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Colin J. Yates

Bio: Colin J. Yates is an academic researcher from Department of Environment and Conservation. The author has contributed to research in topics: Population & Woodland. The author has an hindex of 40, co-authored 111 publications receiving 9595 citations. Previous affiliations of Colin J. Yates include Commonwealth Scientific and Industrial Research Organisation & Murdoch University.


Papers
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Journal ArticleDOI
TL;DR: A new statistical explanation of MaxEnt is described, showing that the model minimizes the relative entropy between two probability densities defined in covariate space, which is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts.
Abstract: MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model from a statistical perspective, making explicit links between the structure of the model, decisions required in producing a modelled distribution, and knowledge about the species and the data that might affect those decisions. To begin we discuss the characteristics of presence-only data, highlighting implications for modelling distributions. We particularly focus on the problems of sample bias and lack of information on species prevalence. The keystone of the paper is a new statistical explanation of MaxEnt which shows that the model minimizes the relative entropy between two probability densities (one estimated from the presence data and one, from the landscape) defined in covariate space. For many users, this viewpoint is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts. We then step through a detailed explanation of MaxEnt describing key components (e.g. covariates and features, and definition of the landscape extent), the mechanics of model fitting (e.g. feature selection, constraints and regularization) and outputs. Using case studies for a Banksia species native to south-west Australia and a riverine fish, we fit models and interpret them, exploring why certain choices affect the result and what this means. The fish example illustrates use of the model with vector data for linear river segments rather than raster (gridded) data. Appropriate treatments for survey bias, unprojected data, locally restricted species, and predicting to environments outside the range of the training data are demonstrated, and new capabilities discussed. Online appendices include additional details of the model and the mathematical links between previous explanations and this one, example code and data, and further information on the case studies.

4,621 citations

Journal ArticleDOI
TL;DR: In this article, a simple conceptual framework for refugia is presented, and the authors examine the factors that describe them and demonstrate how different disciplines are contributing to their understanding and the tools that they provide for identifying and quantifying refugias.
Abstract: Aim Identifying and protecting refugia is a priority for conservation under projected anthropogenic climate change, because of their demonstrated ability to facilitate the survival of biota under adverse conditions. Refugia are habitats that components of biodiversity retreat to, persist in and can potentially expand from under changing environmental conditions. However, the study and discussion of refugia has often been ad hoc and descriptive in nature. We therefore: (1) provide a habitat-based concept of refugia, and (2) evaluate methods for the identification of refugia. Location Global. Methods We present a simple conceptual framework for refugia and examine the factors that describe them. We then demonstrate how different disciplines are contributing to our understanding of refugia, and the tools that they provide for identifying and quantifying refugia. Results Current understanding of refugia is largely based on Quaternary phylogeographic studies on organisms in North America and Europe during significant temperature fluctuations. This has resulted in gaps in our understanding of refugia, particularly when attempting to apply current theory to forecast anthropogenic climate change. Refugia are environmental habitats with space and time dimensions that operate on evolutionary time-scales and have facilitated the survival of biota under changing environmental conditions for millennia. Therefore, they offer the best chances for survival under climate change for many taxa, making their identification important for conservation under anthropogenic climate change. Several methods from various disciplines provide viable options for achieving this goal. Main conclusions The framework developed for refugia allows the identification and description of refugia in any environment. Various methods provide important contributions but each is limited in scope; urging a more integrated approach to identify, define and conserve refugia. Such an approach will facilitate better understanding of refugia and their capacity to act as safe havens under projected anthropogenic climate change.

835 citations

Journal ArticleDOI
TL;DR: It is suggested that seed sourcing should concentrate less on local collection and more on capturing high quality and genetically diverse seed to maximize the adaptive potential of restoration efforts to current and future environmental change.
Abstract: Restoring degraded land to combat environmental degradation requires the collection of vast quantities of germplasm (seed). Sourcing this material raises questions related to provenance selection, seed quality and harvest sustainability. Restoration guidelines strongly recommend using local sources to maximize local adaptation and prevent outbreeding depression, but in highly modified landscapes this restricts collection to small remnants where limited, poor quality seed is available, and where harvesting impacts may be high. We review three principles guiding the sourcing of restoration germplasm: (i) the appropriateness of using ‘local’ seed, (ii) sample sizes and population characteristics required to capture sufficient genetic diversity to establish self-sustaining populations and (iii) the impact of over-harvesting source populations. We review these topics by examining current collection guidelines and the evidence supporting these, then we consider if the guidelines can be improved and the consequences of not doing so. We find that the emphasis on local seed sourcing will, in many cases, lead to poor restoration outcomes, particularly at broad geographic scales. We suggest that seed sourcing should concentrate less on local collection and more on capturing high quality and genetically diverse seed to maximize the adaptive potential of restoration efforts to current and future environmental change.

