A unifying framework for metapopulation dynamics

Many biologically important processes, such as genetic differentiation, the spread of disease, and population stability, are affected by the (natural or enforced) subdivision of populations into networks of smaller, partly isolated, subunits. Such "metapopulations" can have extremely complex dynamics. We present a new general model that uses only two functions to capture, at the metapopulation scale, the main behavior of metapopulations. We show how complex, structured metapopulation models can be translated into our generalized framework. The metapopulation dynamics arising from some important biological processes are illustrated: the rescue effect, the Allee effect, and what we term the "antirescue effect." The antirescue effect captures instances where high migration rates are deleterious to population persistence, a phenomenon that has been largely ignored in metapopulation conservation theory. Management regimes that ignore a significant antirescue effect will be inadequate and may actually increase extinction risk. Further, consequences of territoriality and conspecific attraction on metapopulation-level dynamics are investigated. The new, simplified framework can incorporate knowledge from epidemiology, genetics, and population biology in a phenomenological way. It opens up new possibilities to identify and analyze the factors that are important for the evolution and persistence of the many spatially subdivided species.     

A unifying gravity framework for dispersal

Theoretical Ecology - Most organisms disperse at some life-history stage, but different research traditions to study dispersal have evolved in botany, zoology, and epidemiology. In this paper, we...     

A comparison of the strength of biodiversity effects across multiple functions

In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.     

Regional management units for marine turtles: a novel framework for prioritizing conservation and research across multiple scales

Background

Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques — including site-based monitoring, genetic analyses, mark-recapture studies and telemetry — can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges.

Methodology/Principal Findings

To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally.

Conclusions/Significance

The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework — including maps and supporting metadata — will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis.     

Consensus framework for exploring microarray data using multiple clustering methods

The large variety of clustering algorithms and their variants can be daunting to researchers wishing to explore patterns within their microarray datasets. Furthermore, each clustering method has distinct biases in finding patterns within the data, and clusterings may not be reproducible across different algorithms. A consensus approach utilizing multiple algorithms can show where the various methods agree and expose robust patterns within the data. In this paper, we present a software package - Consense, written for R/Bioconductor - that utilizes such an approach to explore microarray datasets. Consense produces clustering results for each of the clustering methods and produces a report of metrics comparing the individual clusterings. A feature of Consense is identification of genes that cluster consistently with an index gene across methods. Utilizing simulated microarray data, sensitivity of the metrics to the biases of the different clustering algorithms is explored. The framework is easily extensible, allowing this tool to be used by other functional genomic data types, as well as other high-throughput OMICS data types generated from metabolomic and proteomic experiments. It also provides a flexible environment to benchmark new clustering algorithms. Consense is currently available as an installable R/Bioconductor package (http://www.ohsucancer.com/isrdev/consense/).     

A unifying probabilistic framework for analyzing residual dipolar couplings

Residual dipolar couplings provide complementary information to the nuclear Overhauser effect measurements that are traditionally used in biomolecular structure determination by NMR. In a de novo structure determination, however, lack of knowledge about the degree and orientation of molecular alignment complicates the analysis of dipolar coupling data. We present a probabilistic framework for analyzing residual dipolar couplings and demonstrate that it is possible to estimate the atomic coordinates, the complete molecular alignment tensor, and the error of the couplings simultaneously. As a by-product, we also obtain estimates of the uncertainty in the coordinates and the alignment tensor. We show that our approach encompasses existing methods for determining the alignment tensor as special cases, including least squares estimation, histogram fitting, and elimination of an explicit alignment tensor in the restraint energy.     

A unifying computational framework for motor control and social interaction

Recent empirical studies have implicated the use of the motor system during action observation, imitation and social interaction. In this paper, we explore the computational parallels between the processes that occur in motor control and in action observation, imitation, social interaction and theory of mind. In particular, we examine the extent to which motor commands acting on the body can be equated with communicative signals acting on other people and suggest that computational solutions for motor control may have been extended to the domain of social interaction.     

The multiple decrement life table: a unifying framework for cause-of-death analysis in ecology

Summary The multiple decrement life table is used widely in the human actuarial literature and provides statistical expressions for mortality in three different forms: i) the life table from all causes-of-death combined; ii) the life table disaggregated into selected cause-of-death categories; and iii) the life table with particular causes and combinations of causes eliminated. The purpose of this paper is to introduce the multiple decrement life table to the ecological literature by applying the methods to published death-by-cause information on Rhagoletis pomonella. Interrelations between the current approach and conventional tools used in basic and applied ecology are discussed including the conventional life table, Key Factor Analysis and Abbott's Correction used in toxicological bioassay.     

