Eric H. Fegraus

Standardized Assessment of Biodiversity Trends in Tropical Forest Protected Areas: The End Is Not in Sight

Extinction rates in the Anthropocene are three orders of magnitude higher than background and disproportionately occur in the tropics, home of half the world’s species. Despite global efforts to combat tropical species extinctions, lack of high-quality, objective information on tropical biodiversity has hampered quantitative evaluation of conservation strategies. In particular, the scarcity of population-level monitoring in tropical forests has stymied assessment of biodiversity outcomes, such as the status and trends of animal populations in protected areas. Here, we evaluate occupancy trends for 511 populations of terrestrial mammals and birds, representing 244 species from 15 tropical forest protected areas on three continents. For the first time to our knowledge, we use annual surveys from tropical forests worldwide that employ a standardized camera trapping protocol, and we compute data analytics that correct for imperfect detection. We found that occupancy declined in 22%, increased in 17%, and exhibited no change in 22% of populations during the last 3–8 years, while 39% of populations were detected too infrequently to assess occupancy changes. Despite extensive variability in occupancy trends, these 15 tropical protected areas have not exhibited systematic declines in biodiversity (i.e., occupancy, richness, or evenness) at the community level. Our results differ from reports of widespread biodiversity declines based on aggregated secondary data and expert opinion and suggest less extreme deterioration in tropical forest protected areas. We simultaneously fill an important conservation data gap and demonstrate the value of large-scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional sites, ecosystems, and monitoring methods. In an era of catastrophic biodiversity loss, robust indicators produced from standardized monitoring infrastructure are critical to accurately assess population outcomes and identify conservation strategies that can avert biodiversity collapse.

Interdisciplinary Decision Support Dashboard: A New Framework for a Tanzanian Agricultural and Ecosystem Service Monitoring System Pilot

Landscape degradation, soil depletion, scarcity of water and fuel resources are common threats to ecosystem services, agricultural production and human livelihoods in the developing world. Observatory or monitoring networks which focus on the dynamics of coupled human-natural systems are challenged by scarce data, data heterogeneity across multiple domains and spatial scales, and complex models required to produce meaningful sustainability indicators. An additional challenge is to visualize these complex data and indicators in a unified, easily understandable framework. This paper presents an environmental sustainability dashboard that integrates GIS data with household and plot surveys, field data and remote sensing imagery to compute a variety of metrics of ecosystem stress. The dashboard, a web-based decision support tool, is a key cyberinfrastructure component designed to satisfy the objectives of a Tanzanian agricultural and ecosystem services monitoring pilot. Based on this experience we discuss our framework and how it can be generalized for building decision support tools, and their associated cyberinfrastructure, for multi-scale, interdisciplinary monitoring networks.

An Open Standard for Camera Trap Data

Camera traps that capture photos of animals are a valuable tool for monitoring biodiversity. The use of camera traps is rapidly increasing and there is an urgent need for standardization to facilitate data management, reporting and data sharing. Here we offer the Camera Trap Metadata Standard as an open data standard for storing and sharing camera trap data, developed by experts from a variety of organizations. The standard captures information necessary to share data between projects and offers a foundation for collecting the more detailed data needed for advanced analysis. The data standard captures information about study design, the type of camera used, and the location and species names for all detections in a standardized way. This information is critical for accurately assessing results from individual camera trapping projects and for combining data from multiple studies for meta-analysis. This data standard is an important step in aligning camera trapping surveys with best practices in data-intensive science. Ecology is moving rapidly into the realm of big data, and central data repositories are becoming a critical tool and are emerging for camera trap data. This data standard will help researchers standardize data terms, align past data to new repositories, and provide a framework for utilizing data across repositories and research projects to advance animal ecology and conservation.

Cyberinfrastructure for Observatory and Monitoring Networks: A Case Study from the TEAM Network

Environmental-monitoring and observatory networks currently operating or under development at the national, regional, and global scales have the potential to provide an unprecedented understanding of our natural environment and the threats that endanger it. The breadth of these networks, as well as advances in technology (e.g., from mobile devices to in situ sensors and multidimensional satellite sensor data), will result in larger volumes of data and more complex data sets than ever before. All of these networks require robust cyberinfrastructure to support their varying mission, governance, operational, and scientific objectives. In this article, we use the Tropical Ecology Assessment and Monitoring (TEAM) Network as a fully functional environmental-monitoring network case study to highlight the key cyberinfrastructure components and services that support the network. We provide valuable lessons from our experience building the TEAM Network cyberinfrastructure and suggest future improvements that have broad applicability for other observatory and monitoring networks.

TEAM Network: Building Web-based Data Access and Analysis Environments for Ecosystem Services

A team of ecologists, computer scientists, and engineers from Conservation International (CI) and San Diego Supercomputer Center at the University of California San Diego (SDSC, UCSD) has been collaborating over the past 3 years to develop cyberinfrastructure for the TEAM (Tropical Ecology, Assessment and Monitoring) Network of tropical forest field sites. The TEAM project provides real-time data to understand how tropical forest ecosystems are being impacted by global climate change and land cover change and to improve conservation decisions. A major objective of this project is to provide information and services on tropical forest data disseminated by TEAM sites within countries participating in the TEAM network. The cyberinfrastructure provides a pervasive computational ecosystem, integrating grid computing infrastructure with highperformance backend resources, data warehouses, sophisticated client applications, new instruments, and embedded sensors, thus enabling a new paradigm for monitoring, understanding, and managing ecological and environmental systems. This paper presents the TEAM data management, access, and analysis system that provides end-to-end solutions for sensor-based data and field observations collected at TEAM sites. Specifically, two major applications are presented, viz., the “Data Query and Download Application (DQA)” application, which allows users to navigate and download diverse TEAM datasets such as Tree and Liana Biodiversity, Terrestrial Vertebrate, Climate and Forest Carbon data using a Google Maps based interface; and, the “Forest Carbon Calculator (FCC)” application, which calculates tree biomass using equations for forests with different precipitation regimes, thereby predicting relationships between tree biomass, tree diameter and wood density to estimate the amount of above ground carbon in the forests.

African Golden Cats, Citizen Science, and Serendipity: Tapping the Camera Trap Revolution

The use of camera traps for wildlife research and monitoring is increasing and this is yielding significant observations at an accelerating pace. Yet many potentially valuable observations are overlooked, misinterpreted or withheld. Using our first-ever images of a wild African golden cat (Caracal aurata) catching prey, we consider practical challenges and opportunities for more effective image management systems. In particular we highlight the benefits of online image archives and assessments.