In a changing climate, there is an imperative to build coupled social-ecological systems—including fisheries—that can withstand or adapt to climate stressors. Although resilience theory identifies system attributes that supposedly confer resilience, these attributes have rarely been clearly defined, mechanistically explained, nor tested and applied to inform fisheries governance.
It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed.
Data availability challenges the management of small-scale fisheries in large river basins. One way to circumvent the challenges of data collection is to rely on local stakeholders who are well-positioned to collect data that can inform management through community-based monitoring (CBM). Although science and management has increasingly considered opportunities for community involvement in scientific research, the efficacy of these programs are rarely assessed. We describe a current CBM initiative in the Kuskokwim River Basin of western Alaska.
Coastal marine ecosystems face a host of pressures from both offshore and land-based human activity. Research on terrestrial threats to coastal ecosystems has primarily focused on agricultural runoff, specifically showcasing how fertilizers and livestock waste create coastal eutrophication, harmful algae blooms, or hypoxic or anoxic zones. These impacts not only harm coastal species and ecosystems but also impact human health and economic activities. Few studies have assessed impacts of human wastewater on coastal ecosystems and community health.
1. Spatiotemporal variation in predation risk arises from interactions between land-scape heterogeneity, predator densities and predator hunting mode, generating landscapes of fear for prey species that can have important effects on prey behav-iour and ecosystem dynamics. 2. As widespread apex predators, humans present a significant source of risk for hunted animal populations. Spatiotemporal patterns of risk from hunters can overlap or contrast with patterns of risk from other predators.
With rapid global change, the frequency and severity of extreme disturbance events are increasing worldwide. The ability of animal populations to survive these stochastic events depends on how individual animals respond to their altered environments, yet our understanding of the immediate and short-term behavioral responses of animals to acute disturbances remains poor. We focused on animal behavioral responses to the environmental disturbance created by megafire.
Camera trapping is increasingly being used to monitor wildlife, but this technology typically requires extensive data annotation. Recently, deep learning has substantially advanced automatic wildlife recognition. However, current methods are hampered by a dependence on large static datasets, whereas wildlife data are intrinsically dynamic and involve long-tailed distributions. These drawbacks can be overcome through a hybrid combination of machine learning and humans in the loop.
Schistosome parasites infect more than 200 million people annually, mostly in sub-Saharan Africa, where people may be co-infected with more than one species of the parasite. Infection risk for any single species is determined, in part, by the distribution of its obligate intermediate host snail. As the World Health Organization reprioritizes snail control to reduce the global burden of schistosomiasis, there is renewed importance in knowing when and where to target those efforts, which could vary by schistosome species.
Small-scale fisheries and aquaculture (SSFA) provide livelihoods for over 100 million people and sustenance for ~1 billion people, particularly in the Global South. Aquatic foods are distributed through diverse supply chains, with the potential to be highly adaptable to stresses and shocks, but face a growing range of threats and adaptive challenges. Contemporary governance assumes homogeneity in SSFA despite the diverse nature of this sector.
Background The ecosystem classification of land (ECL) has been studied for a couple of decades, from the beginning of the perfect organism system “top-down†approach to a reversed “bottom-up†approach by defining a micro-ecological unit. After comparing two cases of the ecosystem classification framework implemented in the different continental ecoregions, the processes were carefully examined and justified. Results Theoretically, Bailey’s upper levels of ECL (Description of the ecoregions of the United States, 2nd ed. Rev and expanded (1st ed. 1980). Misc. Publ. No.