A unified Markov chain Monte Carlo framework for mapping multiple quantitative trait loci

In this article, a unified Markov chain Monte Carlo (MCMC) framework is proposed to identify multiple quantitative trait loci (QTL) for complex traits in experimental designs, based on a composite space representation of the problem that has fixed dimension. The proposed unified approach includes the existing Bayesian QTL mapping methods using reversible jump MCMC algorithm as special cases. We also show that a variety of Bayesian variable selection methods using Gibbs sampling can be applied to the composite model space for mapping multiple QTL. The unified framework not only results in some new algorithms, but also gives useful insight into some of the important factors governing the performance of Gibbs sampling and reversible jump for mapping multiple QTL. Finally, we develop strategies to improve the performance of MCMC algorithms.     

Indicators of biodiversity and ecosystem services: a synthesis across ecosystems and spatial scales

According to the Millennium Ecosystem Assessment, common indicators are needed to monitor the loss of biodiversity and the implications for the sustainable provision of ecosystem services. However, a variety of indicators are already being used resulting in many, mostly incompatible, monitoring systems. In order to synthesise the different indicator approaches and to detect gaps in the development of common indicator systems, we examined 531 indicators that have been reported in 617 peer‐reviewed journal articles between 1997 and 2007. Special emphasis was placed on comparing indicators of biodiversity and ecosystem services across ecosystems (forests, grass‐ and shrublands, wetlands, rivers, lakes, soils and agro‐ecosystems) and spatial scales (from patch to global scale). The application of biological indicators was found most often focused on regional and finer spatial scales with few indicators applied across ecosystem types. Abiotic indicators, such as physico‐chemical parameters and measures of area and fragmentation, are most frequently used at broader (regional to continental) scales. Despite its multiple dimensions, biodiversity is usually equated with species richness only. The functional, structural and genetic components of biodiversity are poorly addressed despite their potential value across habitats and scales. Ecosystem service indicators are mostly used to estimate regulating and supporting services but generally differ between ecosystem types as they reflect ecosystem‐specific services. Despite great effort to develop indicator systems over the past decade, there is still a considerable gap in the widespread use of indicators for many of the multiple components of biodiversity and ecosystem services, and a need to develop common monitoring schemes within and across habitats. Filling these gaps is a prerequisite for linking biodiversity dynamics with ecosystem service delivery and to achieving the goals of global and sub‐global initiatives to halt the loss of biodiversity.     

A framework for assessing the biodiversity and fishery aspects of marine reserves

1.  Resource management agencies are often charged with managing natural resources for economic and social goals, while also protecting and conserving biodiversity and ecosystem function. However, this may not always be possible. Ecosystem-based management is frequently suggested as a way to achieve multiple objectives in resource management and requires that trade-offs among conflicting objectives be identified and an effective means to utilize these trade-offs developed.
2.  We examine the relationship between area and species richness in a diverse assemblage of fishes along the US West Coast and then use parameters from this relationship as input for a model that considers trade-offs between fisheries yield and the number of species protected by different management strategies.
3.  The species–area relationship ( S  =  cA ^z ) for fishes along the US Pacific coast is well described by the relationship S  =   16·18 A ^0·226.
4.  There are nearly linear trade-offs between diversity and yield when fishing effort is low. However, the trade-offs become nonlinear as fishing effort increases and imposing MPAs increases both the conservation and fisheries value of the system when the system is overfished.
5.   Synthesis and applications . Solving conflicts between fisheries and conservation requires attention as to how conservation benefits accrue as fishing effort is reduced. However, scientists often lack quantitative information about the trade-offs inherent in human activities such as fisheries. The approach we develop here can begin to help frame the questions to be posed and evaluate the likely consequences of different management options.     

A proposal of framework to obtain an integrated biodiversity indicator for agricultural ponds incorporating the simultaneous effects of multiple pressures

One of the promising approaches to monitoring biodiversity is assessing the status of pressures driving the biodiversity state. To achieve this, we need to identify the principal pressures that cause simultaneous biodiversity loss across taxonomic groups and clarify how multiple pressures act synergistically or at least simultaneously to decrease biodiversity in the focal ecosystem. Here, we used a series of 64 ponds as a case study and we developed a framework for an integrated biodiversity indicator that took into consideration the estimated relative importance of multiple pressures. The indicator is defined as a function of the pressure(s) and is parameterized to explain a number of individual indicators of biodiversity, such as richness, abundance, and functional diversity of focal taxa. We selected aquatic macrophytes, Odonata, and benthic macroinvertebrates as the focal taxa. In addition, we focused on three types of pressure: eutrophication (represented by total phosphorus, total nitrogen, suspended solids, chlorophyll a, and density of cyanobacteria of pond water), habitat destruction (land-use type around the pond and pond bank protection), and invasive alien species (abundance of bluegill, largemouth bass, red swamp crayfish, and American bullfrog). We then evaluated the relationships among direct pressures and the individual biodiversity indicators and used a hierarchical Bayesian approach to calculate the integrated biodiversity indicator. Using this framework, we demonstrated that eutrophication had greater effects on the state of biodiversity of the agricultural ponds than did habitat destruction or the presence of invasive alien species. We also showed that the integrated indicator could well explain the behaviors of several individual biodiversity indicators, including total richness, endangered species richness, and functional diversity of focal taxa. These results demonstrate the advantages of the framework in providing a more practical method for assessing biodiversity, and quantifying the relative importance of the major threats to biodiversity to prioritize strategies in conservation planning and policy making.     