553 citations

Journal ArticleDOI
TL;DR: In this article, the impacts of livestock grazing on native plant species cover, litter cover, soil surface condition, surface soil physical and chemical properties and near ground and soil microclimate in remnant Eucalyptus salmonophloia F. Muell woodlands were investigated.
Abstract: This study investigated the impacts of livestock grazing on native plant species cover, litter cover, soil surface condition, surface soil physical and chemical properties, surface soil hydrology, and near ground and soil microclimate in remnant Eucalyptus salmonophloia F. Muell woodlands. Vegetation and soil surveys were undertaken in three woodlands with a history of regular grazing and in three woodlands with a history of little or no grazing. Livestock grazing was associated with a decline in native perennial cover and an increase in exotic annual cover, reduced litter cover, reduced soil cryptogam cover, loss of surface soil microtopography, increased erosion, changes in the concentrations of soil nutrients, degradation of surface soil structure, reduced soil water infiltration rates and changes in near ground and soil microclimate. The results suggest that livestock grazing changes woodland conditions and disrupts the resource regulatory processes that maintain the natural biological array in E. salmonophloia woodlands. Consequently the conditions and resources in many remnant woodlands may be above or below critical thresholds for many species. The implications of these findings for restoration of plant species diversity and community structure are discussed. Simply removing livestock from degraded woodlands is unlikely to result in the restoration of plant species diversity and community structure. Restoration will require strategies that capture resources, increase their retention and improve microclimate.

404 citations

Journal ArticleDOI
TL;DR: Examining fragmentation impacts on plant populations by considering the processes underlying fragmentation suggests that it is critical to focus on the key processes that are important in particular situations, rather than assuming that the same factors are likely to be important everywhere.
Abstract: Fragmentation of natural vegetation is one of the most pervasive changes in terrestrial ecosystems across the Earth. Developing a general understanding of how fragmentation affects plant and animal populations is essential to meet the pressing need for guidelines for the management of fragmented systems. Nevertheless, this general understanding has to take account of differences in ecosystem types and different biogeographic, evolutionary and ecological backgrounds against which fragmentation impacts are played out in different parts of the world. Here, we examine fragmentation impacts on plant populations by considering the processes underlying fragmentation. We suggest that it is critical to focus on the key processes that are important in particular situations, rather than assuming that the same factors are likely to be important everywhere. In other words, there are inevitable limits to generalisation because of the idiosyncratic nature of the geography, history and biota of different regions. Studies on the effects of fragmentation on plant populations have focused on a limited subset of plant types and have concentrated heavily on reproductive output rather than actual regeneration success. These studies have indicated a clear impact of fragmentation on fecundity, but there is no clear signal in terms of the actual importance of this in relation to population viability. Other factors including local habitat conditions, disturbance and competition from weeds may be just as important as the classical biogeographical impacts of fragmentation. Generalisations based on a clear assessment of key life-history processes may be valuable tools in developing management responses to ecosystem fragmentation, but this requires considerably more emphasis on factors affecting successful recruitment as well as factors affecting fecundity.

329 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

Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

Book
13 Sep 2007
TL;DR: A more systematic approach to locating and designing reserves has been evolving and this approach will need to be implemented if a large proportion of today's biodiversity is to exist in a future of increasing numbers of people and their demands on natural resources.
Abstract: The realization of conservation goals requires strategies for managing whole landscapes including areas allocated to both production and protection. Reserves alone are not adequate for nature conservation but they are the cornerstone on which regional strategies are built. Reserves have two main roles. They should sample or represent the biodiversity of each region and they should separate this biodiversity from processes that threaten its persistence. Existing reserve systems throughout the world contain a biased sample of biodiversity, usually that of remote places and other areas that are unsuitable for commercial activities. A more systematic approach to locating and designing reserves has been evolving and this approach will need to be implemented if a large proportion of today's biodiversity is to exist in a future of increasing numbers of people and their demands on natural resources.

4,916 citations

Journal ArticleDOI
TL;DR: A new statistical explanation of MaxEnt is described, showing that the model minimizes the relative entropy between two probability densities defined in covariate space, which is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts.
Abstract: MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model from a statistical perspective, making explicit links between the structure of the model, decisions required in producing a modelled distribution, and knowledge about the species and the data that might affect those decisions. To begin we discuss the characteristics of presence-only data, highlighting implications for modelling distributions. We particularly focus on the problems of sample bias and lack of information on species prevalence. The keystone of the paper is a new statistical explanation of MaxEnt which shows that the model minimizes the relative entropy between two probability densities (one estimated from the presence data and one, from the landscape) defined in covariate space. For many users, this viewpoint is likely to be a more accessible way to understand the model than previous ones that rely on machine learning concepts. We then step through a detailed explanation of MaxEnt describing key components (e.g. covariates and features, and definition of the landscape extent), the mechanics of model fitting (e.g. feature selection, constraints and regularization) and outputs. Using case studies for a Banksia species native to south-west Australia and a riverine fish, we fit models and interpret them, exploring why certain choices affect the result and what this means. The fish example illustrates use of the model with vector data for linear river segments rather than raster (gridded) data. Appropriate treatments for survey bias, unprojected data, locally restricted species, and predicting to environments outside the range of the training data are demonstrated, and new capabilities discussed. Online appendices include additional details of the model and the mathematical links between previous explanations and this one, example code and data, and further information on the case studies.

4,621 citations

Journal ArticleDOI
24 Feb 2011-Nature
TL;DR: The challenges to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.
Abstract: Evolutionary adaptation can be rapid and potentially help species counter stressful conditions or realize ecological opportunities arising from climate change. The challenges are to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits. Evolutionary processes also need to be incorporated into management programmes designed to minimize biodiversity loss under rapid climate change. These challenges can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.

2,505 citations