conservation efforts. Habitat‐selection analyses that incorporate movement characteristics, referred to as integrated step‐selection analyses, are particularly appealing because they allow modelling of both movement and habitat‐selection processes.
Despite their popularity, many users struggle with interpreting parameters in habitat‐selection and step‐selection functions. Integrated step‐selection analyses also require several additional steps to translate model parameters into a full‐fledged movement model, and the mathematics supporting this approach can be challenging for many to understand.
Using simple examples, we demonstrate how weighted distribution theory and the inhomogeneous Poisson point process can facilitate parameter interpretation in habitat‐selection analyses. Furthermore, we provide a ‘how to’ guide illustrating the steps required to implement integrated step‐selection analyses using the amt package
By providing clear examples with open‐source code, we hope to make habitat‐selection analyses more understandable and accessible to end users.
Habitat‐selection analyses allow researchers to link animals to their environment in support of wildlife management and conservation efforts. We provide a ‘how to' guide for correctly interpreting parameters in habitat‐ and step‐selection functions and for implementing integrated step‐selection analyses using the amt package for program R.
According to the ideal‐free distribution (IFD), individuals within a population are free to select habitats that maximize their chances of success. Assuming knowledge of habitat quality, the IFD ...predicts that average fitness will be approximately equal among individuals and between habitats, while density varies, implying that habitat selection will be density dependent. Populations are often assumed to follow an IFD, although this assumption is rarely tested with empirical data, and may be incorrect when territoriality indicates habitat selection tactics that deviate from the IFD (e.g. ideal‐despotic distribution or ideal‐preemptive distribution).
When territoriality influences habitat selection, species' density will not directly reflect components of fitness such as reproductive success or survival. In such cases, assuming an IFD can lead to false conclusions about habitat quality. We tested theoretical models of density‐dependent habitat selection on a species known to exhibit territorial behaviour in order to determine whether commonly applied habitat models are appropriate under these circumstances.
We combined long‐term radiotelemetry and census data from grey wolves Canis lupus in the Upper Peninsula of Michigan, USA to relate spatiotemporal variability in wolf density to underlying classifications of habitat within a hierarchical state‐space modelling framework. We then iteratively applied isodar analysis to evaluate which distribution of habitat selection best described this recolonizing wolf population.
The wolf population in our study expanded by >1,000% during our study (~50 to >600 individuals), and density‐dependent habitat selection was most consistent with the ideal‐preemptive distribution, as opposed to the ideal‐free or ideal‐despotic alternatives.
Population density of terrestrial carnivores may not be positively correlated with the fitness value of their habitats, and density‐dependent habitat selection patterns may help to explain complex predator–prey dynamics and cascading indirect effects. Source–sink population dynamics appear likely when species exhibit rapid growth and occupy interspersed habitats of contrasting quality. These conditions are likely and have implications for large carnivores in many systems, such as areas in North America and Europe where large predator species are currently recolonizing their former ranges.
Recolonizing wolves exhibited density‐dependent habitat selection by preemptively occupying high quality sites, following theory about territorial species distributions. Density‐dependent selection patterns occurred with respect to prey availability, human conflict potential and land cover variation in stream density. These findings have implications of source–sink population dynamics for recovering large carnivores following saturation of suitable habitats.
1. Describing distribution and abundance is requisite to exploring interactions between organisms and their environment. Recently, the resource selection function (RSF) has emerged to replace many of ...the statistical procedures used to quantify resource selection by animals. 2. A RSF is defined by characteristics measured on resource units such that its value for a unit is proportional to the probability of that unit being used by an organism. It is solved using a variety of techniques, particularly the binomial generalized linear model. 3. Observing dynamics in a RSF - obtaining substantially different functions at different times or places for the same species - alerts us to the varying ecological processes that underlie resource selection. 4. We believe that there is a need for us to reacquaint ourselves with ecological theory when interpreting RSF models. We outline a suite of factors likely to govern ecologically based variation in a RSF. In particular, we draw attention to competition and density-dependent habitat selection, the role of predation, longitudinal changes in resource availability and functional responses in resource use. 5. How best to incorporate governing factors in a RSF is currently in a state of development; however, we see promise in the inclusion of random as well as fixed effects in resource selection models, and matched case-control logistic regression. 6. Investigating the basis of ecological dynamics in a RSF will allow us to develop more robust models when applied to forecasting the spatial distribution of animals. It may also further our understanding of the relative importance of ecological interactions on the distribution and abundance of species.
