Dataset Information

Optimizing conservation planning for multiple cohabiting species.

ABSTRACT: Conservation planning often involves multiple species occupying large areas including habitat sites with varying characteristics. For a given amount of financial resources, designing a spatially coherent nature reserve system that provides the best possible protection to targeted species is an important ecological and economic problem. In this paper, we address this problem using optimization methods. Incorporating spatial criteria in an optimization framework considering spatial habitat needs of multiple species poses serious challenges because of modeling and computational complexities. We present a novel linear integer programming model to address this issue considering spatial contiguity and compactness of the reserved area. The model uses the concept of path in graph theory to ensure contiguity and minimizes the sum of distances between selected sites and a central site in individual reserves to promote compactness. We test the computational efficiency of the model using randomly generated data sets. The results show that the model can be solved quite efficiently in most cases. We also present an empirical application of the model to simultaneous protection of two cohabiting species, Gopher Tortoise and Gopher Frogs, in a military installation in Georgia, USA.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7307775 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimizing conservation planning for multiple cohabiting species.

Wang Yicheng Y Fang Qiaoling Q Dissanayake Sahan T M STM Önal Hayri H

PloS one 20200622 6

Conservation planning often involves multiple species occupying large areas including habitat sites with varying characteristics. For a given amount of financial resources, designing a spatially coherent nature reserve system that provides the best possible protection to targeted species is an important ecological and economic problem. In this paper, we address this problem using optimization methods. Incorporating spatial criteria in an optimization framework considering spatial habitat needs o ...[more]

PMID: 32569315

Similar Datasets

Project description:Genome-scale datasets have been used extensively in model organisms to screen for specific candidates or to predict functions for uncharacterized genes. However, despite the availability of extensive knowledge in model organisms, the planning of genome-scale experiments in poorly studied species is still based on the intuition of experts or heuristic trials. We propose that computational and systematic approaches can be applied to drive the experiment planning process in poorly studied species based on available data and knowledge in closely related model organisms. In this paper, we suggest a computational strategy for recommending genome-scale experiments based on their capability to interrogate diverse biological processes to enable protein function assignment. To this end, we use the data-rich functional genomics compendium of the model organism to quantify the accuracy of each dataset in predicting each specific biological process and the overlap in such coverage between different datasets. Our approach uses an optimized combination of these quantifications to recommend an ordered list of experiments for accurately annotating most proteins in the poorly studied related organisms to most biological processes, as well as a set of experiments that target each specific biological process. The effectiveness of this experiment- planning system is demonstrated for two related yeast species: the model organism Saccharomyces cerevisiae and the comparatively poorly studied Saccharomyces bayanus. Our system recommended a set of S. bayanus experiments based on an S. cerevisiae microarray data compendium. In silico evaluations estimate that less than 10% of the experiments could achieve similar functional coverage to the whole microarray compendium. This estimation was confirmed by performing the recommended experiments in S. bayanus, therefore significantly reducing the labor devoted to characterize the poorly studied genome. This experiment-planning framework could readily be adapted to the design of other types of large-scale experiments as well as other groups of organisms.

Project description:Despite increasing attention to the human dimension of conservation projects, a rigorous, systematic methodology for planning for ecosystem services has not been developed. This is in part because flows of ecosystem services remain poorly characterized at local-to-regional scales, and their protection has not generally been made a priority. We used a spatially explicit conservation planning framework to explore the trade-offs and opportunities for aligning conservation goals for biodiversity with six ecosystem services (carbon storage, flood control, forage production, outdoor recreation, crop pollination, and water provision) in the Central Coast ecoregion of California, United States. We found weak positive and some weak negative associations between the priority areas for biodiversity conservation and the flows of the six ecosystem services across the ecoregion. Excluding the two agriculture-focused services-crop pollination and forage production-eliminates all negative correlations. We compared the degree to which four contrasting conservation network designs protect biodiversity and the flow of the six services. We found that biodiversity conservation protects substantial collateral flows of services. Targeting ecosystem services directly can meet the multiple ecosystem services and biodiversity goals more efficiently but cannot substitute for targeted biodiversity protection (biodiversity losses of 44% relative to targeting biodiversity alone). Strategically targeting only biodiversity plus the four positively associated services offers much promise (relative biodiversity losses of 7%). Here we present an initial analytical framework for integrating biodiversity and ecosystem services in conservation planning and illustrate its application. We found that although there are important potential trade-offs between conservation for biodiversity and for ecosystem services, a systematic planning framework offers scope for identifying valuable synergies.

Project description:The northern spotted owl (Strix occidentalis caurina) was listed as threatened under the U.S. Endangered Species Act (ESA) in 1990. We applied modern spatial conservation theory and models to evaluate several candidate critical habitat networks, and sought an efficient conservation solution that encompassed the highest value lands for spotted owl recovery rather than maximizing the total area of potential critical habitat. We created a map of relative habitat suitability, which served as input to the spatial conservation prioritization program Zonation. We used the spatially-explicit individual-based population model HexSim to estimate and compare simulated spotted owl population outcomes among a suite of candidate critical habitat networks that varied in size and spatial arrangement under alternative scenarios of future habitat suitability and barred owl (S. varia) effects. We evaluated simulated spotted owl population outcomes, including total population size, and extinction and quasi-extinction likelihoods for 108 combinations of candidate critical habitat networks by habitat change by barred owl scenarios, both range-wide and within 11 distinct portions of the owl's range. Barred owl encounter rates and the amount and suitability of habitat had substantial effects on simulated spotted owl populations. When barred owl encounter rates were high, changes in the amount and suitability of habitat had minimal impacts on population performance. Under lowered barred owl encounter rates, candidate critical habitat networks that included most existing high suitability habitat supported a high likelihood of long-term population persistence. Barred owls are currently the primary driving force behind poor population performance of NSOs; however, our models demonstrated that a sufficient area of high suitability habitat remains essential for recovery when effects of barred owls can be reduced. The modeling approach we employed is sufficiently flexible to incorporate new information about spotted owls as it becomes available and could likely be applied to conservation planning for other species.

Dataset Information

Optimizing conservation planning for multiple cohabiting species.

Publications

Optimizing conservation planning for multiple cohabiting species.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure