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Despite several decades of research on the effects of fragmentation and habitat change on biodiversity, there remain strong biases in the geographical regions and taxonomic species studied. The knowledge gaps resulting from these biases are of particular concern if the forests most threatened with modification are also those for which the effects of such change are most poorly understood. To quantify the nature and magnitude of such biases, we conducted a systematic review of the published literature on forest fragmentation in the tropics for the period 1980–2012. Studies included focused on any type of response of single species, communities, or assemblages of any taxonomic group to tropical forest fragmentation and on fragmentation‐related changes to forests. Of the 853 studies we found in the SCOPUS database, 64% were conducted in the Neotropics, 13% in Asia, 10% in the Afrotropics, and 5% in Australasia. Thus, although the Afrotropics is subject to the highest rates of deforestation globally, it was the most disproportionately poorly studied biome. Significant taxonomic biases were identified. Of the taxonomic groups considered, herpetofauna was the least studied in the tropics, particularly in Africa. Research examining patterns of species distribution was by far the most common type (72%), and work focused on ecological processes (28%) was rare in all biomes, but particularly in the Afrotropics and for fauna. We suggest research efforts be directed toward less‐studied biogeographic regions, particularly where the threat of forest fragmentation continues to be high. Increased research investment in the Afrotropics will be important to build knowledge of threats and inform responses in a region where almost no efforts to restore its fragmented landscapes have yet begun and forest protection is arguably most tenuous. Sesgos Biogeográficos y Taxonómicos en la Investigación de la Fragmentación de Bosques Tropicales  相似文献   
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The Convention on Biological Diversity has catalyzed worldwide awareness of threats to biological diversity and stimulated global conservation strategies. These have led to national and international legislation and have generated debate about the most effective conservation actions. Under the EU Habitats Directive, all member states are obliged to establish a system for strict protection of species listed in Annex IV(a), which includes all bats. In England, this obligation has resulted in legislation that allows for derogation from strict protection under license, provided activities are undertaken to mitigate any potential negative effects on bat numbers. We used an evidence‐based approach to assess the cost‐effectiveness of mitigation strategies and the English bat‐derogation licensing process as a whole. We analyzed data from 389 bat derogation licenses issued in England from 2003 to 2005 relating to 1776 roosts and 15 species to determine the nature and extent of development and mitigation activities and their effects on bats. Overall the effects of licensed activities on roosts were negative. Despite the level of protection afforded to bats, the majority (68%) of roosts for which derogation licenses were issued were destroyed. There were species‐specific differences in the probability of roosts being destroyed, and impacts on roosts did not reflect a species’ conservation status. Information provided by licensees was inadequate and inconsistent. Most licensees (67%) failed to submit postdevelopment reports, and postdevelopment monitoring was conducted at only 19% of sites. Despite a minimum of £4.13 million spent on mitigation structures for bats from 2003 to 2005, it was unclear whether the licensing process meets EU obligations. On the basis of our results, we believe there is a need to overhaul the licensing process, to establish a comprehensive, standardized postdevelopment monitoring system, and to demonstrate that mitigation is commensurate with Britain's legal obligations. Mitigando el Efecto del Desarrollo sobre los Murciélagos en Inglaterra con Licencias de Derogación  相似文献   
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Bayesian Networks and Adaptive Management of Wildlife Habitat   总被引:1,自引:0,他引:1  
Abstract: Adaptive management is an iterative process of gathering new knowledge regarding a system's behavior and monitoring the ecological consequences of management actions to improve management decisions. Although the concept originated in the 1970s, it is rarely actively incorporated into ecological restoration. Bayesian networks (BNs) are emerging as efficient ecological decision‐support tools well suited to adaptive management, but examples of their application in this capacity are few. We developed a BN within an adaptive‐management framework that focuses on managing the effects of feral grazing and prescribed burning regimes on avian diversity within woodlands of subtropical eastern Australia. We constructed the BN with baseline data to predict bird abundance as a function of habitat structure, grazing pressure, and prescribed burning. Results of sensitivity analyses suggested that grazing pressure increased the abundance of aggressive honeyeaters, which in turn had a strong negative effect on small passerines. Management interventions to reduce pressure of feral grazing and prescribed burning were then conducted, after which we collected a second set of field data to test the response of small passerines to these measures. We used these data, which incorporated ecological changes that may have resulted from the management interventions, to validate and update the BN. The network predictions of small passerine abundance under the new habitat and management conditions were very accurate. The updated BN concluded the first iteration of adaptive management and will be used in planning the next round of management interventions. The unique belief‐updating feature of BNs provides land managers with the flexibility to predict outcomes and evaluate the effectiveness of management interventions.  相似文献   
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Abstract:  Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (  Phascolarctos cinereus ) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however, anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity.  相似文献   
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