Home range dynamics of the yellow‐footed rock‐wallaby (Petrogale xanthopus celeris) in central‐western Queensland

Analyses of the interspecific differences in macropod home range size suggest that habitat productivity exerts a greater influence on range size than does body mass. This relationship is also apparent within the rock‐wallaby genus. Lim reported that yellow‐footed rock‐wallabies (Petrogale xanthopus xanthopus) inhabiting the semi‐arid Flinders Ranges (South Australia) had a mean home range of 170 ha. While consistent with the hypothesis that species inhabiting less productive habitats will require larger ranges to fulfil their energetic requirements, the ranges reported by Lim were considerably larger than those observed for heavier sympatric macropods. The aim of the current study was to document the home range dynamics of P. x. celeris in central‐western Queensland and undertake a comparison with those reported for their southern counterparts. Wallaby movements were monitored at Idalia National Park, between winter 1992 and winter 1994. Male foraging ranges (95% fixed kernel; 15.4 ha, SD = ±7.8 ha) were found to be significantly larger than those of female wallabies (11.3 ha, SD = ±4.9 ha). Because of varying distances to the wallabies' favoured foraging ground (i.e. an adjacent herb field), the direction in which the wallabies moved to forage also significantly affected range size. Mean home range size was estimated to be 23.5 ha (SD = ±15.2 ha; 95% fixed kernel) and 67.5 ha (SD = ±22.4 ha; 100% minimum convex polygon). The discrepancy between these two estimates resulted from the exclusion of locations, from the 95% kernel estimates, when the wallabies moved to a water source 1.5 km distant from the colony site. The observed foraging and home ranges approximated those that could be expected for a macropod inhabiting the semi‐arid zone (i.e. 2.4 times larger‐than‐predicted from body mass alone). Possible reasons for the disparity between the current study and that of Lim are examined.     

Common species affects the utility of non‐invasive genetic monitoring of a cryptic endangered mammal: The bridled nailtail wallaby

Non‐invasive methods of monitoring wild populations (such as genotyping faeces or hair) are now widely used and advocated. The potential advantages of such methods over traditional direct monitoring (such as live capture) are that accuracy improves because sampling of non‐trappable individuals may be possible, species in difficult and remote terrain can be surveyed more efficiently, and disturbance to animals is minimal. Few studies have assessed the effects of interactions between species on remote sampling success. We test the use of non‐invasive monitoring for the cryptic, forest‐dwelling, solitary and endangered bridled nailtail wallaby (Onychogalea fraenata) that is sympatric with the ecologically similar and more common black‐striped wallaby (Macropus dorsalis). Six types of hair traps were tested for 3668 trap days, and hairs were caught with about a 10% success rate. Camera traps showed that baited hair traps targeted both wallaby species. We microscopically identified hair as bridled nailtail wallaby or black‐striped wallaby. We compared these hairs and their genotypes (using seven microsatellite loci) with known bridled nailtail wallaby hairs and genotypes derived from animal trapping. Trapped bridled nailtail wallaby hairs had characteristics that could be mistaken for black‐stripe wallaby hairs; characteristics were not diagnostic. Genetic assignment tests consistently differentiated the known bridled nailtail wallaby samples from identified black‐striped wallaby samples, however genetic overlap between most of the microsatellite markers means that they are not suitable for species identification of single samples, with the possible exception of the microsatellite locus B151. With similar trapping effort and within the same area, live‐capture mark‐recapture techniques estimated 40–60 individuals and non‐invasive methods only detected 14 genotypes. A species‐specific genetic marker would allow more efficient targeting of bridled nailtail wallaby samples and increase capture rates.     

Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology‐guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish‐guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.     

Using multilevel models to identify drivers of landscape‐genetic structure among management areas

Landscape genetics offers a powerful approach to understanding species' dispersal patterns. However, a central obstacle is to account for ecological processes operating at multiple spatial scales, while keeping research outcomes applicable to conservation management. We address this challenge by applying a novel multilevel regression approach to model landscape drivers of genetic structure at both the resolution of individuals and at a spatial resolution relevant to management (i.e. local government management areas: LGAs) for the koala (Phascolartos cinereus) in Australia. Our approach allows for the simultaneous incorporation of drivers of landscape‐genetic relationships operating at multiple spatial resolutions. Using microsatellite data for 1106 koalas, we show that, at the individual resolution, foliage projective cover (FPC) facilitates high gene flow (i.e. low resistance) until it falls below approximately 30%. Out of six additional land‐cover variables, only highways and freeways further explained genetic distance after accounting for the effect of FPC. At the LGA resolution, there was significant variation in isolation‐by‐resistance (IBR) relationships in terms of their slopes and intercepts. This was predominantly explained by the average resistance distance among LGAs, with a weaker effect of historical forest cover. Rates of recent landscape change did not further explain variation in IBR relationships among LGAs. By using a novel multilevel model, we disentangle the effect of landscape resistance on gene flow at the fine resolution (i.e. among individuals) from effects occurring at coarser resolutions (i.e. among LGAs). This has important implications for our ability to identify appropriate scale‐dependent management actions.     

