Experimental-neuromodeling framework for understanding auditory object processing: integrating data across multiple scales.

In this article, we review a combined experimental-neuromodeling framework for understanding brain function with a specific application to auditory object processing. Within this framework, a model is constructed using the best available experimental data and is used to make predictions. The predictions are verified by conducting specific or directed experiments and the resulting data are matched with the simulated data. The model is refined or tested on new data and generates new predictions. The predictions in turn lead to better-focused experiments. The auditory object processing model was constructed using available neurophysiological and neuroanatomical data from mammalian studies of auditory object processing in the cortex. Auditory objects are brief sounds such as syllables, words, melodic fragments, etc. The model can simultaneously simulate neuronal activity at a columnar level and neuroimaging activity at a systems level while processing frequency-modulated tones in a delayed-match-to-sample task. The simulated neuroimaging activity was quantitatively matched with neuroimaging data obtained from experiments; both the simulations and the experiments used similar tasks, sounds, and other experimental parameters. We then used the model to investigate the neural bases of the auditory continuity illusion, a type of perceptual grouping phenomenon, without changing any of its parameters. Perceptual grouping enables the auditory system to integrate brief, disparate sounds into cohesive perceptual units. The neural mechanisms underlying auditory continuity illusion have not been studied extensively with conventional neuroimaging or electrophysiological techniques. Our modeling results agree with behavioral studies in humans and an electrophysiological study in cats. The results predict a particular set of bottom-up cortical processing mechanisms that implement perceptual grouping, and also attest to the robustness of our model.     

Measures of giant panda habitat selection across multiple spatial scales for species conservation

Examining ecological processes across spatial scales is crucial as animals select and use resources at different scales. We carried out field surveys in September 2005, March–September 2006, and April 2007, and used ecological niche factor analysis to determine habitat preferences for the giant panda (Ailuropoda melanoleuca) across 4 spatial scales: daily movement, core range, home range, and seasonal elevational migration. We found that giant pandas prefer conifer forest and mixed forest at higher than average elevation (2,157 m) of study area in the 4 scale models. However, we also observed significant scale differences in habitat selection. The strength of habitat preference increased with scale for the 2 disturbed forests (sparse forest and fragmented forest), and decreased with scale for 0–30° gentle slope and south- and north-facing aspect. Furthermore, habitat suitability patterns were scale-dependent. These findings highlight the need to determine species–environment associations across multiple scales for habitat management and species conservation. © 2012 The Wildlife Society.     

Informing species conservation at multiple scales using data collected for marine mammal stock assessments

Background

Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments.

Methodology and Results

We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km²). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia''s National Representative System of Marine Protected Areas.

Conclusion/Significance

In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales.     

A unifying quantitative framework for exploring the multiple facets of microbial biodiversity across diverse scales

Recent developments of molecular tools have revolutionized our knowledge of microbial biodiversity by allowing detailed exploration of its different facets and generating unprecedented amount of data. One key issue with such large datasets is the development of diversity measures that cope with different data outputs and allow comparison of biodiversity across different scales. Diversity has indeed three components: local (α), regional (γ) and the overall difference between local communities (β). Current measures of microbial diversity, derived from several approaches, provide complementary but different views. They only capture the β component of diversity, compare communities in a pairwise way, consider all species as equivalent or lack a mathematically explicit relationship among the α, β and γ components. We propose a unified quantitative framework based on the Rao quadratic entropy, to obtain an additive decomposition of diversity (γ = α + β), so the three components can be compared, and that integrate the relationship (phylogenetic or functional) among Microbial Diversity Units that compose a microbial community. We show how this framework is adapted to all types of molecular data, and we highlight crucial issues in microbial ecology that would benefit from this framework and propose ready‐to‐use R‐functions to easily set up our approach.     

