Predicting greater sage‐grouse habitat selection at the southern periphery of their range

Mapping suitable habitat is an important process in wildlife conservation planning. Species distribution reflects habitat selection processes occurring across multiple spatio‐temporal scales. Because habitat selection may be driven by different factors at different scales, conservation planners require information at the scale of the intervention to plan effective management actions. Previous research has described habitat selection processes shaping the distribution of greater sage‐grouse (Centrocercus urophasianus; sage‐grouse) at the range‐wide scale. Finer‐scale information for applications within jurisdictional units inside the species range is lacking, yet necessary, because state wildlife agencies are the management authority for sage‐grouse in the United States. We quantified seasonal second‐order habitat selection for sage‐grouse across the state of Utah to produce spatio‐temporal predictions of their distribution at the southern periphery of the species range. We used location data obtained from sage‐grouse marked with very‐high‐frequency radio‐transmitters and lek location data collected between 1998 and 2013 to quantify species habitat selection in relation to a suite of topographic, edaphic, climatic, and anthropogenic variables using random forest algorithms. Sage‐grouse selected for greater sagebrush (Artemisia spp.) cover, higher elevations, and gentler slopes and avoided lower precipitations and higher temperatures. The strength of responses to habitat variables varied across seasons. Anthropogenic variables previously reported as affecting their range‐wide distribution (i.e., roads, powerlines, communication towers, and agricultural development) were not ranked as top predictors at our focal scale. Other than strong selection for sagebrush cover, the responses we observed differed from what has been reported at the range‐wide scale. These differences likely reflect the unique climatic, geographic, and topographic context found in the southern peripheral area of the species distribution compared to range‐wide environmental gradients. Our results highlight the importance of considering appropriateness of scale when planning conservation actions for wide‐ranging species.     

At what spatial scales does resource selection vary? A case study of koalas in a semi‐arid region

The conservation of any species requires understanding and predicting the distribution of its habitat and resource use, including the effects of scale‐dependent variation in habitat and resource quality. Consequently, testing for resource selection at the appropriate scales is critical. We investigated how the resource selection process varies across scales, using koalas in a semi‐arid landscape of eastern Australia as a case study. We asked: at what scales does tree selection by koalas vary across regions? We tested the importance of the variation of our ecological predictors at the following scales: (i) the site‐scale (a stand of trees representing an individual koala's perception of local habitat); (ii) the landscape‐scale (10 × 10 km area representing a space within which a population of koalas exists); and (iii) a combination of these scales. We used a mixed‐modelling approach to quantify variation in selection of individual trees by koalas among sites and landscapes within a 1600 km² study area. We found that tree species, and tree height, were the most important factors influencing tree selection, and that their effect did not vary across scales. In contrast, preferences for trees of different condition, which is the state of tree canopy health, did vary across landscapes, indicating spatial variation in the selection of trees with respect to tree condition at the landscape‐scale, but not at the site‐scale. We conclude that resource selection processes can depend on the quality of those resources at different scales and their heterogeneous nature across landscapes, highlighting the consequence of scale‐dependent ecological processes. Designing studies that capture the heterogeneity in habitat and resources used by species that have an extensive distribution is an important prerequisite for effective conservation planning and management.     

Use of hunters in wildlife surveys: does hunter and forest grouse habitat selection coincide?

Wildlife monitoring performed by volunteer personnel may suffer from bias with regard to their habitat use. Such errors can lead to erroneous population estimates, evidently influencing both management programmes and research that are based on the monitoring. We used a dataset on hunters’ habitat use in forest while searching for black grouse (Tetrao tetrix) and capercaillie (Tetrao urogallus) to test whether hunters’ utilisation of the habitat was independent of that of grouse or if it corresponded to the grouse habitat preference. Twenty volunteer hunters with dogs registered their tracks and all observations of capercaillie and black grouse in Østfold County, Norway, during August 2003 and 2004. We performed an ecological niche factor analysis (ENFA) and a K-select analysis with respect to hunters’ selection for habitat, described with ecogeographical variables related to forest stand characteristics, as well as the habitat preference of the observed grouse, conditional on the habitat utilisation of the hunters. Individual ENFA on the hunter's tracks revealed large variation in the habitat preferences of the hunters. The K-select indicated few overall patterns in the habitat characteristics of grouse observations, conditional on the hunters selected habitat. Accordingly, the results indicate that hunters’ observation of grouse prior to the hunt may give indicators of changes in grouse density unbiased by habitat preference due to the large between-hunter variation in habitat preference, given that a sufficient number of hunters is used. This suggests that such monitoring programmes can provide information about fluctuations in grouse population sizes valuable for both the management and research of forest grouse species.     