Tortoise ecology is poorly studied in East Africa. Here, using two terrestrial Testudinidae (Stigmochelys pardalis and Kinixys belliana) as study models, we (i) present basic demographic ...characteristics (sex-ratio, and density), (ii) describe correlates of their presence at two spatial scales (micro-habitat and macro-habitat), (iii) evaluate the effects of rainfall on their seasonal activity patterns, and (iv) analyze abundance patterns in relation to macro- and micro-habitat characteristics. We also describe an experiment, using tortoise shells, that can allow to control, and eventually correct, the reliability of observed data by taking into account the detectability of the study species in the wild. On the basis of a suite of statistical analysis and GIS-based elaborations, we confirmed, and further uncovered, the remarkable ecological differences existing between S. pardalis and K. belliana. The habitat use was different interspecifically, with K. belliana being much more linked to dense vegetation spots, often nearby waterbodies, whereas S. pardalis being an habitat generalist, at both micro- and macrohabitat scale. Nonetheless, juveniles of both species were observed in areas with significantly higher % soil covered by vegetation taller than 200 cm than adults of both sexes. This different habitat selection is hypothesized to be due to antipredatory reasons. Overall, our data suggests that interspecific competition should be minimal between these species.
•A detection experiments using real shells was carried out.•Similar experimental approaches are suggested when studying tortoise habitat.•Two tortoises from South Sudan were studied.•The habitat use was different interspecifically at two spatial scales.•Conservation implications are presented.
Though native to Scotland, the grey wolf (Canis lupus) was extirpated c.250 years ago as part of a global eradication drive. The global population has recently expanded, now occupying 67% of its ...former range. Evidence is growing that apex predators provide a range of ecological benefits, most stemming from the reduction of overgrazing by deer-something from which Scotland suffers. In this study, we build a rule-based habitat suitability model for wolves on the Scottish mainland. From existing literature, we identify the most important variables as land cover, prey density, road density and human density, and establish thresholds of suitability for each. Fuzzy membership functions are used to assign suitability values to each variable, followed by fuzzy overlay to combine all four: a novel approach to habitat suitability modelling for terrestrial mammals. Model sensitivity is tested for land cover and prey density, as these variables constitute a knowledge gap and an incomplete dataset, respectively. The Highlands and Grampian mountains emerge strongly and consistently as the most suitable areas, largely due to high negative covariance between prey density and road/human density. Sensitivity testing reveals the models are fairly robust to changes in prey density, but less robust to changes in the scoring of land cover, with the latter altering the distribution of land mainly through the 70-100% suitability range. However, in statistical significance tests, only the least and most generous versions of the model emerge as giving significantly different results. Depending on the version of the model, a contiguous area of between 10,139km.sup.2 and 18,857km.sup.2 is shown to be 80 to 100% suitable. This could be sufficient to support between 50 and 94 packs of four wolves, if the average pack range size is taken to be 200km.sup.2 . We conclude that in terms of habitat availability, reintroduction should be feasible.
Understanding habitat selection of top predators is critical to predict their impacts on ecological communities and interactions with humans, particularly in recovering populations. We analyzed ...habitat selection in a recovering population of bobcats (Lynx rufus) in south-central Indiana using a Random Forest model. We predicted that bobcats would select forest habitat and forest edges but avoid agriculture to maximize encounters with prey species. We also predicted that bobcats would avoid developed areas and roads to minimize potential antagonistic interactions with humans. Results partially supported our predictions and were consistent with bobcats in the early stages of population expansion. Bobcats exhibited elevated use near forest edges, thresholds of avoidance near agriculture, and thresholds of selection for low and intermediate habitat heterogeneity. Bobcats exhibited peak probability of use 1-3 km from major roads, >800 m from minor roads, and <1km from developed areas, suggesting tradeoffs in reward for high-quality hunting areas and mortality risk. Our Random Forest model highlighted complex non-linear patterns and revealed that most shifts in habitat use occurred within 1 km of the edge of each habitat type. These results largely supported previous studies in the Midwest and across North America but also produced refinements of bobcat habitat use in our system, particularly at habitat boundaries. Refined models of habitat selection by carnivores enable improved prediction of the most suitable habitat for recovering populations and provides useful information for conservation.
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