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Influence of landscape structure and human modifications on insect biomass and bat foraging activity in an urban landscape.

Threlfall CG, Law B, Banks PB - PLoS ONE (2012)

Bottom Line: We found that insect biomass was at least an order of magnitude greater within suburban landscapes in bushland and backyard elements located on the most fertile shale influenced geologies (both p<0.001) compared to nutrient poor sandstone landscapes.These were ambient temperature (positive), housing density (negative) and the percent of fertile shale geologies (positive) in the landscape; however variation in insect biomass did not directly explain bat foraging activity.We suggest that prey may be unavailable to bats in highly urbanized areas if these areas are avoided by many species, suggesting that reduced feeding activity may reflect under-use of urban habitats by bats.

View Article: PubMed Central - PubMed

Affiliation: Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia. caragh.threlfall@unimelb.edu.au

ABSTRACT
Urban landscapes are often located in biologically diverse, productive regions. As such, urbanization may have dramatic consequences for this diversity, largely due to changes in the structure and function of urban communities. We examined the influence of landscape productivity (indexed by geology), housing density and vegetation clearing on the spatial distribution of nocturnal insect biomass and the foraging activity of insectivorous bats in the urban landscape of Sydney, Australia. Nocturnal insect biomass (g) and bat foraging activity were sampled from 113 sites representing backyard, open space, bushland and riparian landscape elements, across urban, suburban and vegetated landscapes within 60 km of Sydney's Central Business District. We found that insect biomass was at least an order of magnitude greater within suburban landscapes in bushland and backyard elements located on the most fertile shale influenced geologies (both p<0.001) compared to nutrient poor sandstone landscapes. Similarly, the feeding activity of bats was greatest in bushland, and riparian elements within suburbs on fertile geologies (p = 0.039). Regression tree analysis indicated that the same three variables explained the major proportion of the variation in insect biomass and bat foraging activity. These were ambient temperature (positive), housing density (negative) and the percent of fertile shale geologies (positive) in the landscape; however variation in insect biomass did not directly explain bat foraging activity. We suggest that prey may be unavailable to bats in highly urbanized areas if these areas are avoided by many species, suggesting that reduced feeding activity may reflect under-use of urban habitats by bats. Restoration activities to improve ecological function and maintain the activity of a diversity of bat species should focus on maintaining and restoring bushland and riparian habitat, particularly in areas with fertile geology as these were key bat foraging habitats.

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Regression tree for total insect biomass.Each split corresponds to a rule which is displayed with the variable causing the split (Condition<x, untransformed data). To investigate each condition proceed to the left or right branch of the node, following the less than or greater than signs. Values at the base of each node (vertical lines) represent mean insect biomass (log x+0.01) for that condition. Av_temp = average nightly temperature (°C) for each site during the sampling period; Shale_PC = the percentage of shale geology in each landscape sampled; Housing_Density = number of houses/ha measured within 500 m, 3 km and 5 km radii of each site.
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pone-0038800-g004: Regression tree for total insect biomass.Each split corresponds to a rule which is displayed with the variable causing the split (Condition<x, untransformed data). To investigate each condition proceed to the left or right branch of the node, following the less than or greater than signs. Values at the base of each node (vertical lines) represent mean insect biomass (log x+0.01) for that condition. Av_temp = average nightly temperature (°C) for each site during the sampling period; Shale_PC = the percentage of shale geology in each landscape sampled; Housing_Density = number of houses/ha measured within 500 m, 3 km and 5 km radii of each site.

Mentions: Using regression tree analysis, we examined whether measured environmental variables (see Methods: Environmental variables) explained variation in insect biomass and bat foraging activity. Using this technique, three variables were identified as good predictors of insect biomass (Fig. 4). These three variables were also the most important predictors in regression trees for moth and beetle biomass (graphs not shown). The condition that led to the highest total insect biomass occurred in sites where the average nightly temperature was 18.5°C or above, with a housing density of 7 houses/ha or less, within a 5 km radius (Fig. 4). The condition that led to the lowest biomass occurred in sites where the average nightly temperature was below 18.5°C and less than 72% shale in the landscape occurred. All other variables were omitted from the final model. The residual mean deviance of the final insect biomass model was 0.51, with an R2 of 0.71.


Influence of landscape structure and human modifications on insect biomass and bat foraging activity in an urban landscape.

Threlfall CG, Law B, Banks PB - PLoS ONE (2012)

Regression tree for total insect biomass.Each split corresponds to a rule which is displayed with the variable causing the split (Condition<x, untransformed data). To investigate each condition proceed to the left or right branch of the node, following the less than or greater than signs. Values at the base of each node (vertical lines) represent mean insect biomass (log x+0.01) for that condition. Av_temp = average nightly temperature (°C) for each site during the sampling period; Shale_PC = the percentage of shale geology in each landscape sampled; Housing_Density = number of houses/ha measured within 500 m, 3 km and 5 km radii of each site.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369849&req=5

pone-0038800-g004: Regression tree for total insect biomass.Each split corresponds to a rule which is displayed with the variable causing the split (Condition<x, untransformed data). To investigate each condition proceed to the left or right branch of the node, following the less than or greater than signs. Values at the base of each node (vertical lines) represent mean insect biomass (log x+0.01) for that condition. Av_temp = average nightly temperature (°C) for each site during the sampling period; Shale_PC = the percentage of shale geology in each landscape sampled; Housing_Density = number of houses/ha measured within 500 m, 3 km and 5 km radii of each site.
Mentions: Using regression tree analysis, we examined whether measured environmental variables (see Methods: Environmental variables) explained variation in insect biomass and bat foraging activity. Using this technique, three variables were identified as good predictors of insect biomass (Fig. 4). These three variables were also the most important predictors in regression trees for moth and beetle biomass (graphs not shown). The condition that led to the highest total insect biomass occurred in sites where the average nightly temperature was 18.5°C or above, with a housing density of 7 houses/ha or less, within a 5 km radius (Fig. 4). The condition that led to the lowest biomass occurred in sites where the average nightly temperature was below 18.5°C and less than 72% shale in the landscape occurred. All other variables were omitted from the final model. The residual mean deviance of the final insect biomass model was 0.51, with an R2 of 0.71.

Bottom Line: We found that insect biomass was at least an order of magnitude greater within suburban landscapes in bushland and backyard elements located on the most fertile shale influenced geologies (both p<0.001) compared to nutrient poor sandstone landscapes.These were ambient temperature (positive), housing density (negative) and the percent of fertile shale geologies (positive) in the landscape; however variation in insect biomass did not directly explain bat foraging activity.We suggest that prey may be unavailable to bats in highly urbanized areas if these areas are avoided by many species, suggesting that reduced feeding activity may reflect under-use of urban habitats by bats.

View Article: PubMed Central - PubMed

Affiliation: Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia. caragh.threlfall@unimelb.edu.au

ABSTRACT
Urban landscapes are often located in biologically diverse, productive regions. As such, urbanization may have dramatic consequences for this diversity, largely due to changes in the structure and function of urban communities. We examined the influence of landscape productivity (indexed by geology), housing density and vegetation clearing on the spatial distribution of nocturnal insect biomass and the foraging activity of insectivorous bats in the urban landscape of Sydney, Australia. Nocturnal insect biomass (g) and bat foraging activity were sampled from 113 sites representing backyard, open space, bushland and riparian landscape elements, across urban, suburban and vegetated landscapes within 60 km of Sydney's Central Business District. We found that insect biomass was at least an order of magnitude greater within suburban landscapes in bushland and backyard elements located on the most fertile shale influenced geologies (both p<0.001) compared to nutrient poor sandstone landscapes. Similarly, the feeding activity of bats was greatest in bushland, and riparian elements within suburbs on fertile geologies (p = 0.039). Regression tree analysis indicated that the same three variables explained the major proportion of the variation in insect biomass and bat foraging activity. These were ambient temperature (positive), housing density (negative) and the percent of fertile shale geologies (positive) in the landscape; however variation in insect biomass did not directly explain bat foraging activity. We suggest that prey may be unavailable to bats in highly urbanized areas if these areas are avoided by many species, suggesting that reduced feeding activity may reflect under-use of urban habitats by bats. Restoration activities to improve ecological function and maintain the activity of a diversity of bat species should focus on maintaining and restoring bushland and riparian habitat, particularly in areas with fertile geology as these were key bat foraging habitats.

Show MeSH
Related in: MedlinePlus