The importance of alder to hazel grouse in Fennoscandian boreal forest: evidence from four levels of scale

Buds and staminate catkins of alder (Alnus spp) form an important winter food for hazel grouse Bonasa bonasia in the Fennoscandian boreal forest Alder was found to be highly preferred over other deciduous trees, particularly alders ≥ 10 m tall and ≤15 m from spruce forest Winter territories were probably feeding territories, as size was correlated negatively with alder density and almost significantly correlated negatively with competitor density All winter territories were found to contain ample winter food resources for hazel grouse However, the distribution of territories was associated significantly with the distribution of alders at two levels of scale, the territory level and the landscape level Moreover, relationships between the abundance of alders and hazel grouse were found at two additional levels of scale the local patch level and the biogeographic region level This agreement of the results from four levels of scale strongly suggested that the abundance and distribution of alder was a major factor limiting hazel grouse winter territories within dense Norway spruce Picea abies forests in the boreal zone of Fennoscandia Alder was relatively uncommon and exhibited a clumped dispersion pattern at the local and landscape scales, being associated with wet and rich soils The close relationship to alder implies that hazel grouse winter habitats, even in natural forests, also should be distributed patchily Hazel grouse may select the catkins and buds of alder because it is a very nutntous food source, and small species, such as the hazel grouse, require more nutritious food than larger species     

Small-scale habitat use of black grouse (Tetrao tetrix L.) and rock ptarmigan (Lagopus muta helvetica Thienemann) in the Austrian Alps

We investigated the small-scale habitat use of two grouse species, black grouse (Tetrao tetrix L.) and rock ptarmigan (Lagopus muta helvetica Thienemann) in a study area in the Austrian Central Alps in summer. To build habitat suitability models, we applied multiple logistic regression using presence–absence data from fieldwork as the response variable and a set of habitat characteristics as explanatory variables, respectively. To gain a better understanding of the mechanisms that drive habitat selection, we tested for two-way interaction terms before excluding any variables from the initial variable set. Four explanatory variables significantly contributed to the black grouse model: dwarf shrub cover, dwarf shrub height, patchiness and ant hills. The final model for rock ptarmigan contained three explanatory variables: dwarf shrub cover, rock cover and dwarf shrub height. Most notably, the interaction terms dwarf shrub cover × patchiness in the black grouse model and dwarf shrub cover × dwarf shrub height, rock cover × dwarf shrub height in the rock ptarmigan model point out trade-off mechanisms between food, cover and overview providing features. Thus, our models do not only identify the parameters that mainly drive habitat selection, but also deepen our understanding about the causal relationships between these factors. Therefore, the information gained in this study allows for a deduction of appropriate habitat management strategies and supports conservation efforts of local stakeholders.     

Habitat preferences of sympatric sandgrouse during the breeding season in Spain: a multi-scale approach

Predictive species’ distribution models may answer ecological questions about habitat selection, co-occurrence of species and competition between them. We studied the habitat preferences and segregation of two sympatric species of declining sandgrouse, the black-bellied sandgrouse (Pterocles orientalis) and the pin-tailed sandgrouse (Pterocles alchata), during the breeding season. We developed predictive models that related sandgrouse presence to environmental variables at three different spatial levels: large geographical, landscape and microhabitat scales. At the large geographical scale, differences between sandgrouse distributions, in the Iberian Peninsula, seem to be explained mainly in terms of bioclimatology: pin-tailed sandgrouse appear to be a more thermophilous species and occupy warmer sites usually located in flatter areas. At the landscape spatial level, in those areas that exhibit environmental conditions allowing for both species’ co-existence at a large geographical scale, black-bellied sandgrouse appear to be more tolerant to environmental variation than pin-tailed sandgrouse. At the microhabitat level, however, differences between species could be related to different flocking behaviour as a consequence of different sensitivities to vegetation structure and predators. Thus, the observed spatial distribution patterns are the result of different ecological factors that operate at different spatial levels. Conservation guidelines for these species should therefore consider their habitat preferences at large geographical, landscape and microhabitat scales.     