Sex‐dependent habitat selection in a high‐density Little Bustard Tetrax tetrax population in southern France,and the implications for conservation

Conservation measures often rely on habitat management, so knowledge about a species’ habitat use is a prerequisite for effective conservation planning. The Little Bustard Tetrax tetrax, a medium‐sized bird native to the Palaearctic steppes and today found in extensively farmed habitats, is a threatened species. Its population experienced a 94% decline in farmland habitats in France between 1982 and 1996, and populations all over Europe have suffered equally sharp declines. Due to this steep negative trend, this species has been the subject of a number of habitat selection studies in order to develop relevant conservation measures based on its habitat requirements. In this study, we investigated the habitat selection of a range of habitat types by both sexes and at two nested spatial scales: plot scale and landscape scale. In addition, we analysed intra‐specific social interactions by incorporating conspecific density in the statistical models of habitat use. The study was conducted on a very high‐density population, perhaps the highest ever recorded for this species at around 50 Bustards per 100 ha of suitable habitat. Our methodology combined two field approaches (point counts and quadrat counts). The findings showed rather limited sexual dimorphism in terms of habitat selection at a local scale, with only vegetation height differing between sexes at a micro‐habitat scale, no selection at landscape scale, and a prevailing role of social factors at both scales. The implications for future conservation strategies in relation to population density and landscape composition are discussed.     

Toward community predictions: Multi‐scale modelling of mountain breeding birds' habitat suitability,landscape preferences,and environmental drivers

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including “Bio11” (Mean Temperature of Coldest Quarter), and “Bio 4” (Temperature Seasonality), then in the focal variables including “Forest”, “Orchard”, and “Agriculture area” as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.     

A dynamic multi‐scale occupancy model to estimate temporal dynamics and hierarchical habitat use for nomadic species

Distribution models are increasingly being used to understand how landscape and climatic changes are affecting the processes driving spatial and temporal distributions of plants and animals. However, many modeling efforts ignore the dynamic processes that drive distributional patterns at different scales, which may result in misleading inference about the factors influencing species distributions. Current occupancy models allow estimation of occupancy at different scales and, separately, estimation of immigration and emigration. However, joint estimation of local extinction, colonization, and occupancy within a multi‐scale model is currently unpublished. We extended multi‐scale models to account for the dynamic processes governing species distributions, while concurrently modeling local‐scale availability. We fit the model to data for lark buntings and chestnut‐collared longspurs in the Great Plains, USA, collected under the Integrated Monitoring in Bird Conservation Regions program. We investigate how the amount of grassland and shrubland and annual vegetation conditions affect bird occupancy dynamics and local vegetation structure affects fine‐scale occupancy. Buntings were prevalent and longspurs rare in our study area, but both species were locally prevalent when present. Buntings colonized sites with preferred habitat configurations, longspurs colonized a wider range of landscape conditions, and site persistence of both was higher at sites with greener vegetation. Turnover rates were high for both species, quantifying the nomadic behavior of the species. Our model allows researchers to jointly investigate temporal dynamics of species distributions and hierarchical habitat use. Our results indicate that grassland birds respond to different covariates at landscape and local scales suggesting different conservation goals at each scale. High turnover rates of these species highlight the need to account for the dynamics of nomadic species, and our model can help inform how to coordinate management efforts to provide appropriate habitat configurations at the landscape scale and provide habitat targets for local managers.     

Limited use of bat boxes in a rural landscape: implications for offsetting the clearing of hollow‐bearing trees