Engage the hodgepodge: management factors are essential when prioritizing areas for restoration and conservation action

Restoration and conservation initiatives, such as the eradication of invasive alien plants, should be guided by scientific evidence. Typically, ecological data alone is used to inform the decision‐making of these initiatives. Recent advances in the mapping of conservation opportunity include a diverse range of scientifically‐identified factors that determine the feasibility and likely effectiveness of conservation initiatives, and include, for example, data on the willingness and capacity of land managers to be effectively involved. Social research techniques such as interview surveys, phenomenology, and social network analysis are important approaches for securing useful human and social data. These approaches are yet to be widely adopted in restoration initiatives, but could be usefully applied to improve the effective implementation of these initiatives. Restoration and conservation planners will deliver spatial prioritisations which provide more effective and cost‐efficient decision‐making if they include not simply ecological data, but also data on economic, human, management, social and vulnerability factors that determine implementation effectiveness.     

Phylogeography of a migratory songbird across its Canadian breeding range: Implications for conservation units

The objectives of this study were to describe and evaluate potential drivers of genetic structure in Canadian breeding populations of the Ovenbird, Seiurus aurocapilla. We performed genetic analyses on feather samples of individuals from six study sites using nuclear microsatellites. We also assessed species identity and population genetic structure of quill mites (Acariformes, Syringophilidae). For male Ovenbirds breeding in three study sites, we collected light‐level geolocator data to document migratory paths and identify the wintering grounds. We also generated paleohindcast projections from bioclimatic models of Ovenbird distribution to identify potential refugia during the last glacial maximum (LGM, 21,000 years before present) as a factor explaining population genetic structure. Birds breeding in the Cypress Hills (Alberta/Saskatchewan) may be considered a distinct genetic unit, but there was no evidence for genetic differentiation among any other populations. We found relatively strong migratory connectivity in both western and eastern populations, but some evidence of mixing among populations on the wintering grounds. There was also little genetic variation among syringophilid mites from the different Ovenbird populations. These results are consistent with paleohindcast distribution predictions derived from two different global climate models indicating a continuous single LGM refugium, with the possibility of two refugia. Our results suggest that Ovenbird populations breeding in boreal and hemiboreal regions are panmictic, whereas the population breeding in Cypress Hills should be considered a distinct management unit.     

Subject-specific tribo-contact conditions in total knee replacements: a simulation framework across scales

Fundamental knowledge about in vivo kinematics and contact conditions at the articulating interfaces of total knee replacements are essential for predicting and optimizing their behavior and durability. However, the prevailing motions and contact stresses in total knee replacements cannot be precisely determined using conventional in vivo measurement methods. In silico modeling, in turn, allows for a prediction of the loads, velocities, deformations, stress, and lubrication conditions across the scales during gait. Within the scope of this paper, we therefore combine musculoskeletal modeling with tribo-contact modeling. In the first step, we compute contact forces and sliding velocities by means of inverse dynamics approach and force-dependent kinematic solver based upon experimental gait data, revealing contact forces during healthy/physiological gait of young subjects. In a second step, the derived data are employed as input data for an elastohydrodynamic model based upon the finite element method full-system approach taking into account elastic deformation, the synovial fluid’s hydrodynamics as well as mixed lubrication to predict and discuss the subject-specific pressure and lubrication conditions.

     

Generating spatial data for marine conservation and management

Do fishers know best when it comes to identifying areas with rare and depleted fish species? The global conservation crisis demands that managers marshal all available datasets to inform conservation management plans for depleted species, yet the level of trust placed in local knowledge remains uncertain. This study compares four methods for inferring species distributions of an internationally traded, rare and depleted genus of marine fishes (Hippocampus spp.): the use of (i) fisher interviews; (ii) government research trawls, (iii) scientific diving surveys, and (iv) citizen science contributions. We analyzed these four datasets at the genus and individual species levels to evaluate our conclusions about seahorse spatial occurrence, diversity of species present and the cost effectiveness of sampling effort. We found that fisher knowledge provided more information on our data-poor fish genus at larger spatial scales, with less effort, and for a cheaper price than all other datasets. One drawback was that fishers were unable to provide data down to the species level. People embarking on conservation endeavors for data-poor species may wish to begin with fisher interviews and use these to inform the application of government research, scientific diving, or citizen science programs.     

Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions

Metabolic flux analysis (MFA) has emerged as a tool of great significance for metabolic engineering and mammalian physiology. An important limitation of MFA, as carried out via stable isotope labeling and GC/MS and nuclear magnetic resonance (NMR) measurements, is the large number of isotopomer or cumomer equations that need to be solved, especially when multiple isotopic tracers are used for the labeling of the system. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of realistic situations comprising complex bioreaction networks. Here, we present a novel framework for the modeling of isotopic labeling systems that significantly reduces the number of system variables without any loss of information. The elementary metabolite unit (EMU) framework is based on a highly efficient decomposition method that identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using the knowledge of atomic transitions occurring in the network reactions. The functional units generated by the decomposition algorithm, called EMUs, form the new basis for generating system equations that describe the relationship between fluxes and stable isotope measurements. Isotopomer abundances simulated using the EMU framework are identical to those obtained using the isotopomer and cumomer methods, however, require significantly less computation time. For a typical (13)C-labeling system the total number of equations that needs to be solved is reduced by one order-of-magnitude (100s EMUs vs. 1000s isotopomers). As such, the EMU framework is most efficient for the analysis of labeling by multiple isotopic tracers. For example, analysis of the gluconeogenesis pathway with (2)H, (13)C, and (18)O tracers requires only 354 EMUs, compared to more than two million isotopomers.     

Identifying critical habitat for freshwater turtles: integrating long-term monitoring tools to enhance conservation and management

The effective conservation and management of threatened species requires comprehensive knowledge about resource utilisation. Here we integrated tissue stable isotope analysis and biotelemetry to identify the predominant dietary resources of two sympatric species of freshwater turtle, and locate where those items were acquired. We deployed an array of underwater acoustic telemetry receivers to autonomously, simultaneously, and continuously, monitor the movements of the threatened Elseya albagula and Elusor macrurus, over a 12-month period. Stable isotope (SI) values (δ¹³C and δ¹⁵N) were measured within the carapace of each species, and compared with SI values within potential food items. The integration of movement information and carapace SI data revealed that whilst these species had overlapping home ranges, there was less than 5% probability of inter-species dietary niche overlap. E. macrurus acquired food items consisting of bivalves, gastropods and aquatic insects within rocky riffles whilst E. albagula fed on filamentous algae and crustaceans foraged from the muddy and vegetated shallow margins of deep water pools. Our findings differ from stomach content analysis and mark-recapture studies, which reported these species to have similar habitat and resource requirements. We argue that the observed disparity is because our methods provided a weighted measure of an individual’s dietary preference and habitat utilisation over a broad time-scale, whilst stomach content analysis and mark-recapture studies offer only a single observation of an individual’s dietary preference. The research demonstrates the utility of integrating passive acoustic telemetry and carapace stable isotope analysis for identifying critical habitat for freshwater turtles.     

Ecological traps and species distribution models: a challenge for prioritizing areas of conservation importance

Species distribution models analyse how species use different types of habitats. Their spatial predictions are often used to prioritize areas for conservation. Individuals may, however, prefer settling in habitat types of low quality compared to other available habitats. This ecological trap phenomenon is usually studied in a small number of habitat patches and consequences at the landscape level are largely unknown. It is therefore often unclear whether the spatial pattern of habitat use is aligned with the behavioural decisions made by the individuals during habitat selection or reflects actual variation in the quality of different habitat types. As species distribution models analyse the pattern of occurrence in different habitats, there is a conservation interest in examining what their predictions mean in terms of habitat quality when ecological traps are operating. Previous work in Belgium showed that red-backed shrikes Lanius collurio are more attracted to newly available clear-cut habitat in plantation forests than to the traditionally used farmland habitat. We developed models with shrike distribution data and compared their predictions with spatial variation in shrike reproductive performance used as a proxy for habitat quality. Models accurately predicted shrike distribution and identified the preferred clear-cut patches as the most frequently used habitat, but reproductive performance was lower in clear-cut areas than in farmland. With human-induced rapid environmental changes, organisms may indeed be attracted to low-quality habitats and occupy them at high densities. Consequently, the predictions of statistical models based on occurrence records may not align with variation in significant population parameters for the maintenance of the species. When species expand their range to novel habitats, such models are useful to document the spatial distribution of the organisms, but data on population growth rates are worth collecting before using model predictions to guide the spatial prioritization of conservation actions.     