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

Spatially explicit models of seasonal habitat for greater sage‐grouse at broad spatial scales: Informing areas for management in Nevada and northeastern California

Defining boundaries of species' habitat across broad spatial scales is often necessary for management decisions, and yet challenging for species that demonstrate differential variation in seasonal habitat use. Spatially explicit indices that incorporate temporal shifts in selection can help overcome such challenges, especially for species of high conservation concern. Greater sage‐grouse Centrocercus urophasianus (hereafter, sage‐grouse), a sagebrush obligate species inhabiting the American West, represents an important case study because sage‐grouse exhibit seasonal habitat patterns, populations are declining in most portions of their range and are central to contemporary national land use policies. Here, we modeled spatiotemporal selection patterns for telemetered sage‐grouse across multiple study sites (1,084 sage‐grouse; 30,690 locations) in the Great Basin. We developed broad‐scale spatially explicit habitat indices that elucidated space use patterns (spring, summer/fall, and winter) and accounted for regional climatic variation using previously published hydrographic boundaries. We then evaluated differences in selection/avoidance of each habitat characteristic between seasons and hydrographic regions. Most notably, sage‐grouse consistently selected areas dominated by sagebrush with few or no conifers but varied in type of sagebrush selected by season and region. Spatiotemporal variation was most apparent based on availability of water resources and herbaceous cover, where sage‐grouse strongly selected upland natural springs in xeric regions but selected larger wet meadows in mesic regions. Additionally, during the breeding period in spring, herbaceous cover was selected strongly in the mesic regions. Lastly, we expanded upon an existing joint–index framework by combining seasonal habitat indices with a probabilistic index of sage‐grouse abundance and space use to produce habitat maps useful for sage‐grouse management. These products can serve as conservation planning tools that help predict expected benefits of restoration activities, while highlighting areas most critical to sustaining sage‐grouse populations. Our joint–index framework can be applied to other species that exhibit seasonal shifts in habitat requirements to help better guide conservation actions.     

Habitat selection and movement ecology of eastern Hermann’s tortoises in a rural Romanian landscape

Understanding wildlife movements and habitat selection are critical to drafting conservation and management plans. We studied a population of eastern Hermann’s tortoise (Testudo hermanni boettgeri) in a traditionally managed rural landscape in Romania, near the northern edge of the species geographic distribution. We used telemetry to radio-track 24 individuals between 2005 and 2008 and performed a Euclidian distance-based habitat selection analysis to investigate habitats preferred by tortoises at both landscapes (second-order order selection) and individual (third-order selection) home range scales. The home range size for tortoises in our study area was 3.79?±?0.62 ha and did not differ by gender or season (pre- and post-nesting seasons). Their movement ecology was characterized by short-distance movements (daily mean?=?31.18?±?1.59 m), apparently unaffected by habitat type. In contrast to other studies, movements of males and females were of similar magnitude. At the landscape (population home range) scale, grasslands and shrubs were preferred, but tortoises also showed affinity to forest edges. At the individual home range scale, tortoises selected grassland and shrub habitats, avoided forests, and used forest edges randomly. Creeks were avoided at both spatial scales. Our results suggest that tortoise home ranges contain well-defined associations of habitats despite a higher selection for grasslands. As such, avoiding land conversion to other uses and maintaining habitat heterogeneity through traditional practices (e.g., manual mowing of grasslands, livestock grazing) are critical for the persistence of tortoise populations.     

Broad-scale habitat use by red-legged partridge <Emphasis Type="Italic">(Alectoris rufa</Emphasis>) in a low-density area in northwestern Spain

We developed broad-scale habitat selection models for the distribution of red-legged partridge Alectoris rufa in a low-density area in northwestern Spain, the Baixa-Limia site of community importance (SCI). The fieldwork consisted of ground surveys in 1 × 1 km squares. For habitat selection analysis, we used a 2 × 2 km grid integrating the information obtained in the 1 × 1 km squares. As predictors we used environmental variables measured on digital 1:50,000 scale cartography using a geographical information system (GIS). The red-legged partridge was scarce in the study area. The logistic regression analysis carried out on data from the squares with probable and confirmed breeding included the area of scrubland and pastureland with a positive sign. Using the breeding index category (BIC) three variables produced a slightly positive response: area of scrubland and pastureland, length of border between scrublands and forests, and length of border between forests and dams. The difficulty for modelling the habitat selection of this species could be due to human activities (hunting, habitat loss, restocking of hunt species), and may have modified their habitat preferences. Furthermore, the occupation of suboptimal habitats would distort the real habitat preferences.     

