Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

Effects of tour boats on dolphin activity examined with sensitivity analysis of Markov chains

In Patagonia, Argentina, watching dolphins, especially dusky dolphins (Lagenorhynchus obscurus), is a new tourist activity. Feeding time decreases and time to return to feeding after feeding is abandoned and time it takes a group of dolphins to feed increase in the presence of boats. Such effects on feeding behavior may exert energetic costs on dolphins and thus reduce an individual's survival and reproductive capacity or maybe associated with shifts in distribution. We sought to predict which behavioral changes modify the activity pattern of dolphins the most. We modeled behavioral sequences of dusky dolphins with Markov chains. We calculated transition probabilities from one activity to another and arranged them in a stochastic matrix model. The proportion of time dolphins dedicated to a given activity (activity budget) and the time it took a dolphin to resume that activity after it had been abandoned (recurrence time) were calculated. We used a sensitivity analysis of Markov chains to calculate the sensitivity of the time budget and the activity-resumption time to changes in behavioral transition probabilities. Feeding-time budget was most sensitive to changes in the probability of dolphins switching from traveling to feeding behavior and of maintaining feeding behavior. Thus, an increase in these probabilities would be associated with the largest reduction in the time dedicated to feeding. A reduction in the probability of changing from traveling to feeding would also be associated with the largest increases in the time it takes dolphins to resume feeding. To approach dolphins when they are traveling would not affect behavior less because presence of the boat may keep dolphins from returning to feeding. Our results may help operators of dolphin-watching vessels minimize negative effects on dolphins.     

A generalized approach for producing,quantifying, and validating citizen science data from wildlife images

Citizen science has the potential to expand the scope and scale of research in ecology and conservation, but many professional researchers remain skeptical of data produced by nonexperts. We devised an approach for producing accurate, reliable data from untrained, nonexpert volunteers. On the citizen science website www.snapshotserengeti.org , more than 28,000 volunteers classified 1.51 million images taken in a large‐scale camera‐trap survey in Serengeti National Park, Tanzania. Each image was circulated to, on average, 27 volunteers, and their classifications were aggregated using a simple plurality algorithm. We validated the aggregated answers against a data set of 3829 images verified by experts and calculated 3 certainty metrics—level of agreement among classifications (evenness), fraction of classifications supporting the aggregated answer (fraction support), and fraction of classifiers who reported “nothing here” for an image that was ultimately classified as containing an animal (fraction blank)—to measure confidence that an aggregated answer was correct. Overall, aggregated volunteer answers agreed with the expert‐verified data on 98% of images, but accuracy differed by species commonness such that rare species had higher rates of false positives and false negatives. Easily calculated analysis of variance and post‐hoc Tukey tests indicated that the certainty metrics were significant indicators of whether each image was correctly classified or classifiable. Thus, the certainty metrics can be used to identify images for expert review. Bootstrapping analyses further indicated that 90% of images were correctly classified with just 5 volunteers per image. Species classifications based on the plurality vote of multiple citizen scientists can provide a reliable foundation for large‐scale monitoring of African wildlife.     

Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.     

Trends in Deforestation and Forest Degradation after a Decade of Monitoring in the Monarch Butterfly Biosphere Reserve in Mexico

We used aerial photographs, satellite images, and field surveys to monitor forest cover in the core zones of the Monarch Butterfly Biosphere Reserve in Mexico from 2001 to 2012. We used our data to assess the effectiveness of conservation actions that involved local, state, and federal authorities and community members (e.g., local landowners and private and civil organizations) in one of the world's most iconic protected areas. From 2001 through 2012, 1254 ha were deforested (i.e., cleared areas had <10% canopy cover), 925 ha were degraded (i.e., areas for which canopy forest decreased), and 122 ha were affected by climatic conditions. Of the total 2179 ha of affected area, 2057 ha were affected by illegal logging: 1503 ha by large‐scale logging and 554 ha by small‐scale logging. Mexican authorities effectively enforced efforts to protect the monarch reserve, particularly from 2007 to 2012. Those efforts, together with the decade‐long financial support from Mexican and international philanthropists and businesses to create local alternative‐income generation and employment, resulted in the decrease of large‐scale illegal logging from 731 ha affected in 2005–2007 to none affected in 2012, although small‐scale logging is of growing concern. However, dire regional social and economic problems remain, and they must be addressed to ensure the reserve's long‐term conservation. The monarch butterfly (Danaus plexippus) overwintering colonies in Mexico—which engage in one of the longest known insect migrations—are threatened by deforestation, and a multistakeholder, regional, sustainable‐development strategy is needed to protect the reserve. Tendencias en la Deforestación y la Degradación de Forestal después de una Década de Monitoreo en la Reserva de la Biósfera de la Mariposa Monarca en México     