Adaptive evolutionary conservation: towards a unified concept for defining conservation units

Recent years have seen a debate over various methods that could objectively prioritize conservation value below the species level. Most prominent among these has been the evolutionarily significant unit (ESU). We reviewed ESU concepts with the aim of proposing a more unified concept that would reconcile opposing views. Like species concepts, conflicting ESU concepts are all essentially aiming to define the same thing: segments of species whose divergence can be measured or evaluated by putting differential emphasis on the role of evolutionary forces at varied temporal scales. Thus, differences between ESU concepts lie more in the criteria used to define the ESUs themselves rather than in their fundamental essence. We provide a context-based framework for delineating ESUs which circumvents much of this situation. Rather than embroil in a befuddled debate over an optimal criterion, the key to a solution is accepting that differing criteria will work more dynamically than others and can be used alone or in combination depending on the situation. These assertions constitute the impetus behind adaptive evolutionary conservation.     

An ecosystem evaluation framework for global seamount conservation and management

In the last twenty years, several global targets for protection of marine biodiversity have been adopted but have failed. The Convention on Biological Diversity (CBD) aims at preserving 10% of all the marine biomes by 2020. For achieving this goal, ecologically or biologically significant areas (EBSA) have to be identified in all biogeographic regions. However, the methodologies for identifying the best suitable areas are still to be agreed. Here, we propose a framework for applying the CBD criteria to locate potential ecologically or biologically significant seamount areas based on the best information currently available. The framework combines the likelihood of a seamount constituting an EBSA and its level of human impact and can be used at global, regional and local scales. This methodology allows the classification of individual seamounts into four major portfolio conservation categories which can help optimize management efforts toward the protection of the most suitable areas. The framework was tested against 1000 dummy seamounts and satisfactorily assigned seamounts to proper EBSA and threats categories. Additionally, the framework was applied to eight case study seamounts that were included in three out of four portfolio categories: areas highly likely to be identified as EBSA with high degree of threat; areas highly likely to be EBSA with low degree of threat; and areas with a low likelihood of being EBSA with high degree of threat. This framework will allow managers to identify seamount EBSAs and to prioritize their policies in terms of protecting undisturbed areas, disturbed areas for recovery of habitats and species, or both based on their management objectives. It also identifies seamount EBSAs and threats considering different ecological groups in both pelagic and benthic communities. Therefore, this framework may represent an important tool to mitigate seamount biodiversity loss and to achieve the 2020 CBD goals.     

Ecological Infrastructure as a framework for mapping ecosystem services for place-based conservation and management

