Suchergebnisse

Potential conflicts between forestry production practices and wildlife habitat requirements are increasing globally with rapid socioeconomic development. Moose (Alces alces cameloides) and roe deer (Capreolus pygargus bedfordi) populations are in decline in north-eastern China, an area managed for forestry production. We obtained detailed information about these species' use of habitat by following their movement paths in snow and recording behaviours exhibited along their paths. We used fractal analysis, Mann–Whitney U-tests and linear mixed models to analyse the paths and the relationships between tortuousity, habitat, and the expressed behaviours at different spatial scales. This analysis showed a natural break in the fractal dimension of moose movement paths at a scale of ~10 m, suggesting that moose exhibited different responses to their microhabitat and behavioural requirements at scales above and below this threshold. However, we detected no differences in the responses of roe deer over a scale range of 3–20 m. Moose paths tended to pass through areas with higher basal areas of tree stems and those with deeper snow. Roe deer showed positive associations between tortuousity and the number of bedding sites and feeding sites, and a negative association between tortuousity and the total basal area of tree stems. There was a positive relationship between the numbers of bedding and defaecating sites, and a negative association between the number of bedding sites and snow depth. For moose, we found positive associations between tortuousity and the number of defaecating sites, the basal areas of both broadleaf stands and mixed conifer and broadleaf stands, and a negative association between tortuousity and the number of feeding sites. We concluded that roe deer foraged in accordance with patch-use theory, whereas moose foraged in accordance with diet-selection theory. We concluded that modifications to forestry practices to foster the populations of both species of deer will require forestry operations to be conducted on a much finer scale, and that one species can be promoted over the other by selective fine-scale habitat management.

Context Artificial intelligence algorithms are beneficial for automating the monitoring of threatened species. Devil facial tumour disease (DFTD) is an endemic disease threatening Australia's Tasmanian devil. The disease is a cancer that can be transmitted from one devil to another during social interactions. Cameras and trapping techniques have been employed to monitor the spread of the disease in the wild. The use of cameras allows for more frequent monitoring of devils than does trapping, but differentiating wounds from tumours in images is challenging, and this requires time and expertise. Aim The purpose of this work is to develop a computer vision system to assist in the monitoring of DFTD spread. Method We propose a system that involves image segmentation, feature extraction, and classification steps. U-net architecture, global average pooling layer of pre-trained Resnet-18, and support vector machine (SVM) classifiers were employed for these purposes, respectively. In total, 1250 images of 961 healthy and 289 diseased (DFTD) devils were separated into training, validation, and testing sets. Results The proposed algorithm achieved 92.4% classification accuracy for the differentiation of healthy devils from those with DFTD. Conclusion The high classification accuracy means that our method can help field workers with monitoring devils. Implications The proposed approach will allow for more frequent analysis of devils while reducing the workload of field staff. Ultimately, this automation could be expanded to other species for simultaneous monitoring at shorter intervals to facilitate broadened ecological assessments.

Context Determining and quantifying habitat selection of endangered species in peri-urban environments assists planners and managers to develop strategies and alternative conservation measures in the face of urban expansion and development. Sloane's Froglet (Crinia sloanei), listed nationally as endangered in Australia, is a little-known species distributed within peri-urban environments, where foundational ecological information and the development of adequate conservation responses has been lacking. Aims (a) To determine a core calling period for Sloane's Froglet and detection probabilities for occupancy surveys. (b) To understand and characterise the habitat that Sloane's Froglet uses at the wetland and microhabitat scale. Methods We used generalised linear modelling and the information-theoretic approach to model habitat preferences for this species at two scales: the waterbody scale, and the microhabitat scale. We quantified the habitat characteristics of waterbodies occupied by Sloane's Froglet in winter, its peak breeding period, by measuring the biophysical characteristics of 54 occupied and 40 unoccupied waterbodies. The microhabitat and relative spatial positioning of Sloane's Froglet within waterbodies was examined at 54 calling sites in an area of one m squared around individual male Sloane's Froglets and 57 randomly selected unused sites. Wetlands were surveyed multiple times to determine detection probabilities. Key results Model selection indicated that Sloane's Froglet is 450 times more likely to occupy a waterbody when an adjacent ephemeral shallow overflow is present; and are more likely to be present when there is greater cover of small stem-diameter emergent vegetation and less bare ground on the bank. The microhabitat investigation of one m squared sites showed that Sloane's Froglet's calling sites are predominantly inundated, and at significantly shallower water depths, than unused sites. Sloane's Froglet was found to always call from within the waterbody, distinguishing them from other sympatric Crinia species. Conclusions The habitat characteristics detailed provide information necessary for the management of Sloane's Froglet and its habitat. Implications Housing and industrial development is occurring rapidly in Sloane's Froglet habitat. The information provided here can be used to refine local and state government planning and better design appropriate responses. Indeed, results from this study are currently being used by agencies and environmental consultants when developing conservation plans and in the design of stormwater retention ponds in rapidly urbanising environments.