Conservation biology: predicting birds' responses to forest fragmentation.

Center for Conservation Biology, Department of Biological Sciences, Stanford University, 371 Serra Mall, Stanford, CA 94305, USA.
Current Biology (Impact Factor: 9.92). 11/2007; 17(19):R838-40. DOI: 10.1016/j.cub.2007.07.037
Source: PubMed

ABSTRACT Understanding species' ecological responses to habitat fragmentation is critical for biodiversity conservation, especially in tropical forests. A detailed recent study has shown that changes in the abundances of bird species following fragmentation may be dramatic and unpredictable.

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    ABSTRACT: AimThe concept of nestedness is important in determining the relative contribution to overall system diversity of different habitat patches within a fragmented system. Much of the previous work on nestedness has focused on islands within oceans (islands sensu stricto). The largest analysis of habitat island systems to date found significant nestedness to be a near universal feature, but the methods used have since been criticized as inappropriate. Thus, there is a need for an updated, critical examination of the prevalence, underlying drivers and implications of nestedness in multiple habitat island systems.LocationGlobal.Methods Here, we collate 97 datasets from published habitat island studies, comprising multiple taxa. We use the NODF metric (nestedness metric based on overlap and decreasing fill) to estimate nestedness and determine significance using the four-step proportional–proportional algorithm to simulate presences/absence matrices. We investigate the role of habitat island area in driving observed nestedness. We use linear modelling to examine the impact of dataset characteristics on the degree of nestedness and assess the conservation biogeographic implications of nestedness in relation to strategic conservation planning.ResultsSignificant nestedness occurred in only 9% of systems, whilst anti-nestedness (i.e. datasets less nested than expected by chance) occurred in 16% of systems. For the majority of datasets found to be significantly nested, we observed a relationship with fragment area, suggesting that structured extinctions may be important in determining the composition of certain habitat island communities. We found that the degree of nestedness in an archipelago is an important consideration for systematic conservation planning.Main conclusionsSignificant nestedness is considerably less common in habitat islands than previously reported. Strategic guidance for conservation planning should proceed on a case by case basis, and previous conservation recommendations based on the assumption of significant nestedness in most fragmented landscapes may need to be re-evaluated.
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    ABSTRACT: Summary 1. A recent and controversial topic in landscape ecology is whether populations of species respond to habitat fragmentation in a general fashion. Empirical research has provided mixed support, resulting in controversy about the use of general rules in landscape management. Rather than simply assessing post hoc whether individual species follow such rules, a priori testing could shed light on their accuracy and utility for predicting species response to landscape change. 2. We aim to create an a priori model that predicts the presence or absence of multiple species in habitat patches. Our goal is to balance general theory with relevant species life-history traits to obtain high prediction accuracy. To increase the utility of this work, we aim to use accessible methods that can be applied using readily available inexpensive resources. 3. The classification tree patch-occupancy model we create for birds is based on habitat suitability, minimum area requirements, dispersal potential of each species and overall landscape connectivity. 4. To test our model we apply it to the South East Queensland region, Australia, for 17 bird species with varying dispersal potential and habitat specialization. We test the accuracy of our predictions using presence–absence information for 55 vegetation patches. 5. Overall we achieve Cohen’s kappa of 0·33, or ‘fair’ agreement between the model predictions and test data sets, and generally a very high level of absence prediction accuracy. Habitat specialization appeared to influence the accuracy of the model for different species. 6. We also compare the a priori model to the statistically derived model for each species. Although this ‘optimal model’ generally differed from our original predictive model, the process revealed ways in which it could be improved for future attempts. 7. Synthesis and applications. Our study demonstrates that ecological generalizations alongside basic resources (a vegetation map and some species-specific information) can provide conservative accuracy for predicting species occupancy in remnant vegetation patches. We show that the process of testing and developing models based on general rules could provide basic tools for conservation managers to understand the impact of current or planned landscape change on wildlife populations.
    Journal of Applied Ecology 10/2009; 46(5). DOI:10.1111/j.1365-2664.2009.01694.x · 4.75 Impact Factor

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