Ecosystem services are an important nexus between people and nature. Nevertheless, their inclusion in place-based conservation and management is limited also because they are often intangible. The Ecological Infrastructure (EI) concept is a promising framework to address this, but a clear definition and mapping approach is still missing. We aim to analyse the uses of EI and to distil a definition and recommendations for using EI as a framework for mapping ecosystem services. A semi-systematic review of peer-reviewed and grey literature was conducted to examine: (1) perceptions of what constitutes EI (n = 117), and (2) EI mapping approaches (n = 51). The main interpretations of EI indicated that it should be natural or naturally functioning (56%); deliver multiple services (75%); and benefit humans (64%) and biodiversity (36%). EI was thus defined as ‘natural and naturally functioning ecological systems or networks of ecological systems that deliver multiple services to humans and enable biodiversity persistence’. Studies have used simple proxies, e.g., land cover, to identify EI, sometimes combined with service-specific variables. To evaluate EI performance (26% of studies), modelling all three ecosystem service aspects (capacity, flow, and demand) was considered appropriate. EI prioritisation (50% of studies) as part of a systematic spatial prioritisation process was recommended. Sixteen recommendations for mapping EI for inclusion in place-based conservation and management were developed. We illustrate how EI can be used to integrate ecosystem services into conservation and management in three real-world applications. The EI-based framework is a promising approach and supports the new ‘people and nature’ era in conservation.     

OrthoClust: an orthology-based network framework for clustering data across multiple species

Increasingly, high-dimensional genomics data are becoming available for many organisms.Here, we develop OrthoClust for simultaneously clustering data across multiple species. OrthoClust is a computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific. We demonstrate the application of OrthoClust using the RNA-Seq expression profiles of Caenorhabditis elegans and Drosophila melanogaster from the modENCODE consortium. A potential application of cross-species modules is to infer putative analogous functions of uncharacterized elements like non-coding RNAs based on guilt-by-association.

Electronic supplementary material

The online version of this article (doi:10.1186/gb-2014-15-8-r100) contains supplementary material, which is available to authorized users.     

Combining genetic and demographic data for prioritizing conservation actions: insights from a threatened fish species

Prioritizing and making efficient conservation plans for threatened populations requires information at both evolutionary and ecological timescales. Nevertheless, few studies integrate multidisciplinary approaches, mainly because of the difficulty for conservationists to assess simultaneously the evolutionary and ecological status of populations. Here, we sought to demonstrate how combining genetic and demographic analyses allows prioritizing and initiating conservation plans. To do so, we combined snapshot microsatellite data and a 30‐year‐long demographic survey on a threatened freshwater fish species (Parachondrostoma toxostoma) at the river basin scale. Our results revealed low levels of genetic diversity and weak effective population sizes (<63 individuals) in all populations. We further detected severe bottlenecks dating back to the last centuries (200–800 years ago), which may explain the differentiation of certain populations. The demographic survey revealed a general decrease in the spatial distribution and abundance of P. toxostoma over the last three decades. We conclude that demo‐genetic approaches are essential for (1) identifying populations for which both evolutionary and ecological extinction risks are high; and (2) proposing conservation plans targeted toward these at risk populations, and accounting for the evolutionary history of populations. We suggest that demo‐genetic approaches should be the norm in conservation practices.     

Spatial and temporal scales of adaptive divergence in marine fishes and the implications for conservation

Knowledge of geographic and temporal scales of adaptive genetic variation is crucial to species conservation, yet understanding of these phenomena, particularly in marine systems, is scant. Until recently, the belief has been that because most marine species have highly dispersive or mobile life stages, local adaptation could occur only on broad geographic scales. This view is supported by comparatively low levels of genetic variation among populations as detected by neutral markers. Similarly, the time scale of adaptive divergence has also been assumed to be very long, requiring thousands of generations. Recent studies of a variety of species have challenged these beliefs. First, there is strong evidence of geographically structured local adaptation in physiological and morphological traits. Second, the proportion of quantitative trait variation at the among-population level ( Q _ST) is much higher than it is for neutral markers ( F _ST) and these two metrics of genetic variation are poorly correlated. Third, evidence that selection is a potent evolutionary force capable of sustaining adaptive divergence on contemporary time scales is summarized. The differing spatial and temporal scales of adaptive v. neutral genetic divergence call for a new paradigm in thinking about the relationship between phenogeography (the geography of phenotypic variation) and phylogeography (the geography of lineages) in marine species. The idea that contemporary selective processes can cause fine-scale spatial and temporal divergence underscores the need for a new emphasis on Darwinian fishery science.