Extrapolation of random forest models shows scale adaptation in egret colony site selection against landscape complexity

Availability of certain habitats or landscape configurations can cause differential habitat selection in animal species. Landscape complexity can affect foraging scales, home ranges and movement, but its effect on habitat selection is not well documented. We aimed to examine differences in colony site selection of herons and egrets in different regions. We studied whether landscape complexities could affect their scale of selection and habitat preferences. We used colony distribution data and land-use maps for two neighboring regions, Ibaraki and Chiba prefectures in Japan, to create random forest models for analyzing habitat preferences and important scales of selection. We did cross-validation of the models, adjusted for its respective region's land-use maps with changing scales. The scales that best explained colony distribution were 1-, 4-, 10- and 15-km in the Ibaraki region, and 1- and 10-km in the Chiba region. Evergreen forest was the most important variable for Ibaraki at 4-km and for the Chiba at 1-km. The importance of other variables differed for other models. Cross-validation showed that herons and egrets had the same habitat preferences at a 4-km scale in Ibaraki and at a 1-km scale in Chiba. The scale of selection was reduced in Chiba, where the main foraging resources for herons and egrets was more complex. Differences in landscape complexities did not affect habitat preferences but resulted in differences in the scale of selection. Habitat selection models created at the landscape level can be useful to study behavioral aspects difficult to describe with direct observation in detail.     

On the Relationship Between Clonal Traits and Small-Scale Spatial Patterns of Three Dominant Grasses and its Consequences on Community Diversity

In a secondary successional community, we focused on the role of local dispersion mediated by clonal growth in the density and spatial patterning of tillers of three dominant grass species (Elymus repens, Brachypodium pinnatum and Calamagrostis epigejos) on the plant neighbourhood scale. We also asked whether the spatial pattern/density of their tillers were linked to the local diversity structure. In ten 75 cm?×?75 cm quadrats for each of the three species, we quantified i) the clonal morphology patterns from measuring spacer length, branching rate and the number of clumping tillers per module, ii) the spatial patterns and density of tillers in grids at four different resolutions (cell sizes varied between 1 cm?×?1 cm; 2.5 cm?×?2.5 cm; 5 cm?×?5 cm and 7.5 cm?×?7.5 cm), and iii) local species richness and local dominance based on botanical relevés. Then, we explored the relationships between iv) the clonal architecture pattern and the density/spatial pattern of tillers and v) the density/spatial pattern of tillers and local diversity variables, through regression analyses. Aggregation intensity on the smallest scales and tiller density were negatively linked to spacer length and positively linked to branching rate and number of clumping tillers. Species richness and dominance in quadrats were negatively and positively linked to tiller density, respectively. Dominance was positively linked to aggregation intensity on a 1-cm scale. This study emphasized and quantified the importance of clonal growth in the intensity and quality of grass tiller patterning in space on the plant neighbourhood scale. Our approach allowed the accurate positioning of species, or even clones on the phalanx-guerrilla continuum. This should help us to understand how dominant grass species affect the dynamics of stand communities.     

Forest and Landscape Structure as Predictors of Capercaillie Occurrence

ABSTRACT Capercaillie (Tetrao urogallus) is a large, endangered forest grouse species with narrow habitat preferences and large spatial requirements that make it susceptible to habitat changes at different spatial scales. Our aim was to evaluate the relative power of variables relating to forest versus landscape structure in predicting capercaillie occurrence at different spatial scales. We investigated capercaillie-habitat relationships at the scales of forest stand and forest-stand mosaic in 2 Swiss regions. We assessed forest structure from aerial photographs in 52 study plots each 5 km². We classified plots into one of 3 categories denoting the observed local population trend (stable, declining, extinct), and we compared forest structure between categories. At the stand scale, we used presence-absence data for grid cells within the plots to build predictive habitat models based on logistic regression. At this scale, habitat models that included only variables relating to forest structure explained the occurrence of capercaillie only in part, whereas variables selected by the models differed between regions. Including variables relating to landscape features improved the models significantly. At the scale of stand mosaic, variables describing forest structure (e.g., mean canopy cover, proportion of open forest, and proportion of multistoried forest) differed between plot categories. We conclude that small-scale forest structure has limited power to predict capercaillie occurrence at the stand scale, but that it explains well at the scale of the stand mosaic. Including variables for landscape structure improves predictions at the forest-stand scale. Habitat models built with data from one region cannot be expected to predict the species occurrence in other regions well. Thus, multiscale approaches are necessary to better understand species-habitat relationships. Our results can help regional authorities and forest-management planners to identify areas where suitable habitat for capercaillie is not available in the required proportion and, thus, where management actions are needed to improve habitat suitability.     

Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales

Predictive models on breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus; Aves: Accipitridae) have been performed at four different spatial scales in Castellón province, East of Iberian Peninsula. The scales considered were: (1) nest site scale (1×1 km² Universal Transverse Mercator (UTM) square containing the nest); (2) near nest environment (3×3 km² UTM square); (3) home range scale (5×5 km² UTM square); and (4) landscape level scale (9×9 km² UTM square containing the above mentioned ones). Topographic, disturbance, climatic and land use factors were measured on a geographic information system (GIS) at occupied and unoccupied UTM squares. Logistic regression was performed by means of a stepwise addition procedure. We tested whether inclusion of new subset of variables improved the models by increasing the area under the receiver operator characteristic plot. At nest site scale, only topographic factors were considered as the most parsimonious predictors. Probability of species occurrence increases with slope in craggy areas at lower altitudes. At the 3×3 km² scale, climate and disturbance variables were included. At home range and landscape level scales, models included climate, disturbance, topographic and land use factors. Higher temperatures in January, template ones in July, higher rainfall in June, lower altitudes and higher slope in the sample unit increase probability of occurrence of Bonelli’s eagle at broadest scales. The species seems to prefer disperse forests, scrubland and agricultural areas. From our results, we consider that there is a hierarchical framework on habitat selection procedure. We suggest that it is necessary to analyse what key factors are affecting Bonelli’s eagle nest-site selection at every study area to take steps to ensure appropriate conservation measures. The combination of regression modelling and GIS will become a powerful tool for biodiversity and conservation studies, taking into account that application depends on sampling design and the model assumptions of the statistical methods employed. Finally, predictive models obtained could be used for the efficient monitoring of this scarce species, to predict range expansions or identify suitable locations for reintroductions, and also to design protected areas and to help on wildlife management.     

Coupling in goshawk and grouse population dynamics in Finland

Different prey species can vary in their significance to a particular predator. In the simplest case, the total available density or biomass of a guild of several prey species might be most relevant to the predator, but behavioural and ecological traits of different prey species can alter the picture. We studied the population dynamics of a predator–prey setting in Finland by fitting first-order log-linear vector autoregressive models to long-term count data from active breeding sites of the northern goshawk (Accipiter gentilis; 1986–2009), and to three of its main prey species (1983–2010): hazel grouse (Bonasa bonasia), black grouse (Tetrao tetrix) and capercaillie (T. urogallus), which belong to the same forest grouse guild and show synchronous fluctuations. Our focus was on modelling the relative significance of prey species and estimating the tightness of predator–prey coupling in order to explain the observed population dynamics, simultaneously accounting for effects of density dependence, winter severity and spatial correlation. We established nine competing candidate models, where different combinations of grouse species affect goshawk dynamics with lags of 1–3 years. Effects of goshawk on grouse were investigated using one model for each grouse species. The most parsimonious model for goshawk indicated separate density effects of hazel grouse and black grouse, and different effects with lags of 1 and 3 years. Capercaillie showed no effects on goshawk populations, while the effect of goshawk on grouse was clearly negative only in capercaillie. Winter severity had significant adverse effects on goshawk and hazel grouse populations. In combination, large-scale goshawk–grouse population dynamics are coupled, but there are no clear mutual effects for any of the individual guild members. In a broader context, our study suggests that pooling data on closely related, synchronously fluctuating prey species can result in the loss of relevant information, rather than increased model parsimony.     

The NATURA 2000 database as a tool in the analysis of habitat selection at large scales: factors affecting the occurrence of pine and stone martens in Southern Europe

Most studies on habitat selection among animals are conducted at local scales, whereas reliable determination of species requirements at larger spatial scales can be problematic. We used data available for NATURA 2000 sites to determine the habitat requirements of two relatively widespread and common species—pine marten Martes martes and stone marten Martes foina—in Southern Europe. Using presence-absence data, we applied statistical models at two spatial scales. At the local scale (within the dispersal distances of the species), sites occupied by martens were compared with unoccupied sites using buffers of different sizes, whereas at the regional scale, unoccupied sites were selected randomly. To adjust for spatial autocorrelation of data, penalised quasi-likelihood approximations were used. Both species of martens demonstrated preferences for areas with higher proportions of forest cover and steeper terrain. At the local, but not at the regional, scale, pine martens occurred at lower elevations, whilst stone martens occurred at higher elevations. We found that climatic variables (mean temperature, precipitation) had no significant effect on the presence of the martens. The results of our analyses generally confirmed findings of previous studies on habitat selection of both marten species in Southern Europe. This demonstrates the utility of data collected for NATURA 2000 sites for use in various analyses such as conservation planning and evaluating the impact of climate change on the distribution of animal species.     