Bat boxes frequently form part of hollow‐bearing tree offsets; however, their effectiveness is poorly documented. We investigated the effectiveness of a bat box program designed to partially offset tree hollow loss from clearing for a coal mine. During the first year of monitoring, we detected bats in 5% of 1,308 box checks. Only 3 of 13 local tree cavity‐roosting bat species/species groups used boxes and occupancy was not strongly associated with modeled box and site attributes. In the second year, we tested two hypotheses that may explain the relatively low box use: (1) solar exposure of boxes was inadequate for heterothermic bats and (2) available box designs were of low suitability. Relocating boxes to increase solar exposure did not increase use, or enhance the temperature profiles of relocated boxes. Introduction of a new box design led to 11 times higher use compared with existing designs for Nyctophilus spp. (long‐eared bat). Overall, our data suggest that the bat box program was ineffective due to few bat species using boxes, infrequent box use by three species, and rarity of maternity roosting. The knowledge gap of species‐specific box designs and roosting ecology limits the effectiveness of boxes to offset cleared hollow‐bearing trees. Lack of knowledge and the widespread use of bat boxes to offset lost tree hollows highlights the need to (1) rigorously protect hollow‐bearing trees and (2) advance our understanding of species‐specific roost ecology, box design preferences and mechanical hollow creation into trees, before artificial hollows can be considered a meaningful offset measure.     

Landscape‐scale redistribution of a highly mobile threatened species,Pteropus conspicillatus (Chiroptera,Pteropodidae), in response to Tropical Cyclone Larry

Abstract Severe category 4 Tropical Cyclone Larry, which crossed north‐east Queensland on 20 March 2006, provided a unique opportunity to examine the short‐term impacts of a major disturbance event on the population of a highly mobile threatened species, Pteropus conspicillatus. As we had recorded, the species’ population distribution in colonial roosts (camps) across the region each month for almost 2 years prior to Cyclone Larry, we continued monthly surveying of P. conspicillatus camp‐sites for a year post‐cyclone. Here we report on how P. conspicillatus responded and redistributed immediately after the cyclone, and over the subsequent year. Post‐cyclone, P. conspicillatus typically roosted in smaller camps than pre‐cyclone, suggesting that these animals had largely dispersed to locate available blossoms and fruit. For 6 months after Cyclone Larry, up to 90% of the pre‐cyclone P. conspicillatus population (ca. 250 000) was unaccounted for across the region. Information provided by the general public assisted us in locating six small camps of P. conspicillatus at ‘new’ locations, but contributed little to increase our overall population estimate for the species at this time. After November 2006, the number of P. conspicillatus built up at located camp‐sites until a post‐cyclone peak of 209 000 at the end of the study in March 2007, comparable with the population estimates in March 2005 and 2006. There is no evidence that the cyclone caused significant direct mortality among P. conspicillatus, although there may yet be longer‐term and indirect effects on population size. We suggest that redistribution by P. conspicillatus makes sense ecologically in the face of major habitat disturbance and short‐ to long‐term food resource limitation, and is not unlike the response of other Australian mainland Pteropus species to seasonal changes in food availability.     

Small fish,large river: Surprisingly minimal genetic structure in a dispersal‐limited,habitat specialist fish

Genetic connectivity is expected to be lower in species with limited dispersal ability and a high degree of habitat specialization (intrinsic factors). Also, gene flow is predicted to be limited by habitat conditions such as physical barriers and geographic distance (extrinsic factors). We investigated the effects of distance, intervening pools, and rapids on gene flow in a species, the Tuxedo Darter (Etheostoma lemniscatum), a habitat specialist that is presumed to be dispersal‐limited. We predicted that the interplay between these intrinsic and extrinsic factors would limit dispersal and lead to genetic structure even at the small spatial scale of the species range (a 38.6 km river reach). The simple linear distribution of E. lemniscatum allowed for an ideal test of how these factors acted on gene flow and allowed us to test expectations (e.g., isolation‐by‐distance) of linearly distributed species. Using 20 microsatellites from 163 individuals collected from 18 habitat patches, we observed low levels of genetic structure that were related to geographic distance and rapids, though these factors were not barriers to gene flow. Pools separating habitat patches did not contribute to any observed genetic structure. Overall, E. lemniscatum maintains gene flow across its range and is comprised of a single population. Due to the linear distribution of the species, a stepping‐stone model of dispersal best explains the maintenance of gene flow across its small range. In general, our observation of higher‐than‐expected connectivity likely stems from an adaptation to disperse due to temporally unstable and patchy habitat.     

