976 resultados para Wildlife Conservation|Ecology|Conservation


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Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.

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"Sponsors: The Wildlife Society's Working Group on Sustainable Use of Ecosystem Resources ... [et al.]."

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Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.

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Wildlife managers are often faced with the difficult task of determining the distribution of species, and their preferred habitats, at large spatial scales. This task is even more challenging when the species of concern is in low abundance and/or the terrain is largely inaccessible. Spatially explicit distribution models, derived from multivariate statistical analyses and implemented in a geographic information system (GIS), can be used to predict the distributions of species and their habitats, thus making them a useful conservation tool. We present two such models: one for a dasyurid, the Swamp Antechinus (Antechinus minimus), and the other for a ground-dwelling bird, the Rufous Bristlebird (Dasyornis broadbenti), both of which are rare species occurring in the coastal heathlands of south-western Victoria. Models were generated using generalized linear modelling (GLM) techniques with species presence or absence as the independent variable and a series of landscape variables derived from GIS layers and high-resolution imagery as the predictors. The most parsimonious model, based on the Akaike Information Criterion, for each species then was extrapolated spatially in a GIS. Probability of species presence was used as an index of habitat suitability. Because habitat fragmentation is thought to be one of the major threats to these species, an assessment of the spatial distribution of suitable habitat across the landscape is vital in prescribing management actions to prevent further habitat fragmentation.

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Mode of access: Internet.