Prioritizing forest management actions to benefit marine habitats in data-poor regions.
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ABSTRACT:
SUBMITTER: Delevaux JMS
PROVIDER: S-EPMC9293477 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Managing marine nonindigenous species (mNIS) is challenging, because marine environments are highly connected, allowing the dispersal of species across large spatial scales, including geopolitical borders. Cross-border inconsistencies in biosecurity management can promote the spread of mNIS across geopolitical borders, and incursions often go unnoticed or unreported. Collaborative surveillance programs can enhance the early detection of mNIS, when response may still be possible, and can foster capacity building around a common threat. Regional or international databases curated for mNIS can inform local monitoring programs and can foster real-time information exchange on mNIS of concern. When combined, local species reference libraries, publicly available mNIS databases, and predictive modeling can facilitate the development of biosecurity programs in regions lacking baseline data. Biosecurity programs should be practical, feasible, cost-effective, mainly focused on prevention and early detection, and be built on the collaboration and coordination of government, nongovernment organizations, stakeholders, and local citizens for a rapid response.
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Project description:Urbanization-driven landscape changes are harmful to many species. Negative effects can be mitigated through habitat preservation and restoration, but it is often difficult to prioritize these conservation actions. This is due, in part, to the scarcity of species response data, which limit the predictive accuracy of modeling to estimate critical thresholds for biological decline and recovery. To address these challenges, we quantify effort required for restoration, in combination with a clear conservation objective and associated metric (e.g., habitat for focal organisms). We develop and apply this framework to coho salmon (Oncorhynchus kisutch), a highly migratory and culturally iconic species in western North America that is particularly sensitive to urbanization. We examine how uncertainty in biological parameters may alter locations prioritized for conservation action and compare this to the effect of shifting to a different conservation metric (e.g., a different focal salmon species). Our approach prioritized suburban areas (those with intermediate urbanization effects) for preservation and restoration action to benefit coho. We found that prioritization was most sensitive to the selected metric, rather than the level of uncertainty or critical threshold values. Our analyses highlight the importance of identifying metrics that are well-aligned with intended outcomes.
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Project description: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. We combined genetic and demographic data from a threatened freshwater fish species (Parachondrostoma toxostoma) at the river basin scale for conservation purposes. Genetic diversity and effective population sizes are very low, probably due to the strong genetic bottlenecks detected in this study. The species spatial distribution and abundance also decreased during the last decades.
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Project description:Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species' populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.
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Project description:Marine biogenic habitats-habitats created by living organisms-provide essential ecosystem functions and services, such as physical structuring, nutrient cycling, biodiversity support, and increases in primary, secondary, and tertiary production. With the growing trend toward ecosystem approaches to marine conservation and fisheries management, there is greater emphasis on rigorously designed habitat monitoring programs. However, such programs are challenging to design for data-limited habitats for which underlying ecosystem processes are poorly understood. To provide guidance in this area, we reviewed approaches to benthic assessments across well-studied marine biogenic habitats and identified common themes related to indicator selection, sampling methods, and survey design. Biogenic habitat monitoring efforts largely focus on the characteristics, distribution, and ecological function of foundation species, but may target other habitat-forming organisms, especially when community shifts are observed or expected, as well as proxies of habitat status, such as indicator species. Broad-scale methods cover large spatial areas and are typically used to examine the spatial configuration of habitats, whereas fine-scale methods tend to be laborious and thus restricted to small survey areas, but provide high-resolution data. Recent, emerging methods enhance the capabilities of surveying large areas at high spatial resolution and improve data processing efficiency, bridging the gap between broad- and fine-scale methods. Although sampling design selection may be limited by habitat characteristics and available resources, it is critically important to ensure appropriate matching of ecological, observational, and analytical scales. Drawing on these common themes, we propose a structured, iterative approach to designing monitoring programs for marine biogenic habitats that allows for rigorous data collection to inform management strategies, even when data and resource limitations are present. A practical application of this approach is illustrated using glass sponge reefs-a recently discovered and data-limited habitat type-as a case study.