The unusual suspect: Land use is a key predictor of biodiversity patterns in the Iberian Peninsula

Although land use change is a key driver of biodiversity change, related variables such as habitat area and habitat heterogeneity are seldom considered in modeling approaches at larger extents. To address this knowledge gap we tested the contribution of land use related variables to models describing richness patterns of amphibians, reptiles and passerines in the Iberian Peninsula. We analyzed the relationship between species richness and habitat heterogeneity at two spatial resolutions (i.e., 10 km × 10 km and 50 km × 50 km). Using both ordinary least square and simultaneous autoregressive models, we assessed the relative importance of land use variables, climate variables and topographic variables. We also compare the species–area relationship with a multi-habitat model, the countryside species–area relationship, to assess the role of the area of different types of habitats on species diversity across scales. The association between habitat heterogeneity and species richness varied with the taxa and spatial resolution. A positive relationship was detected for all taxa at a grain size of 10 km × 10 km, but only passerines responded at a grain size of 50 km × 50 km. Species richness patterns were well described by abiotic predictors, but habitat predictors also explained a considerable portion of the variation. Moreover, species richness patterns were better described by a multi-habitat species-area model, incorporating land use variables, than by the classic power model, which only includes area as the single explanatory variable. Our results suggest that the role of land use in shaping species richness patterns goes beyond the local scale and persists at larger spatial scales. These findings call for the need of integrating land use variables in models designed to assess species richness response to large scale environmental changes.     

Multi-scale analysis on wintering habitat selection of Reeves's Pheasant (Syrmaticus reevesii) in Dongzhai National Nature Reserve, Henan Province, China

Reeves's Pheasant (Syrmaticus reevesii), endemic to China, is an endangered species of pheasants. The wintering habitat selection by the species was investigated at three scales (10, 115 m and 250 m) in Dongzhai National Nature Reserve from 2000 to 2002. At each scale, a range of habitat variables were compared between the used and the control sites. At the smallest scale (10 m), the variables influencing wintering habitat selection were slope, tree cover, and the interaction between the cosine of slope aspect and the shrub height. At the mid-scale (115 m), the area of shrub, the area of broad-leaved forest, and the area of conifer forest were the key factors. At the largest scale (250 m), broad-leaved and conifer forest coverages and their interaction were the key factors. According to the lowest AIC and AIC_c values at the mid-scale, the characteristics at this scale were stated as the ultimate factors influencing the habitat selection of the bird. When a range of habitat variables at all scales within a multivariate regression were considerred, the most important variables were conifer forest coverage at the mid-scale, broad-leaved forest coverage, and the interaction between the conifer forest and shrub coverages at the large-scale, and the distance to beach and farmland. These results highlight the importance of multiscale analyses when habitat selection by pheasants are considerred.     

Multi-scale habitat selection affects offspring survival in a precocial species

In theory, habitat preferences should be adaptive. Accordingly, fitness is often assumed to be greater in preferred habitats; however, this assumption is rarely tested and, when it is, the results are often equivocal. Habitat preferences may not directly convey fitness advantages if animals are constrained by tradeoffs with other selective pressures like predation or food availability. We address unresolved questions about the survival consequences of habitat choices made during brood-rearing in a precocial species with exclusive maternal care (mallard Anas platyrhynchos, n = 582 radio-marked females on 27 sites over 8 years). We directly linked duckling survival with habitat selection patterns at two spatial scales using logistic regression and model selection techniques. At the landscape scale (55–80 km²), females that demonstrated stronger selection of areas with more cover type 4 wetlands and greater total cover type 3 wetland area (wetlands with large expanses of open water surrounded by either a narrow or wide peripheral band of vegetation, respectively) had lower duckling survival rates than did females that demonstrated weaker selection of these habitats. At finer scales (0.32–7.16 km²), females selected brood-rearing areas with a greater proportion of wetland habitat with no consequences for duckling survival. However, females that avoided woody perennial habitats composed of trees and shrubs fledged more ducklings. The relationship between habitat selection and survival depended on both spatial scale and habitats considered. Females did not consistently select brood-rearing habitats that conferred the greatest benefits, an unexpected finding, although one that has also been reported in other recent studies of breeding birds.