Foundations of Resilience Thinking

Through 3 broad and interconnected streams of thought, resilience thinking has influenced the science of ecology and natural resource management by generating new multidisciplinary approaches to environmental problem solving. Resilience science, adaptive management (AM), and ecological policy design (EPD) contributed to an internationally unified paradigm built around the realization that change is inevitable and that science and management must approach the world with this assumption, rather than one of stability. Resilience thinking treats actions as experiments to be learned from, rather than intellectual propositions to be defended or mistakes to be ignored. It asks what is novel and innovative and strives to capture the overall behavior of a system, rather than seeking static, precise outcomes from discrete action steps. Understanding the foundations of resilience thinking is an important building block for developing more holistic and adaptive approaches to conservation. We conducted a comprehensive review of the history of resilience thinking because resilience thinking provides a working context upon which more effective, synergistic, and systems‐based conservation action can be taken in light of rapid and unpredictable change. Together, resilience science, AM, and EPD bridge the gaps between systems analysis, ecology, and resource management to provide an interdisciplinary approach to solving wicked problems. Fundamentos del Pensamiento sobre Resiliencia     

Threats of illegal,unregulated, and unreported fishing to biodiversity and food security in the Republic of the Congo

Illegal, unregulated, and unreported (IUU) fishing poses a major threat to effective management of marine resources, affecting biodiversity and communities dependent on these coastal resources. Spatiotemporal patterns of industrial fisheries in developing countries are often poorly understood, and global efforts to describe spatial patterns of fishing vessel activity are currently based on automatic identification system (AIS) data. However, AIS is often not a legal requirement on fishing vessels, likely resulting in underestimates of the scale and distribution of legal and illegal fishing activity, which could have significant ramifications for targeted enforcement efforts and the management of fisheries resources. To help address this knowledge gap, we analyzed 3 years of vessel monitoring system (VMS) data in partnership with the national fisheries department in the Republic of the Congo to describe the behavior of national and distant-water industrial fleets operating in these waters. We found that the spatial footprint of the industrial fisheries fleet encompassed over one-quarter of the Exclusive Economic Zone. On average, 73% of fishing activity took place on the continental shelf (waters shallower than 200 m). Our findings highlight that VMS is not acting as a deterrent or being effectively used as a proactive management tool. As much as 33% (13% on average) of fishing effort occurred in prohibited areas set aside to protect biodiversity, including artisanal fisheries resources, and the distant-water fleet responsible for as much as 84% of this illegal activity. Given the growth in industrial and distant-water fleets across the region, as well as low levels of management and enforcement, these findings highlight that there is an urgent need for the global community to help strengthen regional and national capacity to analyze national scale data sets if efforts to combat IUU fishing are to be effective.     