Additive partitioning of aquatic invertebrate species diversity across multiple spatial scales

1. Additive partitioning of three measures of diversity (species richness, Shannon's diversity index H and Simpson's diversity D) was used to study the relationship between local and regional diversity of benthic macroinvertebrate communities of boreal lakes (littoral habitats) and streams (riffle habitats) across three spatial scales (sampling sites, ecoregions and biogeographic regions). 2. Alpha (α) and beta (β) diversity are defined as within‐habitat and between‐habitat diversity, respectively. According to the concept of additive partitioning, diversity can be partitioned across multiple spatial scales such that the total (γ) diversity on one spatial scale becomes within‐habitat (α) diversity at the next higher scale. Hence, the total diversity at one scale is determined by the α diversity and the between‐habitat diversity (β) at the next lower scale. Consequently, one of the advantages of additive partitioning is that it is possible to study simultaneously β diversity and the regional‐local species relationship and the scale dependence of α and β components. 3. For both lakes and streams α diversity was low for sites and ecoregions, whereas β diversity was high, indicating that among‐site factors are important in describing the variability among the lakes and streams studied here. 4. Weak, albeit significant, evidence was found for regional and local species saturation patterns. Multiple stepwise regression indicated that local processes might be more important in structuring lake‐littoral and stream‐riffle species assemblages than regional processes. From these results we conclude that environmental heterogeneity may act as an important factor contributing to species coexistence, resulting in the observed saturation patterns. 5. Our study supports the use of additive partitioning for identifying specific patterns of macroinvertebrate diversity on multiple spatial scales and the underlying processes generating these patterns. This information is needed to improve understanding of the relation between patterns and processes affecting (decreasing) trends in aquatic biodiversity.     

Universal scaling of species‐abundance distributions across multiple scales

The scale‐dependent species abundance distribution (SAD) is fundamental in ecology, but few spatially explicit models of this pattern have thus far been studied. Here we show spatially explicit neutral model predictions for SADs over a wide range of spatial scales, which appear to match empirical patterns qualitatively. We find that the assumption of a log‐series SAD in the metacommunity made by spatially implicit neutral models can be justified with a spatially explicit model in the large area limit. Furthermore, our model predicts that SADs on multiple scales are characterized by a single, compound parameter that represents the ratio of the survey area to the species’ average biogeographic range (which is in turn set by the speciation rate and the dispersal distance). This intriguing prediction is in line with recent empirical evidence for a universal scaling of the species‐area curve. Hence we hypothesize that empirical SAD patterns will show a similar universal scaling for many different taxa and across multiple spatial scales.     

Changing importance of habitat structure across multiple spatial scales for three species of insects

Considerable scientific effort has gone into examining how the spatial structure of habitat influences organism distribution and abundance in both theoretical and applied contexts. An emerging conclusion from these works is that the overall amount of habitat in the landscape matters most for species persistence and that more local attributes of habitat structure such as the size and arrangement of patches is of secondary importance. In this study, we quantify how and when the effects of habitat configuration (patch size and isolation) influence the density of three species of insects (Order: Diptera; Wyeomyia smithii , Metriocnemus knabi , Fletcherimyia fletcheri ) whose larvae are found exclusively in identical habitats (the water-filled leaves of pitcher plants – Sarracenia purpurea ) in a system that is naturally patchy at multiple spatial scales. We illustrate that relationships with configuration exist regardless of the overall amount of habitat in the broader landscape, and that there are distinct changes in the relationship between insect density and habitat configuration across multiple spatial scales. In general, patch size is more important within the movement range of the individual and isolation is important at larger, aggregation scales. Thus we demonstrate that a) both the amount and configuration of habitat are important attributes of species distribution; b) responses to measures of configuration can be scaled to processes such as movement and c) that hierarchical frameworks extending across very broad scales are essential for understanding how species respond to habitat structure and their role in ecosystem function.