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Journal ArticleDOI

Population connectivity: recent advances and new perspectives

TL;DR: Current developments in connectivity science are reviewed, providing perspectives on recent advances in identifying, quantifying, modelling and analysing connectivity, and highlighting new applications for conservation.
Abstract: Connectivity is a vital component of metapopulation and landscape ecology, influencing fundamental processes such as population dynamics, evolution, and community responses to climate change. Here, we review ongoing developments in connectivity science, providing perspectives on recent advances in identifying, quantifying, modelling and analysing connectivity, and highlight new applications for conservation. We also address ongoing challenges for connectivity research, explore opportunities for addressing them and highlight potential linkages with other fields of research. Continued development of connectivity science will provide insights into key aspects of ecology and the evolution of species, and will also contribute significantly towards achieving more effective conservation outcomes.

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Citations
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Journal ArticleDOI
TL;DR: This review describes the main topics that have contributed most significantly to the progress of landscape genetics, such as conceptual and methodological developments in spatial and temporal patterns of gene flow, seascape genetics, and landscape genomics.
Abstract: Landscape genetics is now ten years old. It has stimulated research into the effect of landscapes on evolutionary processes. This review describes the main topics that have contributed most significantly to the progress of landscape genetics, such as conceptual and methodological developments in spatial and temporal patterns of gene flow, seascape genetics, and landscape genomics. We then suggest perspectives for the future, investigating what the field will contribute to the assessment of global change and conservation in general and to the management of tropical and urban areas in particular. To address these urgent topics, future work in landscape genetics should focus on a better integration of neutral and adaptive genetic variation and their interplay with species distribution and the environment.

570 citations

Journal ArticleDOI
TL;DR: For example, this paper showed that even simple and predictable linkages among sites caused by to-and-fro migration can make migratory species especially vulnerable to habitat loss, and substantially affect the results of conservation prioritizations.
Abstract: The distributions of many species are dynamic in space and time, and movements made by individuals range from regular and predictable migrations to erratic, resource-driven nomadism. Conserving such mobile species is challenging; the effectiveness of a conservation action taken at one site depends on the condition of other sites that may be geographically and politically distant (thousands of kilometers away or in another jurisdiction, for example). Recent work has shown that even simple and predictable linkages among sites caused by “to-and-fro” migration can make migratory species especially vulnerable to habitat loss, and substantially affect the results of conservation prioritizations. Species characterized by more erratic or nomadic movements are very difficult to protect through current conservation planning techniques, which typically view species distributions as static. However, collaborations between migration ecologists, conservation planners, and mathematical ecologists are paving the way for improvements in conservation planning for mobile species.

377 citations


Cites background from "Population connectivity: recent adv..."

  • ...Existing prioritization approaches can be adapted where connectivity is both spatially continuous (Kool et al. 2013) and geographically discrete (Beger et al....

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  • ...Existing prioritization approaches can be adapted where connectivity is both spatially continuous (Kool et al. 2013) and geographi- 2013) have led to improvements in mapping movements of mobile species and their population dynamics across the full life cycle....

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Journal ArticleDOI
TL;DR: Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry as mentioned in this paper, where large sets of virtual particles are integrated within the 3D, time-evolving velocity fields.

309 citations

Journal ArticleDOI
TL;DR: An accessible overview of the latest develop- ments in seascape genetics that merge exciting new ideas from the field of marine population connectivity with statistical and technical advances in population genetics is provided.
Abstract: Seascape genetics, a term coined in 2006, is a fast growing area of population genetics that draws on ecology, oceanography and geography to address challenges in basic understanding of mar- ine connectivity and applications to management We provide an accessible overview of the latest develop- ments in seascape genetics that merge exciting new ideas from the field of marine population connectivity with statistical and technical advances in population genetics After summarizing the historical context leading to the emergence of seascape genetics, we detail questions and methodological approaches that are evolving the discipline, highlight applications to conservation and management, and conclude with a summary of the field's transition to seascape ge- nomics From 100 seascape genetic studies, we assess trends in taxonomic and geographic coverage, sam- pling and statistical design, and dominant seascape drivers Notably, temperature, oceanography and geo - graphy show equal prevalence of influence on spatial genetic patterns, and tests of over 20 other seascape factors suggest that a variety of forces impact connec- tivity at distinct spatio-temporal scales A new level of rigor in statistical analysis is critical for disentangling multiple drivers and spurious effects Coupled with GIS data and genomic scale sequencing methods, this rigor is taking seascape genetics beyond an initial focus on identifying correlations to hypothesis-driven insights into patterns and processes of population

