Dataset Information

Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

ABSTRACT:

Background

Urbanization is characterized by high levels of sealed land-cover, and small, geometrically complex, fragmented land-use patches. The extent and density of urbanized land-use is increasing, with implications for habitat quality, connectivity and city ecology. Little is known about densification thresholds for urban ecosystem function, and the response of mammals, nocturnal and cryptic taxa are poorly studied in this respect. Bats (Chiroptera) are sensitive to changing urban form at a species, guild and community level, so are ideal model organisms for analyses of this nature.

Methodology/principal findings

We surveyed bats around urban ponds in the West Midlands conurbation, United Kingdom (UK). Sites were stratified between five urban land classes, representing a gradient of built land-cover at the 1 km(2) scale. Models for bat presence and activity were developed using land-cover and land-use data from multiple radii around each pond. Structural connectivity of tree networks was used as an indicator of the functional connectivity between habitats. All species were sensitive to measures of urban density. Some were also sensitive to landscape composition and structural connectivity at different spatial scales. These results represent new findings for an urban area. The activity of Pipistrellus pipistrellus (Schreber 1774) exhibited a non-linear relationship with the area of built land-cover, being much reduced beyond the threshold of ?60% built surface. The presence of tree networks appears to mitigate the negative effects of urbanization for this species.

Conclusions/significance

Our results suggest that increasing urban density negatively impacts the study species. This has implications for infill development policy, built density targets and the compact city debate. Bats were also sensitive to the composition and structure of the urban form at a range of spatial scales, with implications for land-use planning and management. Protecting and establishing tree networks may improve the resilience of some bat populations to urban densification.

SUBMITTER: Hale JD

PROVIDER: S-EPMC3299780 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

Hale James D JD Fairbrass Alison J AJ Matthews Tom J TJ Sadler Jon P JP

PloS one 20120312 3

<h4>Background</h4>Urbanization is characterized by high levels of sealed land-cover, and small, geometrically complex, fragmented land-use patches. The extent and density of urbanized land-use is increasing, with implications for habitat quality, connectivity and city ecology. Little is known about densification thresholds for urban ecosystem function, and the response of mammals, nocturnal and cryptic taxa are poorly studied in this respect. Bats (Chiroptera) are sensitive to changing urban fo ...[more]

PMID: 22428015

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Project description:BackgroundAdverse muscle composition (MC) as measured by magnetic resonance imaging has previously been linked to poor function, comorbidity, and increased hospitalization. The aim of this study was to investigate if adverse MC predicts all-cause mortality using data from UK Biobank.MethodsThere were 40 178 participants scanned using a 6 min magnetic resonance imaging protocol. Images were analysed for thigh fat-tissue free muscle volume and muscle fat infiltration (MFI) using AMRA® Researcher (AMRA Medical, Linköping, Sweden). For each participant, a sex, weight, and height invariant muscle volume z-score was calculated. Participants were partitioned into four MC groups: (i) normal MC, (ii) only low muscle volume [<25th percentile for muscle volume z-score (population wide)], (iii) only high MFI [>75th percentile (population wide, sex-specific)], and (iv) adverse MC (low muscle volume z-score and high MFI). Association of MC groups with mortality was investigated using Cox proportional-hazard modelling with normal MC as referent (unadjusted and adjusted for low hand grip strength, sex, age, body mass index, previous diagnosis of disease (cancer, type 2 diabetes and coronary heart disease), lifestyle, and socioeconomic factors (smoking, alcohol consumption, physical activity, and Townsend deprivation index).ResultsMuscle composition measurements were complete for 39 804 participants [52% female, mean (SD) age 64.2 (7.6) years and body mass index 26.4 (4.4) kg/m2 ]. Three hundred twenty-eight deaths were recorded during a follow-up period of 2.9 (1.4) years after imaging. At imaging, adverse MC was detected in 10.5% of participants. The risk of death from any cause in adverse MC compared with normal MC was 3.71 (95% confidence interval 2.81-4.91, P < 0.001). Only low muscle volume and only high MFI were independently associated with all-cause mortality [1.58 (1.13-2.21), P = 0.007, and 2.02 (1.51-2.71), P < 0.001, respectively]. Adjustment of low hand grip strength [1.77 (1.28-2.44), P < 0.001] did not attenuate the associations with any of the MC groups. In the fully adjusted model, adverse MC and only high MFI remained significant (P < 0.001 and P = 0.020) while the association with only low muscle volume was attenuated to non-significance (P = 0.560). The predictive performance of adverse MC [1.96 (1.42-2.71), P < 0.001] was comparable with that of previous cancer diagnosis [1.93 (1.47-2.53), P < 0.001] and smoking [1.71 (1.02-2.84), P = 0.040]. Low hand grip strength was borderline non-significant [1.34 (0.96-1.88), P = 0.090].ConclusionsAdverse MC was a strong and independent predictor of all-cause mortality. Sarcopenia guidelines can be strengthened by including cut-offs for myosteatosis enabling detection of adverse MC.

Dataset Information

Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

Background

Methodology/principal findings

Conclusions/significance

Publications

Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

Similar Datasets

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