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Author

Alison Cameron

Other affiliations: University of Leeds, University of York, Max Planck Society  ...read more
Bio: Alison Cameron is an academic researcher from Queen's University Belfast. The author has contributed to research in topics: Climate change & Biodiversity. The author has an hindex of 16, co-authored 28 publications receiving 8165 citations. Previous affiliations of Alison Cameron include University of Leeds & University of York.

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TL;DR: A general direction of development is suggested, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.
Abstract: To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

136 citations

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TL;DR: A novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity is developed and demonstrated, demonstrating the potential of these analyses for understanding the diversification history of Madagascar's biota.
Abstract: Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A 'one-size-fits-all' model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar's biota.

80 citations

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TL;DR: The authors sampled the endemic forest-dwelling Helictopleurini dung beetles across Madagascar during 2002–2006, suggesting that deforestation has already caused the extinction, or effective extinction, of a large number of insect species with small geographical ranges, typical for many endemic taxa in Madagascar.
Abstract: Madagascar has lost about half of its forest cover since 1953 with much regional variation, for instance most of the coastal lowland forests have been cleared. We sampled the endemic forest-dwelling Helictopleurini dung beetles across Madagascar during 2002–2006. Our samples include 29 of the 51 previously known species for which locality information is available. The most significant factor explaining apparent extinctions (species not collected by us) is forest loss within the historical range of the focal species, suggesting that deforestation has already caused the extinction, or effective extinction, of a large number of insect species with small geographical ranges, typical for many endemic taxa in Madagascar. Currently, roughly 10% of the original forest cover remains. Species–area considerations suggest that this will allow roughly half of the species to persist. Our results are consistent with this prediction.

80 citations

Journal ArticleDOI
TL;DR: Air-borne olfactory information seems to be important for migrating gulls to navigate successfully in some circumstances, as well as intact birds and gulls with the ophthalmic branch of the trigeminal nerve sectioned oriented towards their population-specific migratory corridor.
Abstract: During migratory journeys, birds may become displaced from their normal migratory route. Experimental evidence has shown that adult birds can correct for such displacements and return to their goal. However, the nature of the cues used by migratory birds to perform long distance navigation is still debated. In this experiment we subjected adult lesser black-backed gulls migrating from their Finnish/Russian breeding grounds (from >60°N) to Africa (to < 5°N) to sensory manipulation, to determine the sensory systems required for navigation. We translocated birds westward (1080 km) or eastward (885 km) to simulate natural navigational challenges. When translocated westwards and outside their migratory corridor birds with olfactory nerve section kept a clear directional preference (southerly) but were unable to compensate for the displacement, while intact birds and gulls with the ophthalmic branch of the trigeminal nerve sectioned oriented towards their population-specific migratory corridor. Thus, air-borne olfactory information seems to be important for migrating gulls to navigate successfully in some circumstances.

59 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

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TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.

13,120 citations

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TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

7,589 citations

Journal ArticleDOI
TL;DR: An overview of recent advances in species distribution models, and new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales are suggested.
Abstract: In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

5,620 citations