217 citations

Journal ArticleDOI
TL;DR: A review of the literature based on 162 publications from 2000 to 2013, in which they evaluated the current state and recent advances in the integration of landscape connectivity in the identification and planning of conservation areas is presented in this article.
Abstract: The study of landscape connectivity in conservation has increased considerably since the early part of the 21st century. While the implications of landscape connectivity are self-evident for conservation, they are also important for physical geography since a proper understanding of landscape patterns and processes allows for better landscape management practices, which are at the core of geography. This paper presents a review of the literature based on 162 publications from 2000 to 2013, in which we evaluated the current state and recent advances in the integration of landscape connectivity in the identification and planning of conservation areas. The literature review and data analysis were based on a database organized into five categories: General information, study areas, research objectives, research methods in connectivity studies, and integration of connectivity with conservation. We found a substantial increase in the number of publications relating to connectivity and conservation from 2008 to ...

210 citations


Cites background or methods from "Population connectivity: recent adv..."

  • ...Theoretical articles and critical reviews were discarded in the analysis because we did not intend to discuss theoretical developments of the discipline, since these have been widely documented in other recently published reviews (e.g. Baguette et al., 2013; Kool et al., 2013; McRae et al., 2008; Minor and Urban, 2008; Mitchell et al., 2013; Rudnick et al., 2012)....

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  • ..., 2012) and other anthropic threats such as those related to global climate change (Kool et al., 2013)....

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  • ...…because we did not intend to discuss theoretical developments of the discipline, since these have been widely documented in other recently published reviews (e.g. Baguette et al., 2013; Kool et al., 2013; McRae et al., 2008; Minor and Urban, 2008; Mitchell et al., 2013; Rudnick et al., 2012)....

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  • ...…a major criterion to address the identification and maintenance of ecological integrity of the landscape, above all as a strategy to mitigate the negative effects of fragmentation (Rudnick et al., 2012) and other anthropic threats such as those related to global climate change (Kool et al., 2013)....

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References
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Journal ArticleDOI
TL;DR: A hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (md log n) where d is the depth of the dendrogram describing the community structure.
Abstract: The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (md log n) where d is the depth of the dendrogram describing the community structure. Many real-world networks are sparse and hierarchical, with m approximately n and d approximately log n, in which case our algorithm runs in essentially linear time, O (n log(2) n). As an example of the application of this algorithm we use it to analyze a network of items for sale on the web site of a large on-line retailer, items in the network being linked if they are frequently purchased by the same buyer. The network has more than 400 000 vertices and 2 x 10(6) edges. We show that our algorithm can extract meaningful communities from this network, revealing large-scale patterns present in the purchasing habits of customers.

6,599 citations


"Population connectivity: recent adv..." refers background or methods in this paper

  • ...Network community structure can be evaluated through various clustering methods (Clauset et al. 2004; Palla et al. 2005), characterizing associations between individuals or groups....

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  • ...Network community structure can be evaluated through various clustering methods (Clauset et al. 2004; Palla et al. 2005), characterizing associations 176 Landscape Ecol (2013) 28:165–185...

