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An ecological framework for informing permitting decisions on scientific activities in protected areas.

ABSTRACT: There are numerous reasons to conduct scientific research within protected areas, but research activities may also negatively impact organisms and habitats, and thus conflict with a protected area's conservation goals. We developed a quantitative ecological decision-support framework that estimates these potential impacts so managers can weigh costs and benefits of proposed research projects and make informed permitting decisions. The framework generates quantitative estimates of the ecological impacts of the project and the cumulative impacts of the proposed project and all other projects in the protected area, and then compares the estimated cumulative impacts of all projects with policy-based acceptable impact thresholds. We use a series of simplified equations (models) to assess the impacts of proposed research to: a) the population of any targeted species, b) the major ecological assemblages that make up the community, and c) the physical habitat that supports protected area biota. These models consider both targeted and incidental impacts to the ecosystem and include consideration of the vulnerability of targeted species, assemblages, and habitats, based on their recovery time and ecological role. We parameterized the models for a wide variety of potential research activities that regularly occur in the study area using a combination of literature review and expert judgment with a precautionary approach to uncertainty. We also conducted sensitivity analyses to examine the relationships between model input parameters and estimated impacts to understand the dominant drivers of the ecological impact estimates. Although the decision-support framework was designed for and adopted by the California Department of Fish and Wildlife for permitting scientific studies in the state-wide network of marine protected areas (MPAs), the framework can readily be adapted for terrestrial and freshwater protected areas.

SUBMITTER: Saarman ET

PROVIDER: S-EPMC6007909 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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An ecological framework for informing permitting decisions on scientific activities in protected areas.

Saarman Emily T ET Owens Brian B Murray Steven N SN Weisberg Stephen B SB Ambrose Richard F RF Field John C JC Nielsen Karina J KJ Carr Mark H MH

PloS one 20180619 6

There are numerous reasons to conduct scientific research within protected areas, but research activities may also negatively impact organisms and habitats, and thus conflict with a protected area's conservation goals. We developed a quantitative ecological decision-support framework that estimates these potential impacts so managers can weigh costs and benefits of proposed research projects and make informed permitting decisions. The framework generates quantitative estimates of the ecological ...[more]

PMID: 29920527

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Project description:Protected areas are a crucial tool for halting the loss of biodiversity. Yet, the management of protected areas is under resourced, impacting the ability to achieve effective conservation actions. Effective management depends on the application of the best available knowledge, which can include both scientific evidence and the local knowledge of onsite managers. Despite the clear value of evidence-based conservation, there is still little known about how much scientific evidence is used to guide the management of protected areas. This knowledge gap is especially evident in developing countries, where resource limitations and language barriers may create additional challenges for the use of scientific evidence in management. To assess the extent to which scientific evidence is used to inform management decisions in a developing country, we surveyed Brazilian protected area managers about the information they use to support their management decisions. We targeted on-ground managers who are responsible for management decisions made at the local protected area level. We asked managers about the sources of evidence they use, how frequently they assess the different sources of evidence and the scientific content of the different sources of evidence. We also considered a range of factors that might explain the use of scientific evidence to guide the management of protected areas, such as the language spoken by managers, the accessibility of evidence sources and the characteristics of the managers and the protected areas they manage. The managers who responded to our questionnaire reported that they most frequently made decisions based on their personal experience, with scientific evidence being used relatively infrequently. While managers in our study tended to value scientific evidence less highly than other sources, most managers still considered science important for management decisions. Managers reported that the accessibility of scientific evidence is low relative to other types of evidence, with key barriers being the low levels of open access research and insufficient technical training to enable managers to interpret research findings. Based on our results, we suggest that managers in developing countries face all the same challenges as those in developed countries, along with additional language barriers that can prevent greater use of scientific evidence to support effective management of protected areas in Brazil.

Project description:Marine protected areas (MPAs) are a primary tool for the stewardship, conservation, and restoration of marine ecosystems, yet 69% of global MPAs are only partially protected (i.e., are open to some form of fishing). Although fully protected areas have well-documented outcomes, including increased fish diversity and biomass, the effectiveness of partially protected areas is contested. Partially protected areas may provide benefits in some contexts and may be warranted for social reasons, yet social outcomes often depend on MPAs achieving their ecological goals to distinguish them from open areas and justify the cost of protection. We assessed the social perceptions and ecological effectiveness of 18 partially protected areas and 19 fully protected areas compared with 19 open areas along 7000 km of coast of southern Australia. We used mixed methods, gathering data via semistructured interviews, site surveys, and Reef Life (underwater visual census) surveys. We analyzed qualitative data in accordance with grounded theory and quantitative data with multivariate and univariate linear mixed-effects models. We found no social or ecological benefits for partially protected areas relative to open areas in our study. Partially protected areas had no more fish, invertebrates, or algae than open areas; were poorly understood by coastal users; were not more attractive than open areas; and were not perceived to have better marine life than open areas. These findings provide an important counterpoint to some large-scale meta-analyses that conclude partially protected areas can be ecologically effective but that draw this conclusion based on narrower measures. We argue that partially protected areas act as red herrings in marine conservation because they create an illusion of protection and consume scarce conservation resources yet provide little or no social or ecological gain over open areas. Fully protected areas, by contrast, have more fish species and biomass and are well understood, supported, and valued by the public. They are perceived to have better marine life and be improving over time in keeping with actual ecological results. Conservation outcomes can be improved by upgrading partially protected areas to higher levels of protection including conversion to fully protected areas.

Project description:BackgroundSalvia is a large, diverse, and polymorphous genus of the family Lamiaceae, comprising about 900 ornamentals, medicinal species with almost cosmopolitan distribution in the world. The success of Salvia limbata seed germination depends on a numerous ecological factors and stresses. We aimed to analyze Salvia limbata seed germination under four ecological stresses of salinity, drought, temperature and pH, with application of artificial intelligence modeling techniques such as MLR (Multiple Linear Regression), and MLP (Multi-Layer Perceptron). The S.limbata seeds germination was tested in different combinations of abiotic conditions. Five different temperatures of 10, 15, 20, 25 and 30 °C, seven drought treatments of 0, -2, -4, -6, -8, -10 and -12 bars, eight treatments of salinity containing 0, 50, 100.150, 200, 250, 300 and 350 mM of NaCl, and six pH treatments of 4, 5, 6, 7, 8 and 9 were tested. Indeed 228 combinations were tested to determine the percentage of germination for model development.ResultsComparing to the MLR, the MLP model represents the significant value of R2 in training (0.95), validation (0.92) and test data sets (0.93). According to the results of sensitivity analysis, the values of drought, salinity, pH and temperature are respectively known as the most significant variables influencing S. limbata seed germination. Areas with high moisture content and low salinity in the soil have a high potential to seed germination of S. limbata. Also, the temperature of 18.3 °C and pH of 7.7 are proposed for achieving the maximum number of germinated S. limbata seeds.ConclusionsMultilayer perceptron model helps managers to determine the success of S.limbata seed planting in agricultural or natural ecosystems. The designed graphical user interface is an environmental decision support system tool for agriculture or rangeland managers to predict the success of S.limbata seed germination (percentage) in different ecological constraints of lands.

Dataset Information

An ecological framework for informing permitting decisions on scientific activities in protected areas.

Publications

An ecological framework for informing permitting decisions on scientific activities in protected areas.

Similar Datasets

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