Urbanization Impacts on Mammals across Urban-Forest Edges and a Predictive Model of Edge Effects

Abstract

With accelerating rates of urbanization worldwide, a better understanding of ecological processes at the wildland-urban interface is critical to conserve biodiversity. We explored the effects of high and low-density housing developments on forest-dwelling mammals. Based on habitat characteristics, we expected a gradual decline in species abundance across forest-urban edges and an increased decline rate in higher contrast edges. We surveyed arboreal mammals in sites of high and low housing density along 600 m transects that spanned urban areas and areas turn on adjacent native forest. We also surveyed forest controls to test whether edge effects extended beyond our edge transects. We fitted models describing richness, total abundance and individual species abundance. Low-density housing developments provided suitable habitat for most arboreal mammals. In contrast, high-density housing developments had lower species richness, total abundance and individual species abundance, but supported the highest abundances of an urban adapter (Trichosurus vulpecula). We did not find the predicted gradual decline in species abundance. Of four species analysed, three exhibited no response to the proximity of urban boundaries, but spilled over into adjacent urban habitat to differing extents. One species (Petaurus australis) had an extended negative response to urban boundaries, suggesting that urban development has impacts beyond 300 m into adjacent forest. Our empirical work demonstrates that high-density housing developments have negative effects on both community and species level responses, except for one urban adapter. We developed a new predictive model of edge effects based on our results and the literature. To predict animal responses across edges, our framework integrates for first time: (1) habitat quality/preference, (2) species response with the proximity to the adjacent habitat, and (3) spillover extent/sensitivity to adjacent habitat boundaries. This framework will allow scientists, managers and planners better understand and predict both species responses across edges and impacts of development in mosaic landscapes.

A stochastic model for landscape patterns of biodiversity

“…Prevedello et al (2013) quantified the geometric edge effect only for habitat patches embedded in a completely unsuitable matrix, and suggested that this effect should become weaker as matrix suitability increased, a prediction supported by our simulations. The outcomes of the landscape model are also in accordance with many empirical studies, which have shown that matrix suitability regulates the intensity of edge effects (Perfecto and Vandermeeer 2002; Ries et al 2004;Villaseñor et al 2014). This general agreement between model outcomes and expectations shows that the well-known influence of matrix suitability on edge effects is not necessarily mediated by changes in habitat quality near habitat edges, but potentially can result from simple geometric constraints.…”

Biodiversity in Urban environments of Ordu City and Nearby Areas: Mammals, Birds, Reptiles and Amphibians

“…According to the list, a significant amount of mammal species in Turkey consists of rodents with 43%, while 24% consists of bats, 13,5% carnivores, and 12% insectivores. Devastation of habitats and the rapid urbanization negatively effects not only bird faunas, but also mammal faunas [20,21]. In the present study, since large mammal observations rather than small mammals were made around the university campus with phototrap method, potential small mammals, and bats were not determined.…”

Closing Persistent Gaps in Knowledge About Edge Ecology

“…An expansion of this model predicts response shape based on the strength of quality differences between habitat (b). Adapted with permission from [23]. Ewers and Didham [24] suggested how traits might be associated with different aspects of fragmentation including edges (c).…”

“…One drawback of the ERM is that it only makes qualitative predictions (positive, negative, or neutral), but a recent adaptation [23] of the ERM develops specific predictions about response shape based on how strong the quality difference is between adjoining habitats (Fig. 3b).…”

“…Of the few studies that did account for habitat quality differences, the results were mixed. Since that review, additional research has continued to show that hard edges tend to elicit stronger responses than soft edges [23,36]. However, without a priori controlling for habitat quality in adjacent habitat, it is still difficult to tease out the importance of physical edge contrast with the fact that similarly structured habitats often have more similar resource availability compared to starkly different habitat structures.…”