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 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.
Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition ...that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman's ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58). Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.
Queen snapper (Etelis oculatus) is of interest from an ecological and management perspective as it is the second most landed finfish species (by total pounds) as determined by Puerto Rico commercial ...landings (2010-2019). As fishing activities progressively expand into deeper waters, it is critical to gather data on deep-sea fish populations to identify essential fish habitats (EFH). In the U.S. Caribbean, the critically data-deficient nature of this species has made this challenging. We investigated the use of ensemble species distribution modeling (ESDM) to predict queen snapper distribution along the coast of Puerto Rico. Using occurrence data and terrain attributes derived from bathymetric datasets at different resolutions, we developed species distribution models unique to each sampling region (west, northeast, and southeast Puerto Rico) using seven different algorithms. Then, we developed ESDM models to analyze fish distribution using the highest-performing algorithms for each region. Model performance was evaluated for each ensemble model, with all depicting 'excellent' predictive capability (AUC > 0.8). Additionally, all ensemble models depicted 'substantial agreement' (Kappa > 0.7). We then used the models in combination with existing knowledge of the species' range to produce binary maps of potential queen snapper distributions. Variable importance differed across spatial resolutions of 30 m (west region) and 8 m (northeast and southeast region); however, bathymetry was consistently one of the best predictors of queen snapper suitable habitat. Positive detections showed strong regional patterns localized around large bathymetric features, such as seamounts and ridges. Despite the data-deficient condition of queen snapper population dynamics, these models will help facilitate the analysis of their spatial distribution and habitat preferences at different spatial scales. Our results therefore provide a first step in designing long-term monitoring programs targeting queen snapper, and determining EFH and the general distribution of this species in Puerto Rico.
Geomorphometry, the science of quantitative terrain characterization, has traditionally focused on the investigation of terrestrial landscapes. However, the dramatic increase in the availability of ...digital bathymetric data and the increasing ease by which geomorphometry can be investigated using geographic information systems (GISs) and spatial analysis software has prompted interest in employing geomorphometric techniques to investigate the marine environment. Over the last decade or so, a multitude of geomorphometric techniques (e.g. terrain attributes, feature extraction, automated classification) have been applied to characterize seabed terrain from the coastal zone to the deep sea. Geomorphometric techniques are, however, not as varied, nor as extensively applied, in marine as they are in terrestrial environments. This is at least partly due to difficulties associated with capturing, classifying, and validating terrain characteristics underwater. There is, nevertheless, much common ground between terrestrial and marine geomorphometry applications and it is important that, in developing marine geomorphometry, we learn from experiences in terrestrial studies. However, not all terrestrial solutions can be adopted by marine geomorphometric studies since the dynamic, four-dimensional (4-D) nature of the marine environment causes its own issues throughout the geomorphometry workflow. For instance, issues with underwater positioning, variations in sound velocity in the water column affecting acoustic-based mapping, and our inability to directly observe and measure depth and morphological features on the seafloor are all issues specific to the application of geomorphometry in the marine environment. Such issues fuel the need for a dedicated scientific effort in marine geomorphometry.This review aims to highlight the relatively recent growth of marine geomorphometry as a distinct discipline, and offers the first comprehensive overview of marine geomorphometry to date. We address all the five main steps of geomorphometry, from data collection to the application of terrain attributes and features. We focus on how these steps are relevant to marine geomorphometry and also highlight differences and similarities from terrestrial geomorphometry. We conclude with recommendations and reflections on the future of marine geomorphometry. To ensure that geomorphometry is used and developed to its full potential, there is a need to increase awareness of (1) marine geomorphometry amongst scientists already engaged in terrestrial geomorphometry, and of (2) geomorphometry as a science amongst marine scientists with a wide range of backgrounds and experiences.
Rivers continue to be harnessed to meet humanity's growing demands for electricity, water, and flood control. While the socioecological impacts of river infrastructure projects (RIPs) have been ...well-documented, methodological approaches to quantify river fragmentation and flow alteration vary widely in spatiotemporal scope, required data, and interpretation. In this review, we first present a framework to visualise the effects of different kinds of RIPs on river fragmentation and flow alteration. We then review available methods to quantify connectivity and flow alteration, along with their data requirements, scale of application, advantages, and disadvantages. Finally, we present decision-making trees to help stakeholders select among these methods based on their objectives, resource availability, and the characteristics of the project(s) being evaluated. Thematic searches of peer-reviewed literature using topic-relevant keywords were conducted on Google Scholar. The bibliography of selected papers was also reviewed, resulting in the selection of 79 publications. Papers that did not define or apply a specific metric were excluded. With respect to fragmentation, we selected papers focused on instream connectivity and excluded those dealing with overland hydrologic connections. For flow alteration, we selected papers that quantified the extent of alteration and excluded those aimed at prescribing environmental flows. The expected hydrological consequences of various RIP types were 'mapped' on a conceptual fragmentation-flow alteration plot. We compiled 29 metrics of river fragmentation and 13 metrics to flow alteration, and used these to develop decision-making trees to facilitate method selection. Despite recent advances in metric development, further work is needed to better understand the relationships between and among metrics, assess their ecological significance and spatiotemporal scale of application, and develop more informative methods that can be effectively applied in data-scarce regions. These objectives are especially critical given the growing use of such metrics in basin-wide conservation and development planning.
Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce ...habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes-recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity-yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making.
•River fragmentation is a threat to riverine ecosystem processes and communities.•We propose a novel Catchment Area-based Fragmentation Index (CAFI)•CAFI avoids methodological and data limitation ...drawbacks of existing methods.•Simulations and case studies support the utility of CAFI in diverse settings.•This approach can improve basin-wide conservation and development planning.
The proliferation of river infrastructure projects has altered aquatic longitudinal connectivity, posing a growing threat to riverine biodiversity and ecosystem processes worldwide. Effective methods to quantify loss of river connectivity across spatiotemporal scales and in data-limited landscapes are important to understand and inform basin-wide conservation and development planning. Here we introduce a Catchment Area-based Fragmentation Index (CAFI) and its derivative, the Catchment Area- and Rainfall-based Fragmentation Index (CARFI) as new metrics to quantify river fragmentation. These indices use catchment area as a proxy for riverine habitat availability, avoiding the drawbacks of existing metrics that rely on river length and associated derivatives. CAFI/CARFI can be computed across spatiotemporal scales, incorporate barrier passability values, assesses the cumulative impact of multiple barriers, and be applied even in data-limited environments.
We first applied CAFI and CARFI to a simulated network to illustrate their properties with respect to the number and location of barriers and compared these results to the widely applied Dendritic Connectivity Index (DCI). While all indices varied with barrier addition, CAFI and CARFI were more sensitive to both barrier number and location. Next, we illustrated the utility of CAFI and CARFI through case studies in two contrasting settings: the Klamath River in California, where dam building has ceased (and dam removals are being considered) and the Netravathi River in India, where dam building is ongoing, with 65 dams proposed for future development. Results indicate that CAFI and CARFI can effectively quantify trends in fragmentation across spatial scales and temporal scenarios of dam development (i.e. descriptive applications) and can aid the prioritization of sites for dam removal, restoration, or conservation (i.e. prescriptive applications). Overall, these indices can quantify the impacts of individual dams and assess a range of development scenarios to inform basin-wide conservation and development planning.
Marine mammals are under pressure from multiple threats, such as global climate change, bycatch, and vessel collisions. In this context, more frequent and spatially extensive surveys for abundance ...and distribution studies are necessary to inform conservation efforts. Marine mammal surveys have been performed visually from land, ships, and aircraft. These methods can be costly, logistically challenging in remote locations, dangerous to researchers, and disturbing to the animals. The growing use of imagery from satellite and unoccupied aerial systems (UAS) can help address some of these challenges, complementing crewed surveys and allowing for more frequent and evenly distributed surveys, especially for remote locations. However, manual counts in satellite and UAS imagery remain time and labor intensive, but the automation of image analyses offers promising solutions. Here, we reviewed the literature for automated methods applied to detect marine mammals in satellite and UAS imagery. The performance of studies is quantitatively compared with metrics that evaluate false positives and false negatives from automated detection against manual counts of animals, which allows for a better assessment of the impact of miscounts in conservation contexts. In general, methods that relied solely on statistical differences in the spectral responses of animals and their surroundings performed worse than studies that used convolutional neural networks (CNN). Despite mixed results, CNN showed promise, and its use and evaluation should continue. Overall, while automation can reduce time and labor, more research is needed to improve the accuracy of automated counts. With the current state of knowledge, it is best to use semi-automated approaches that involve user revision of the output. These approaches currently enable the best tradeoff between time effort and detection accuracy. Based on our analysis, we identified thermal infrared UAS imagery as a future research avenue for marine mammal detection and also recommend the further exploration of object-based image analysis (OBIA). Our analysis also showed that past studies have focused on the automated detection of baleen whales and pinnipeds and that there is a gap in studies looking at toothed whales, polar bears, sirenians, and mustelids.
•Intertidal oyster reef condition is studied using drone lidar.•Surface complexity metrics carry significant relationships with live intertidal oyster densities.•Surface complexity metrics predicted ...medium intertidal oyster densities (29–38/0.25 m2) with the least error.•Metrics such as volume to area ratio allow for rapid intertidal oyster reef monitoring.
Eastern oysters (Crassostrea virginica) generate structurally complex reef systems that offer diverse ecosystem services. However, there is limited understanding of how reef structure translates into reef condition. This knowledge gap might be better addressed if oyster reef structure could be more rapidly assessed. Conventional in situ monitoring techniques are often time-intensive, invasive, and do not provide spatially continuous information on the reef structure. Unoccupied Aircraft Systems (UAS), commonly referred to as drones, equipped with optical sensors can rapidly and non-invasively map intertidal oyster reef surfaces. We demonstrate how a digital surface model from UAS-based light detection and ranging (lidar) can enable very high-resolution characterization and monitoring of intertidal oyster reef surface morphology. Generalized linear models (GLMs) identified relationships between in situ live oyster counts and surface complexity metrics derived from digital surface models produced from lidar point clouds. Statistically significant relationships between surface complexity metrics (e.g., gray level co-occurrence features, volume to area ratio, skewness of elevation) and live oyster counts suggest that surface complexity provides useful proxies for reef condition. Advancing the application of remote sensing to intertidal oyster reefs can help identify reefs that are prone to degradation and inform conservation and restoration strategies.
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