Bridging research and practice in conservation

Calls for biodiversity conservation practice to be more evidence based are growing, and we agree evidence use in conservation practice needs improvement. However, evidence-based conservation will not be realized without improved access to evidence. In medicine, unlike in conservation, a well-established and well-funded layer of intermediary individuals and organizations engage with medical practitioners, synthesize primary research relevant to decision making, and make evidence easily accessible. These intermediaries prepare targeted evidence summaries and distribute them to practitioners faced with time-sensitive and value-laden decisions. To be effective, these intermediaries, who we refer to as evidence bridges, should identify research topics based on the priorities of practitioners; synthesize evidence; prepare and distribute easy-to-find and easy-to-use evidence summaries; and develop and maintain networks of connections with researchers and practitioners. Based on a review of the literature regarding evidence intermediaries in conservation and environmental management, as well as an anonymous questionnaire searching for such organizations, we found few intermediaries that met all these criteria. Few evidence bridges that do exist are unable to reach most conservation practitioners, which include resource managers in government and industry, conservation organizations, and farmers and other private landowners. We argue that the lack of evidence bridges from research to practitioners contributes to evidence complacency and limits the use of evidence in conservation action. Nevertheless, several existing organizations help reduce the gap between evidence and practice and could serve as a foundation for building additional components of evidence bridges in conservation. Although evidence bridges need expertise in research and evidence synthesis, they also require expertise in identifying and communicating with the community of practitioners most in need of clear and concise syntheses of evidence. Article Impact Statement: Evidence-based conservation will not be realized without improved access to evidence. We call for intermediary evidence bridges.     

Conservation planning on China's borders with Myanmar,Laos, and Vietnam

Transboundary conservation is playing an increasingly important role in maintaining ecosystem integrity and halting biodiversity loss caused by anthropogenic activities. However, lack of information on species distributions in transboundary regions and understanding of the threats in these areas impairs conservation. We developed a spatial conservation plan for the transboundary areas between Yunnan province, southwestern China, and neighboring Myanmar, Laos, and Vietnam in the Indo-Burma biodiversity hotspot. To identify priority areas for conservation and restoration, we determined species distribution patterns and recent land-use changes and examined the spatiotemporal dynamics of the connected natural forest, which supports most species. We assessed connectivity with equivalent connected area (ECA), which is the amount of reachable habitat for a species. An ECA incorporates the presence of habitat in a patch and the amount of habitat in other patches within dispersal distance. We analyzed 197,845 locality records from specimen collections and monographs for 21,004 plant and vertebrate species. The region of Yunnan immediately adjacent to the international borders had the highest species richness, with 61% of recorded species and 56% of threatened vertebrates, which suggests high conservation value. Satellite imagery showed the area of natural forest in the border zone declined by 5.2% (13,255 km²) from 1995 to 2018 and monoculture plantations increased 92.4%, shrubland 10.1%, and other cropland 6.2%. The resulting decline in connected natural forest reduced the amount of habitat, especially for forest specialists with limited dispersal abilities. The most severe decline in connectivity was along the Sino-Vietnamese border. Many priority areas straddle international boundaries, indicating demand and potential for establishing transboundary protected areas. Our results illustrate the importance of bi- and multilateral cooperation to protect biodiversity in this region and provide guidance for future conservation planning and practice.     

Risks to large marine protected areas posed by drifting fish aggregation devices

Mapping and predicting the potential risk of fishing activities to large marine protected areas (MPAs), where management capacity is low but fish biomass may be globally important, is vital to prioritizing enforcement and maximizing conservation benefits. Drifting fish aggregating devices (dFADs) are a highly effective fishing method employed in purse seine fisheries that attract and accumulate biomass fish, making fish easier to catch. However, dFADs are associated with several negative impacts, including high bycatch rates and lost or abandoned dFADs becoming beached on sensitive coastal areas (e.g., coral reefs). Using Lagrangian particle modeling, we determined the potential transit of dFADs in a large MPA around the Chagos Archipelago in the central Indian Ocean. We then quantified the risk of dFADs beaching on the archipelago's reefs and atolls and determined the potential for dFADs to pass through the MPA, accumulate biomass while within, and export it into areas where it can be legally fished (i.e., transit). Over one-third (37.51%) of dFADs posed a risk of either beaching or transiting the MPA for >14 days, 17.70% posed a risk of beaching or transiting the MPA for >30 days, and 13.11% posed a risk of beaching or transiting the MPA for >40 days. Modeled dFADs deployed on the east and west of the perimeter were more likely to beach and have long transiting times (i.e., posed the highest risk). The Great Chagos Bank, the largest atoll in the archipelago, was the most likely site to be affected by dFADs beaching. Overall, understanding the interactions between static MPAs and drifting fishing gears is vital to developing suitable management plans to support enforcement of MPA boundaries and the functioning and sustainability of their associated biomass.