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Journal ArticleDOI
09 Jun 2005-Nature
TL;DR: After defining a set of new characteristic quantities for the statistics of communities, this work applies an efficient technique for exploring overlapping communities on a large scale and finds that overlaps are significant, and the distributions introduced reveal universal features of networks.
Abstract: A network is a network — be it between words (those associated with ‘bright’ in this case) or protein structures. Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections among the units they are made of1,2,3,4. A key question is how to interpret the global organization of such networks as the coexistence of their structural subunits (communities) associated with more highly interconnected parts. Identifying these a priori unknown building blocks (such as functionally related proteins5,6, industrial sectors7 and groups of people8,9) is crucial to the understanding of the structural and functional properties of networks. The existing deterministic methods used for large networks find separated communities, whereas most of the actual networks are made of highly overlapping cohesive groups of nodes. Here we introduce an approach to analysing the main statistical features of the interwoven sets of overlapping communities that makes a step towards uncovering the modular structure of complex systems. After defining a set of new characteristic quantities for the statistics of communities, we apply an efficient technique for exploring overlapping communities on a large scale. We find that overlaps are significant, and the distributions we introduce reveal universal features of networks. Our studies of collaboration, word-association and protein interaction graphs show that the web of communities has non-trivial correlations and specific scaling properties.

5,217 citations


"Population connectivity: recent adv..." refers background or methods in this paper

  • ...Network community structure can be evaluated through various clustering methods (Clauset et al. 2004; Palla et al. 2005), characterizing associations between individuals or groups....

    [...]

  • ...Network community structure can be evaluated through various clustering methods (Clauset et al. 2004; Palla et al. 2005), characterizing associations 176 Landscape Ecol (2013) 28:165–185...

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Journal ArticleDOI
TL;DR: Species distribution models (SDMs) as mentioned in this paper are numerical tools that combine observations of species occurrence or abundance with environmental estimates, and are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time.
Abstract: Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use.” Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty.

5,076 citations


"Population connectivity: recent adv..." refers background in this paper

  • ...This has operational significance because most spatial habitat data currently exists in raster format, and high-resolution analyses are necessary to link the data with on-theground conservation applications (Elith and Leathwick 2009)....

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Journal ArticleDOI
TL;DR: This study derives likelihood ratios for paternity inference with codominant markers taking account of typing error, and defines a statistic Δ for resolving paternity, and demonstrates the method is robust to their presence under commonly encountered conditions.
Abstract: Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.

4,076 citations


"Population connectivity: recent adv..." refers background in this paper

  • ...However, the requirement that the population be comprehensively sampled (Marshall et al. 1998) makes large-scale studies difficult, or in many cases, impossible....

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Book
01 Jan 2001
TL;DR: In this article, the age-classified matrix model was used to analyze the life-cycle graph sensitivity analysis and evolutionary demography statistical inference time-varying and stochastic models.
Abstract: The age-classified matrix model stage-classified life cycles stage-classified matrix models analysis of the life-cycle graph sensitivity analysis and evolutionary demography statistical inference time-varying and stochastic models density-dependent models two-sex models.

3,491 citations


"Population connectivity: recent adv..." refers background or methods in this paper

  • ...Matrix analysis Matrix models provide another means of analysing connectivity flows (Caswell 2001), and have recently been used to project connectivity structure over time (Kool 2009), providing a link between individualbased biophysical dispersal models and population genetic structure (Foster et…...

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  • ...Matrix models provide another means of analysing connectivity flows (Caswell 2001), and have recently been used to project connectivity structure over time (Kool 2009), providing a link between individualbased biophysical dispersal models and population genetic structure (Foster et al....

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  • ...Caswell (2001) noted that matrix models can be linked to IBMs, and arise naturally from stochastic models where each individual moves through its life cycle independently....

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  • ...The sensitivity and elasticity of connectivity matrices (Caswell 2001, 2007) can be used to identify connections that exert the greatest influence on the overall system, and ordering matrices through sorting (Tsafrir et al. 2005), reduction (Bode et al. 2006) or recursive partitioning (Jacobi et…...

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