Sound produced by fish spawning aggregations (FSAs) permits the use of passive acoustic methods to identify the timing and location of spawning. However, difficulties in relating sound levels to abundance have impeded the use of passive acoustics to conduct quantitative assessments of biomass. Here we show that models of measured fish sound production versus independently measured fish density can be generated to estimate abundance and biomass from sound levels at FSAs. We compared sound levels produced by spawning Gulf Corvina (Cynoscion othonopterus) with simultaneous measurements of density from active acoustic surveys in the Colorado River Delta, Mexico. During the formation of FSAs, we estimated peak abundance at 1.53 to 1.55 million fish, which equated to a biomass of 2,133 to 2,145 metric tons. Sound levels ranged from 0.02 to 12,738 Pa2, with larger measurements observed on outgoing tides. The relationship between sound levels and densities was variable across the duration of surveys but stabilized during the peak spawning period after high tide to produce a linear relationship. Our results support the use of active acoustic methods to estimate density, abundance, and biomass of fish at FSAs; using appropriately scaled empirical relationships, sound levels can be used to infer these estimates.
Remote Sensing and GIS
Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95–98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management.
The deployment of Hybrid Offshore Wind and Wave Energy Systems (HOWiWaES) towards the simultaneous exploitation of the corresponding offshore renewable energy sources, may efficiently address the common challenge of the offshore wind and the wave energy sector to reduce their costs, with multiple additional benefits. A prerequisite at an early stage of the realization of a HOWiWaES project is the determination of marine areas suitable for the deployment of HOWiWaES. In the present paper, a methodological framework for identifying the most appropriate marine areas in Greece towards the deployment/siting of HOWiWaES is developed and presented. The framework is based on the combined use of multi-criteria decision making methods and Geographical Information Systems (GIS). At the first stage of the analysis, the unsuitable for the deployment of HOWiWaES marine areas are identified through the development of a GIS database that produces thematic maps representing exclusion criteria related to utilization restrictions as well as to economic, technical and social constraints. Then, at the second stage of the analysis, eligible marine areas not satisfying exclusion criteria are evaluated and ranked using the Analytical Hierarchy Process (AHP), based on evaluation criteria related to economic, technical and socio-political factors. The AHP's implementation is supported by the developed GIS database, eliminating significantly the subjectivity in judgments. The results of the paper illustrate the potential for deploying HOWiWaES in Greece, especially in the offshore areas of Crete and in a lengthwise zone extended from North-central to central Aegean.
We describe and analyse data on fishing effort collected by interviewing 1914 fishermen between 2007 and 2010. Combining socio-spatial data collected through a voluntary mapping project called “FisherMap” with UK and European vessel satellite monitoring data provides high resolution, national-scale maps of distribution and relative intensity of fishing for six gear types. The effort maps show, for the first time, a large scale and holistic approach to mapping fishing effort by including the under-reported, yet significant, inshore fishing fleet (85% of registered vessels,<15 m). The data from this study have been used to facilitate the planning, management advice and subsequent designation of 38 inshore Marine Conservation Zones. The authors conclude that, effective management of the inshore marine environment requires up-to-date, high resolution and holistic maps of fishing effort that can be obtained only through validated interpretation of inshore vessel monitoring system data.
Access to high quality spatial data raises fundamental questions about how to select the appropriate scale and unit of analysis. Studies that evaluate the impact of conservation programs have used multiple scales and areal units: from 5x5 km grids; to 30m pixels; to irregular units based on land uses or political boundaries. These choices affect the estimate of program impact. The bias associated with scale and unit selection is a part of a well-known dilemma called the modifiable areal unit problem (MAUP). We introduce this dilemma to the literature on impact evaluation and then explore the tradeoffs made when choosing different areal units. To illustrate the consequences of the MAUP, we begin by examining the effect of scale selection when evaluating a protected area in Mexico using real data. We then develop a Monte Carlo experiment that simulates a conservation intervention. We find that estimates of treatment effects and variable coefficients are only accurate under restrictive circumstances. Under more realistic conditions, we find biased estimates associated with scale choices that are both too large or too small relative to the data generating process or decision unit. In our context, the MAUP may reflect an errors in variables problem, where imprecise measures of the independent variables will bias the coefficient estimates toward zero. This problem may be pronounced at small scales of analysis. Aggregation may reduce this bias for continuous variables, but aggregation exacerbates bias when using a discrete measure of treatment. While we do not find a solution to these issues, even though treatment effects are generally underestimated. We conclude with suggestions on how researchers might navigate their choice of scale and aerial unit when evaluating conservation policies.
Unmanned aerial vehicles (UAVs) are being increasingly used in studies of marine fauna. Here, we tested the use of a UAV (DJI Phantom II®) to assess fine-scale variation in densities of 2 elasmobranchs (blacktip reef sharks Carcharhinus melanopterus and pink whiprays Himantura fai) on reef systems off Moorea (French Polynesia). We flew parallel transects designed to sample reef habitats (fringing, channel and sandflat habitats) across 2 survey blocks. Block 1 included a shark and ray provisioning site with potentially higher elasmobranch densities, whereas Block 2 most likely had lower densities with no provisioning activities. Across 10 survey days in July 2014, we flew 3 transects (400 m) within each survey block (n = 60 total transect passes). As expected, densities (animals ha-1) were significantly higher in Block 1 than in Block 2, particularly where provisioning activities occur. Differences between habitats surveyed were also found. Our study provides the first direct estimates of shark and ray densities in coral-reef ecosystems and demonstrates that UAVs can produce important fishery-independent data for elasmobranchs, particularly in shallow-water habitats.
