Species distribution models and local ecological knowledge in marine protected areas: The case of Os Miñarzos (Spain)

Species distribution models (SDMs) are a tool for predicting the eventual geographical range of an emerging pathogen. Most SDMs, however, rely on an assumption of equilibrium with the environment, which an emerging pathogen, by definition, has not reached. To determine if some SDM approaches work better than others for modelling the spread of emerging, non-equilibrium pathogens, we studied time-sensitive predictive performance of SDMs for Batrachochytrium dendrobatidis, a devastating infectious fungus of amphibians, using multiple methods trained on time-incremented subsets of the available data. We split our data into timeline-based training and testing sets, and evaluated models on each set using standard performance criteria, including AUC, kappa, false negative rate and the Boyce index. Of eight models examined, we found that boosted regression trees and random forests performed best, closely followed by MaxEnt. As expected, predictive performance generally improved with the length of time series used for model training. These results provide information on how quickly the potential extent of an emerging disease may be determined, and identify which modelling frameworks are likely to provide useful information during the early phases of pathogen expansion.

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“…Given increasing use of the Boyce index for SDM evaluation (e.g. [53–55]), this discrepancy warrants further investigation.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of climate-based forecasts of pathogen spread

2017

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“…Boosted regression trees Supervised Costa et al, 2014;Hewitt et al, 2015 Classification rule with unbiased interaction selection and estimation Supervised Ierodiaconou et al, 2011 Discriminant function analysis Supervised Degraer et al, 2008 Ecological niche factor analysis Supervised Tong et al, 2012;Sánchez-Carnero et al, 2016 Fuzzy k-means Unsupervised Falace et al, 2015 Generalized additive model Supervised Schmiing et al, 2013;Touria et al, 2015 Generalized Quick, unbiased, efficient tree Supervised Ierodiaconou et al, 2011;Hasan et al, 2012 Random forest Both Hasan et al, 2012;Diesing et al, 2014;Piechaud et al, 2015 Support vector machine Supervised Hasan et al, 2012 Frontiers in Marine Science | www.frontiersin.orgFIGURE 2 | Example of how different methods can produce different outcomes. The input data were bathymetric data, backscatter data, and topographic data (i.e., slope, easterness, northerness, and relative deviation from mean value) (see Lecours et al, 2016b).…”

Section: Supervised/unsupervised Examplesmentioning

confidence: 99%

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

Lecours

2017

Front. Mar. Sci.

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Conservation planning and management typically require accurate and spatially explicit data at scales that are relevant for conservation objectives. In marine conservation, these data are often combined with spatial analytical techniques to produce marine habitat maps. While marine habitat mapping is increasingly used to inform conservation efforts, this field is still relatively young and its methods are rapidly evolving. Because conservation efforts do not always specify standards or guidelines for the production of habitat maps, results can vary dramatically. As representations of real environmental characteristics, habitat maps are highly sensitive to how they are produced. In this review paper, I present four concepts that are known to cause variation in spatial representation and prediction of habitats: the methodology used, the quality and scale of the data, and the choice of variables in regards to fitness for use. I then discuss the potential antinomy associated with the use of habitat maps in conservation: while habitat maps have become an invaluable tool to inform and assist decision-making, maps of the same area built using different methods and data may provide dissimilar representations, thus providing different information and possibly leading to different decisions. Exploring the theories and methods that have proved effective in terrestrial conservation and the spatial sciences, and how they can be integrated in marine habitat mapping practices, could help improve maps used to support marine conservation efforts and result in more reliable products to inform conservation decisions. Having a strong, consistent, transparent, repeatable, and science-based protocol for data collection and mapping is essential for effectively supporting decision-makers in developing conservation and management plans. The development of user-friendly tools to assist in the application of such protocol is crucial to a widespread improvement in practices. I discuss the potential to use interactive and collaborative Geographic Information Systems (GIS) to encourage the conservation and management community, from data collectors and mapmakers to decision-makers, to move toward a digital resilience and to develop such science-based protocol. Until standards and protocols are developed, habitat maps should always be interpreted with care, and the methods and metadata associated with their production should always be explicitly stated.

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“…Application of questionnaire surveys and long‐term satellite‐based remote‐sensing data may help to fill these information gaps over a broad spatial scale. Information from questionnaire surveys has proved valuable in revealing the occurrence and distribution of animals over a broad geographic range (Logan, Gerber, Karpanty, Justin, & Rabenahy, ; Turvey et al, ; Wang, Yang et al, ; Wu, Wang, Ding, Miao, & Zhu, ), and to facilitate conservation‐action planning and protected‐area design (Sánchez‐Carnero, Rodríguez‐Pérez, Couñago, Barzik, & Freire, ; Turvey et al, ). The legacy of Landsat missions (http://landsat.usgs.gov/about_mission_history.php) provides satellite‐borne monitoring of environmental characteristics on a fine spatial (30–60 m) and spectral resolution over a mesoscopic region.…”

Section: Introductionmentioning

confidence: 99%

Long‐term habitat loss in a lightly‐disturbed population of the Indo‐Pacific humpback dolphin, Sousa chinensis

Peng

et al. 2017

Aquatic Conservation

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Coastal and estuarine waters are important ecosystems with high primary and secondary productivity, but they are prone to the impacts of habitat loss caused by anthropogenic activities. For species exclusively inhabiting coastal and estuarine waters, such as the Indo‐Pacific humpback dolphin, Sousa chinensis, irreversible habitat loss can have dramatic implications for population viability. A Landsat image database was used to determine the extent of coastal changes along the northern Beibu Gulf, where a large humpback dolphin population is found. The results were compared with the standardized sighting gradient (SPUF) determined from a questionnaire survey of fishermen and likely core habitats identified by application of a global digital elevation model. Both SPUF and likely core habitat results indicated a continuous distribution of the humpback dolphin along the northern Beibu Gulf. Landsat images revealed that 129.6 km2 of coastal waters were permanently lost in the past 40 years, 60 km2 within the likely core habitats. Although this may be considered small, the impact of such habitat loss could be substantial in some local habitats. The humpback dolphin population in the northern Beibu Gulf should be regarded as one management unit, with two or more social subunits. Immediate systematic surveys are needed to fill information gaps on true distribution range and habitat‐use patterns. Habitat protection actions for dolphins in the northern Beibu Gulf should include both core and linking habitats, including enacting protected areas in core habitats, mitigating anthropogenic impacts in likely habitats, restoring both coastal waters and surrounding landscape quality, effective treatment of industrial sewage discharge, and comprehensive environmental impact assessments for the planning of coastal development projects.

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Species distribution models and local ecological knowledge in marine protected areas: The case of Os Miñarzos (Spain)

Cited by 18 publications

References 55 publications

Accuracy of climate-based forecasts of pathogen spread

Accuracy of climate-based forecasts of pathogen spread

On the Use of Maps and Models in Conservation and Resource Management (Warning: Results May Vary)

Long‐term habitat loss in a lightly‐disturbed population of the Indo‐Pacific humpback dolphin, Sousa chinensis

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