Bio‐ORACLE: a global environmental dataset for marine species distribution modelling

Aim The oceans harbour a great diversity of organisms whose distribution and ecological preferences are often poorly understood. Species distribution modelling (SDM) could improve our knowledge and inform marine ecosystem management and conservation. Although marine environmental data are available from various sources, there are currently no user‐friendly, high‐resolution global datasets designed for SDM applications. This study aims to fill this gap by assembling a comprehensive, uniform, high‐resolution and readily usable package of global environmental rasters. Location Global, marine. Methods We compiled global coverage data, e.g. satellite‐based and in situ measured data, representing various aspects of the marine environment relevant for species distributions. Rasters were assembled at a resolution of 5 arcmin (c. 9.2 km) and a uniform landmask was applied. The utility of the dataset was evaluated by maximum entropy SDM of the invasive seaweed Codium fragile ssp. fragile. Results We present Bio‐ORACLE (ocean rasters for analysis of climate and environment), a global dataset consisting of 23 geophysical, biotic and climate rasters. This user‐friendly data package for marine species distribution modelling is available for download at http://www.bio‐oracle.ugent.be . The high predictive power of the distribution model of C. fragile ssp. fragile clearly illustrates the potential of the data package for SDM of shallow‐water marine organisms. Main conclusions The availability of this global environmental data package has the potential to stimulate marine SDM. The high predictive success of the presence‐only model of a notorious invasive seaweed shows that the information contained in Bio‐ORACLE can be informative about marine distributions and permits building highly accurate species distribution models.     

Machine learning based modeling of households: A regionalized bottom‐up approach to investigate consumption‐induced environmental impacts

As major drivers of economy, households induce a large share of worldwide environmental impacts. The variability of local consumption patterns and associated environmental impacts needs to be quantified as an important starting point to devise targeted measures aimed at reducing household environmental footprints. The goal of this article is the development and appraisal of a comprehensive regionalized bottom‐up model that assesses realistic environmental profiles for individual households in a specific region. For this purpose, a physically based building energy model, the results of an agent‐based transport simulation, and a data‐driven household consumption model were interlinked within a new probability‐based classification framework and applied to the case of Switzerland. The resulting model predicts the demands in about 400 different consumption areas for each Swiss household by considering its particular circumstances and produces a realistic picture of variability in household environmental footprints. An analysis of the model results on a municipal level reveals per‐capita income, population density, buildings' age, and household structure as possible drivers of municipal carbon footprints. While higher‐emission municipalities are located in rural areas and tend to show higher shares of older buildings, lower‐emission communities have larger proportions of families and can be found in highly populated regions by trend. However, the opposing effects of various variables observed in this analysis confirm the importance of a model that is able to capture regional distinctions. The overall model constitutes a comprehensive information base supporting policymakers in understanding consumption patterns in their region and deriving environmental strategies tailored to their specific population.     

Large Mammal Distribution in a Transfrontier Landscape: Trade‐offs Between Resource Availability and Human Disturbance

Understanding factors that affect the persistence of charismatic megafauna in human‐dominated landscapes is crucial to inform conservation decision‐making and reduce human‐wildlife conflict. We assessed the effect of environmental and anthropogenic factors at different landscape and management scales in predicting the distribution of African elephant (Loxodonta africana) within the Greater Mapungubwe Transfrontier Conservation Area in Southern Africa. We combined aerial distribution counts over a 12‐yr period with 14 variables, representing food availability, landscape, and anthropogenic effects, into generalized linear models. Generalized linear models were run for the broader landscape, as well as three separate management units within the broader landscape, namely ecotourism, trophy hunting, and a combination of hunting and ecotourism. Human activities within different management units forced elephant to trade‐off between disturbance avoidance, and good food and water availability. In addition, the important predictors of elephant distribution within each of the management units differed from the predictors at the broader landscape. Overall, our results suggest that at the fine scale, elephant are constraint by factors that may be masked at the broader landscape scale. We suggest that accounting for anthropogenic disturbance is important in determining the distribution of large, wide‐ranging, mammal species in increasingly human‐dominated landscapes, and that modeling needs to be done at the spatial scales at which conservation decisions are made.     

Steller sea lion spatial‐use patterns derived from a Bayesian model of opportunistic observations

Despite acquisition of a substantial catalog of telemetry data from Steller sea lions (Eumetopias jubatus) over the past two decades, scientists still lack comprehensive regionally explicit knowledge about Steller sea lion habitat use. The Platforms of Opportunity data contain records of Steller sea lion sightings throughout the species’ entire range and have potential to fill gaps in knowledge about their spatial use; however, the data have not previously been used because effort (e.g., time spent surveying or area sampled) was not recorded when sightings were obtained. For this study a novel approach was used to overcome the lack of effort data through development of an effort index and a Bayesian negative binomial model. The model quantified Steller sea lion encounter rates and associated uncertainty within 15 × 15 km² grid cells across the species’ entire range. Year‐round, as well as breeding and nonbreeding season encounter rates were estimated. The results of this analysis identify several previously undocumented areas of high use by Steller sea lions, indicate that only 37% of Steller sea lion high‐use areas fall within designated critical habitat, and demonstrate that use of depth and distance from shore as indicators of Steller sea lion habitat is contraindicated.