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The original version of this Article contained an error in the author affiliations. The affiliation of Martin Schütz with Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland was inadvertently omitted. Martin Schütz was incorrectly associated with Department of Forest Resources, University of Minnesota, Saint Paul, MN, US. This has now been corrected in both the PDF and HTML versions of the Article.

Este artículo contiene 14 páginas, 7 figuras., Reef Life Survey (RLS) provides a new model for ecological monitoring through training experienced recreational divers in underwater visual census methods to the level of skilled scientists. Detail produced is similar to that of programs with professional scientific teams, at low cost to allow global coverage. RLS differs from most other citizen science initiatives in its emphasis on rigorous training and data quality rather than open participation, selectively involving the most skilled and committed members. Volunteers participate primarily because they appreciate the close relationship with scientists, other divers, and managers, and see their efforts directly contributing to improved environmental outcomes. RLS works closely with Australian management agencies, scheduling annual events at core monitoring sites associated with 10 inshore marine protected areas Australiawide. Surveys of 12 offshore Australian Marine Parks (AMPs) are realized through 2–4 week voyages in a sailing catamaran crewed by volunteers. Across the AMP network, RLS surveys have quantified densities of fishes, mobile invertebrates, macroalgae and corals at 350 shallow coral reef sites (180 sites surveyed on two or more occasions), providing an understanding of (i) population changes amongst threatened species including sea snakes, (ii) responses of fish and invertebrate populations following fisheries closures, (iii) ecosystem-wide impacts of marine heat-waves, and (iv) the extent that AMPs spanning the network comprehensively encompass national coral reef biodiversity. This scientist/volunteer/manager collaboration could be greatly expanded globally (presently 3537 sites in 53 countries)., Reef Life Survey Foundation has been sustained through grants from the Ian Potter Foundation and Minderoo Foundation, reporting contracts from Parks Australia, and administrative and analytical support from the University of Tasmania. The RLS program was established through a grant to GJE through the former Commonwealth Environment Research Facilities Program. Analyses were supported by the Australian Research Council and the Marine Biodiversity Hub, a collaborative partnership supported through the Australian Government’s National Environmental Science Program. Additional advice and assistance have been provided by the Department for Environment and Water (South Australia), Department of Primary Industries, Parks, Water and Environment (Tasmania), Department of Primary Industries (New South Wales), Department of Biodiversity, Conservation and Attractions (Western Australia), and Parks Victoria. Data management and distribution is supported through the Integrated Marine Observing System.

Restricting human activities through Marine Protected Areas (MPAs) is assumed to create more resilient biological communities with a greater capacity to resist and recover following climate events. Here we review the evidence linking protection from local pressures (e.g., fishing and habitat destruction) with increased resilience. Despite strong theoretical underpinnings, studies have only rarely attributed resilience responses to the recovery of food webs and habitats, and increases in the diversity of communities and populations. When detected, resistance to ocean warming and recovery after extreme events in MPAs have small effect sizes against a backdrop of natural variability. By contrast, large die-offs are well described from MPAs following climate stress events. This may be in part because protection from one set of pressures or drivers (such as fishing) can select for species that are highly sensitive to others (such as warming), creating a ‘Protection Paradox’. Given that climate change is overwhelming the resilience capacity of marine ecosystems, the only primary solution is to reduce carbon emissions. High-quality monitoring data in both space and time can also identify emergent resilience signals that do exist, in combination with adequate reference data to quantify the initial system state. This knowledge will allow networks of diverse protected areas to incorporate spatial refugia against climate change, and identify resilient biological components of natural systems. Sufficient spatial replication further offers insurance against losses in any given MPA, and the possibility for many weak signals of resilience to accumulate.

Interactions among global change stressors and their effects at large scales are often proposed but seldom evaluated, in part due to lack of comprehensive, sufficiently long-term, and spatially-extensive datasets. Seagrasses, which provide nursery habitat, improve water quality, and constitute a globally-important carbon sink, are among the most vulnerable habitats on the planet. Here, we unite 31-years of high-resolution aerial monitoring and water quality data to elucidate the patterns and drivers of eelgrass (Zostera marina) abundance in Chesapeake Bay, USA, one of the largest and most valuable estuaries in the world, with an unparalleled history of regulatory efforts. We show that eelgrass cover has declined 29% in total since 1991, with wide-ranging and severe ecological and economic consequences. We go on to identify an interaction between decreasing water clarity and warming temperatures as the primary driver of this trend. Declining clarity has gradually reduced eelgrass over the past two decades, primarily in deeper beds where light is already limiting. In shallow beds, however, reduced visibility exacerbates the physiological stress of acute warming, leading to recent instances of decline approaching 80%. While degraded water quality has long been known to influence underwater grasses worldwide, we demonstrate a clear and rapidly emerging interaction with climate change. We highlight the urgent need to integrate a broader perspective into local water quality management, in the Chesapeake Bay and in the many other coastal systems facing similar stressors.

Ecologists and evolutionary biologists are relying on an increasingly sophisticated set of statistical tools to describe complex natural systems. One such tool that has gained increasing traction in the life sciences is structural equation modeling (SEM), a variant of path analysis that resolves complex multivariate relationships among a suite of interrelated variables. SEM has historically relied on covariances among variables, rather than the values of the data points themselves. While this approach permits a wide variety of model forms, it limits the incorporation of detailed specifications. Here, I present a fully-documented, open-source R package piecewiseSEM that builds on the base R syntax for all current generalized linear, least-square, and mixed effects models. I also provide two worked examples: one involving a hierarchical dataset with non-normally distributed variables, and a second involving phylogenetically-independent contrasts. My goal is to provide a user-friendly and tractable implementation of SEM that also reflects the ecological and methodological processes generating data., Comment: 20 pages, 2 figures

Incorporating natural complexity into BEF research is a key challenge in ecology. Energy flux dynamics in networks underpin BEF theory in multitrophic systems. Network energetics define stability and functions across ecological scales, allowing for the expansion of BEF research to complex systems. We propose future directions for integrating network energy fluxes into BEF research. Relating biodiversity to ecosystem functioning in natural communities has become a paramount challenge as links between trophic complexity and multiple ecosystem functions become increasingly apparent. Yet, there is still no generalised approach to address such complexity in biodiversity–ecosystem functioning (BEF) studies. Energy flux dynamics in ecological networks provide the theoretical underpinning of multitrophic BEF relationships. Accordingly, we propose the quantification of energy fluxes in food webs as a powerful, universal tool for understanding ecosystem functioning in multitrophic systems spanning different ecological scales. Although the concept of energy flux in food webs is not novel, its application to BEF research remains virtually untapped, providing a framework to foster new discoveries into the determinants of ecosystem functioning in complex systems.