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Assessment of socio-environmental problems and the search for solutions often require intersecting geospatial data on environmental factors and human population densities. In the United States, Census data is the most common source for information on population. However, timely acquisition of such data at sufficient spatial resolution can be problematic, especially in cases where the analysis area spans urban-rural gradients. With this data release, we provide a 30-m resolution population estimate for the contiguous United States. The workflow dasymetrically distributes Census block level population estimates across all non-transportation impervious surfaces within each Census block. The methodology is updatable using the most recent Census data and remote sensing-based observations of impervious surface area. The dataset, known as the U.G.L.I (updatable gridded lightweight impervious) population dataset, compares favorably against other population data sources, and provides a useful balance between resolution and complexity.

 

Diet shifts and food waste reduction have the potential to reduce the land and biodiversity footprint of the food system. In this study, we estimated the amount of land used to produce food consumed in the United States and the number of species threatened with extinction as a result of that land use. We predicted potential changes to the biodiversity threat under scenarios of food waste reduction and shifts to recommended healthy and sustainable diets. Domestically produced beef and dairy, which require vast land areas, and imported fruit, which has an intense impact on biodiversity per unit land, have especially high biodiversity footprints. Adopting the Planetary Health diet or the US Department of Agriculture (USDA)–recommended vegetarian diet nationwide would reduce the biodiversity footprint of food consumption. However, increases in the consumption of foods grown in global biodiversity hotspots both inside and outside the United States, especially fruits and vegetables, would partially offset the reduction. In contrast, the USDA-recommended US-style and Mediterranean-style diets would increase the biodiversity threat due to increased consumption of dairy and farmed fish. Simply halving food waste would benefit global biodiversity more than half as much as all Americans simultaneously shifting to a sustainable diet. Combining food waste reduction with the adoption of a sustainable diet could reduce the biodiversity footprint of US food consumption by roughly half. Species facing extinction because of unsustainable food consumption practices could be rescued by reducing agriculture's footprint; diet shifts and food waste reduction can help us get there. 

While many instructors have reservations against Wikipedia use in academic settings, editing Wikipedia teaches students valuable writing, editing, and critical thinking skills. Wikipedia assignments align with the community of inquiry framework, which focuses on the elements needed for a successful online learning experience. We report on a faculty mentoring network, created by WikiProject Limnology and Oceanography, which helped 14 instructors with little to no prior experience implement a Wikipedia assignment in their classes. We found that Wikipedia assignments increase students’ motivation to produce high quality work and enhance their awareness of reliable scientific sources. Wikipedia assignments can be comparable to other writing assignments in length and complexity, but have a far wider audience than a traditional research paper. Participants in our mentoring network reported challenges with implementing this new type of assignment, and here, we share resources and solutions to those reported barriers. 

Ponds are often identified by their small size and shallow depths, but the lack of a universal evidence-based definition hampers science and weakens legal protection. Here, we compile existing pond definitions, compare ecosystem metrics (e.g., metabolism, nutrient concentrations, and gas fluxes) among ponds, wetlands, and lakes, and propose an evidence-based pond definition. Compiled definitions often mentioned surface area and depth, but were largely qualitative and variable. Government legislation rarely defined ponds, despite commonly using the term. Ponds, as defined in published studies, varied in origin and hydroperiod and were often distinct from lakes and wetlands in water chemistry. We also compared how ecosystem metrics related to three variables often seen in waterbody definitions: waterbody size, maximum depth, and emergent vegetation cover. Most ecosystem metrics (e.g., water chemistry, gas fluxes, and metabolism) exhibited nonlinear relationships with these variables, with average threshold changes at 3.7 ± 1.8 ha (median: 1.5 ha) in surface area, 5.8 ± 2.5 m (median: 5.2 m) in depth, and 13.4 ± 6.3% (median: 8.2%) emergent vegetation cover. We use this evidence and prior definitions to define ponds as waterbodies that are small (< 5 ha), shallow (< 5 m), with < 30% emergent vegetation and we highlight areas for further study near these boundaries. This definition will inform the science, policy, and management of globally abundant and ecologically significant pond ecosystems.

 

A major source of uncertainty in the global methane budget arises from quantifying the area of wetlands and other inland waters. This study addresses how the dynamics of surface water extent in forested wetlands affect the calculation of methane emissions. We used fine resolution satellite imagery acquired at sub‐weekly intervals together with a semiempirical methane emissions model to estimate daily surface water extent and diffusive methane fluxes for a low‐relief wetland‐rich watershed. Comparisons of surface water model predictions to field measurements showed agreement with the magnitude of changes in water extent, including for wetlands with surface area less than 1,000 m². Results of methane emission models showed that wetlands smaller than 1 hectare (10,000 m²) were responsible for a majority of emissions, and that considering dynamic inundation of forested wetlands resulted in 49%–62% lower emission totals compared to models using a single estimate for each wetland’s size.

 

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. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building.