Remote sensing has been widely used for mapping land cover and is considered key to monitoring changes in forest areas in the REDD+ Measurement, Reporting and Verification (MRV) system. But Remote Sensing as a desk study cannot capture the whole picture; it also requires ground checking. Therefore, complementing remote sensing analysis using participatory mapping can help provide information for an initial forest cover assessment, gain better understanding of how local land use might affect changes, and provide a way to engage local communities in REDD+. Our study looked at the potential of participatory mapping in providing complementary information for remotely sensed maps. The research sites were located in different ecological and socio-economic contexts in the provinces of Papua, West Kalimantan and Central Java, Indonesia. Twenty-one maps of land cover and land use were drawn with local community participation during focus group discussions in seven villages. These maps, covering a total of 270,000ha, were used to add information to maps developed using remote sensing, adding 39 land covers to the eight from our initial desk assessment. They also provided additional information on drivers of land use and land cover change, resource areas, territory claims and land status, which we were able to correlate to understand changes in forest cover. Incorporating participatory mapping in the REDD+ MRV protocol would help with initial remotely sensed land classifications, stratify an area for ground checks and measurement plots, and add other valuable social data not visible at the RS scale. Ultimately, it would provide a forum for local communities to discuss REDD+ activities and develop a better understanding of REDD+.
Maps that depict the distribution of substrate, habitat or biotope types on the seabed are in increasing demand by marine ecologists and spatial planners, underpinning decision making in relation to marine spatial planning and marine protected area network design. Yet, the science discipline of image-based seabed mapping has not fully matured and rapid progress is needed to improve the reliability and accuracy of maps. To speed up the process we have conducted a literature review of common practices in terrestrial image classification based on remote sensing data, a related discipline, albeit with a larger scientific community and longer history. We identified the following key elements of a mapping workflow: (i) Data pre-processing, (ii) Feature extraction, (iii) Feature selection, (iv) Classification, (v) Post-classification enhancements, and (vi) Evaluation of classification performance. Insights gained from the review served as a baseline against which recent seabed mapping studies were compared. In this way we identified knowledge gaps and propose modifications to the mapping workflow. A main concern in current seabed mapping practice is that a large amount of often correlated predictor features is extracted, creating a multidimensional feature space. To effectively fill this space with an appropriate amount of training samples is likely to be impossible. Hence, it is necessary to reduce the dimensionality of the feature space via data transformation [e.g. principal component analysis (PCA)] or feature selection and remove correlated features. We propose to make dimensionality reduction an integral part of any mapping workflow. We also suggest to adopt recommendations for accuracy assessment originally drawn up for terrestrial land cover mapping. These include the publication of two or more measures of accuracy including overall and class-specific metrics, publication of associated confidence limits and the provision of the error matrix.
The Ocean Tracking Network is a major global project to establish tracking of endangered fish and marine mammal species through acoustic telemetry. The project has only begun to generate the policy-related outcomes that may be utilized as benchmarks for evaluating the success of the project. We propose that projects like this one make technical advances before scientific ones, and that scientific advances may be quite long term. Further, the development of policy outcomes is shaped by the larger political economies in which the technologies are located; scientists are quite used to “flying under the radar”, waiting for more propitious circumstances. There are serious questions regarding which actors are capable of making matters of fact issues of public debate.
Remote polar and deepwater fish faunas are under pressure from ongoing climate change and increasing fishing effort. However, these fish communities are difficult to monitor for logistic and financial reasons. Currently, monitoring of marine fishes largely relies on invasive techniques such as bottom trawling, and on official reporting of global catches, which can be unreliable. Thus, there is need for alternative and non-invasive techniques for qualitative and quantitative oceanic fish surveys. Here we report environmental DNA (eDNA) metabarcoding of seawater samples from continental slope depths in Southwest Greenland. We collected seawater samples at depths of 188–918 m and compared seawater eDNA to catch data from trawling. We used Illumina sequencing of PCR products to demonstrate that eDNA reads show equivalence to fishing catch data obtained from trawling. Twenty-six families were found with both trawling and eDNA, while three families were found only with eDNA and two families were found only with trawling. Key commercial fish species for Greenland were the most abundant species in both eDNA reads and biomass catch, and interpolation of eDNA abundances between sampling sites showed good correspondence with catch sizes. Environmental DNA sequence reads from the fish assemblages correlated with biomass and abundance data obtained from trawling. Interestingly, the Greenland shark (Somniosus microcephalus) showed high abundance of eDNA reads despite only a single specimen being caught, demonstrating the relevance of the eDNA approach for large species that can probably avoid bottom trawls in most cases. Quantitative detection of marine fish using eDNA remains to be tested further to ascertain whether this technique is able to yield credible results for routine application in fisheries. Nevertheless, our study demonstrates that eDNA reads can be used as a qualitative and quantitative proxy for marine fish assemblages in deepwater oceanic habitats. This relates directly to applied fisheries as well as to monitoring effects of ongoing climate change on marine biodiversity—especially in polar ecosystems.