| S-EPMC6662303 | biostudies-literature
Project description:Management of invasive populations is typically investigated case-by-case. Comparative approaches have been applied to single aspects of management, such as demography, with cost or efficacy rarely incorporated.We present an analysis of the ranks of management actions for 14 species in five countries that extends beyond the use of demography alone to include multiple metrics for ranking management actions, which integrate cost, efficacy and demography (cost-effectiveness) and managers' expert opinion of ranks. We use content analysis of manager surveys to assess the multiple criteria managers use to rank management strategies.Analysis of the matrix models for managed populations showed that all management actions led to reductions in population growth rate (λ), with a median 48% reduction in λ across all management units; however, only 66% of the actions led to declining populations (λ < 1).Each management action ranked by cost-effectiveness and cost had a unique rank; however, elasticity ranks were often tied, providing less discrimination among management actions. Ranking management actions by cost alone aligned well with cost-effectiveness ranks and demographic elasticity ranks were also well aligned with cost-effectiveness. In contrast, efficacy ranks were aligned with managers' ranks and managers identified efficacy and demography as important. 80% of managers identified off-target effects of management as important, which was not captured using any of the other metrics. Synthesis and applications. A multidimensional view of the benefits and costs of management options provides a range of single and integrated metrics. These rankings, and the relationships between them, can be used to assess management actions for invasive plants. The integrated cost-effectiveness approach goes well 'beyond demography' and provides additional information for managers; however, cost-effectiveness needs to be augmented with information on off-target effects and social impacts of management in order to provide greater benefits for on-the-ground management.
| S-EPMC4949517 | biostudies-literature
Project description:While genome-wide differential DNA methylation regions (DMRs) have been extensively identified, the comprehensive prioritization of their functional importance is still poorly explored. Here, we aggregated multiple data resources rooted in the genome, epigenome and transcriptome to systematically prioritize functional DMRs (fDMRs) in colorectal cancer (CRC). As demonstrated, the top-ranked fDMRs from all of the data resources showed a strong enrichment for known methylated genes. Additionally, we analyzed those top 5% DMR-coupled coding genes using functional enrichment, which resulted in significant disease-related biological functions in contrast to the tail 5% genes. To further confirm the functional importance of the top-ranked fDMRs, we applied chromatin modification alterations of CRC cell lines to characterize their functional regulation. Specifically, we extended the utility of the top-ranked DMR-coupled genes to serve as classification and survival biomarkers, which showed a robust performance across diverse independent data sets. Collectively, our results established an integrative framework to prioritize fDMRs, which could help characterize aberrant DNA methylation-induced potential mechanisms underlying tumorigenesis and uncover epigenome-based biomarkers for clinical diagnosis and prognosis.
| S-EPMC4523937 | biostudies-literature
Project description:Incentivized debt conversion is a financing mechanism that can assist countries with a heavy debt burden to bolster their long-term domestic investment in nature conservation. The Nature Conservancy, an international conservation-based nongovernmental organization, is adapting debt conversions to support marine conservation efforts by small island developing states and coastal countries. Prioritizing debt conversion opportunities according to their potential return on investment can increase the impact and effectiveness of this finance mechanism. We developed guidance on how to do so with a decision-support approach that relies on a novel threat-based adaptation of cost-effectiveness analysis. We constructed scenarios by varying parameters of the approach, including enabling conditions, expected benefits, and threat classifications. Incorporating both abatable and unabatable threats affected priorities across planning scenarios. Similarly, differences in scenario construction resulted in unique solution sets for top priorities. We show how environmental organizations, private entities, and investment banks can adopt structured prioritization frameworks for making decisions about conservation finance investments, such as debt conversions. Our guidance can accommodate a suite of social, ecological, and economic considerations, making the approach broadly applicable to other conservation finance mechanisms or investment strategies that seek to establish a transparent process for return-on-investment decision-making.
| S-EPMC8129986 | biostudies-literature
Project description:BackgroundResolving 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 findingsTo 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/significanceThe 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.
| S-EPMC3003737 | biostudies-literature
Project description:Funding biodiversity conservation strategies are usually minimal, thus prioritizing habitats at high risk should be conducted. We developed and tested a conservation priority index (CPI) that ranks habitats to aid in prioritizing them for conservation. We tested the index using 1897 fish species from 273 African inland lakes and 34 countries. In the index, lake surface area, rarity, and their International Union for Conservation of Nature (IUCN) Red List status were incorporated. We retrieved data from the Global Biodiversity Information Facility (GBIF) and IUCN data repositories. Lake Nyasa had the highest species richness (424), followed by Tanganyika (391), Nokoué (246), Victoria (216), and Ahémé (216). However, lakes Otjikoto and Giunas had the highest CPI of 137.2 and 52.1, respectively. Lakes were grouped into high priority (CPI > 0.5; n = 56) and low priority (CPI < 0.5; n = 217). The median surface area between priority classes was significantly different (W = 11,768, p < .05, effect size = 0.65). Prediction accuracy of Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) for priority classes were 0.912 and 0.954, respectively. Both models exhibited lake surface area as the variable with the highest importance. CPI generally increased with a decrease in lake surface area. This was attributed to less ecological substitutability and higher exposure levels of anthropogenic stressors such as pollution to a species in smaller lakes. Also, the highest species richness per unit area was recorded for high-priority lakes. Thus, smaller habitats or lakes may be prioritized for conservation although larger waterbodies or habitats should not be ignored. The index can be customized to local, regional, and international scales as well as marine and terrestrial habitats.
| S-EPMC8956788 | biostudies-literature