Explore the vast range of titles available.

International agreements aim to conserve 17% of Earth's land area by 2020 but include no area‐based conservation targets within the working landscapes that support human needs through farming, ranching, and forestry. Through a review of country‐level legislation, we found that just 38% of countries have minimum area requirements for conserving native habitats within working landscapes. We argue for increasing native habitats to at least 20% of working landscape area where it is below this minimum. Such target has benefits for food security, nature's contributions to people, and the connectivity and effectiveness of protected area networks in biomes in which protected areas are underrepresented. We also argue for maintaining native habitat at higher levels where it currently exceeds the 20% minimum, and performed a literature review that shows that even more than 50% native habitat restoration is needed in particular landscapes. The post‐2020 Global Biodiversity Framework is an opportune moment to include a minimum habitat restoration target for working landscapes that contributes to, but does not compete with, initiatives for expanding protected areas, the UN Decade on Ecosystem Restoration (2021–2030) and the UN Sustainable Development Goals.

Many decision-makers are looking to science to clarify how nature supports human well-being. Scientists’ responses have typically focused on empirical models of the provision of ecosystem services (ES) and resulting decision-support tools. Although such tools have captured some of the complexities of ES, they can be difficult to adapt to new situations. Globally useful tools that predict the provision of multiple ES under different decision scenarios have proven challenging to develop. Questions from decision-makers and limitations of existing decision-support tools indicate three crucial research frontiers for incorporating cutting-edge ES science into decision-support tools: (1) understanding the complex dynamics of ES in space and time, (2) linking ES provision to human well-being, and (3) determining the potential for technology to substitute for or enhance ES. We explore these frontiers in-depth, explaining why each is important and how existing knowledge at their cutting edges can be incorporated to improve ES decision-making tools.

Restoring native grassland vegetation can substantially improve ecosystem service outcomes from agricultural watersheds, but profitable pathways are needed to incentivize conversion from conventional crops. Given growing demand for renewable energy, using grassy biomass to produce biofuels provides a potential solution. We assessed the techno‐economic feasibility and life cycle outcomes of a “grass‐to‐gas” pathway that includes harvesting grassy (lignocellulosic) biomass for renewable natural gas (RNG) production through anaerobic digestion (AD), expanding on previous research that quantified ecosystem service and landowner financial outcomes of simulated grassland restoration in the Grand River Basin of Iowa and Missouri, United States. We found that the amount of RNG produced through AD of grassy biomass ranged 0.12–45.04 million gigajoules (GJ), and the net present value (NPV) of the RNG ranged − $97 to $ 422 million, depending on the combination of land use, productivity, and environmental credit scenarios. Positive NPVs are achieved with environmental credits for replacement of synthetic agricultural inputs with digestate and clean fuel production (e.g., USEPA D3 Renewable Identification Number, California Low Carbon Fuel Standard). Producing RNG from grassy biomass emits 15.1 g CO2‐eq/MJ, which compares favorably to the fossil natural gas value of 61.1 g CO2‐eq/MJ and exceeds the US Environmental Protection Agency's requirement for cellulosic biofuel. Overall, this study demonstrates opportunities and limitations to using grassy biomass from restored grasslands for sustainable RNG production. Restoring native grasslands in agricultural watersheds can enhance ecosystem services and offer profitable routes for biomass use in renewable natural gas (RNG) production. Our study assessed the techno‐economic and life cycle impacts of converting grassy biomass to RNG via anaerobic digestion, observing RNG outputs between 0.12 and 45.04 million gigajoules. Economic viability, based on a net present value ranging from − $97 to $ 422 million, relies on environmental credits. RNG production from this pathway emits significantly lower CO2 compared to fossil fuels, meeting stringent EPA standards for cellulosic biofuels, and showcasing the sustainable potential and challenges of this approach.

Process-based agroecosystem models are powerful tools to assess performance of managed landscapes, but their ability to accurately represent reality is limited by the types of input data they can use. Ensuring these models can represent cropping field heterogeneity and environmental impact is important, especially given the growing interest in using agroecosystem models to quantify ecosystem services from best management practices and land use change. We posited that augmenting process-based agroecosystem models with additional field-specific information such as topography, hydrologic processes, or independent indicators of yield could help limit simulation artifacts that obscure mechanisms driving observed variations. To test this, we augmented the agroecosystem model Agricultural Production Systems Simulator (APSIM) with field-specific topography and satellite imagery in a simulation framework we call Foresite. We used Foresite to optimize APSIM yield predictions to match those created from a machine learning model built on remotely sensed indicators of hydrology and plant productivity. Using these improved subfield yield predictions to guide APSIM optimization, total N O 3 − N loss estimates increased by 39% in maize and 20% in soybeans when summed across all years. In addition, we found a disproportionate total amount of leaching in the lowest yielding field areas vs the highest yielding areas in maize (42% vs 15%) and a similar effect in soybeans (31% vs 20%). Overall, we found that augmenting process-based models with now-common subfield remotely sensed data significantly increased values of predicted nutrient loss from fields, indicating opportunities to improve field-scale agroecosystem simulations, particularly if used to calculate nutrient credits in ecosystem service markets.

The agricultural conservation practice of prairie strips is new and novel. Prairie strips planted in row crop fields warrants greater adoption because the application decreases erosion; protects water quality; and supports habitat for wildlife and biodiversity, including pollinators. Prairie strips are a vegetative practice composed of diverse, native, and mostly perennial species that, as a community, follow principles of ecological succession; however, they must be managed for success. Farm advisor comprehension of practice characteristics is key for adoption by producers and landowners. This article reports on a developmental evaluation of workshops intended to change farm advisor knowledge, skills, and confidence related to prairie strips management for use in consulting with farmers and landowners. The study used pre-post instruments of knowledge and skill focused on prairie species identification and age of prairie strips planing; pre-then post-end of session questions were asked in a survey to report change in knowledge, skill, and confidence, as well as farm advisor situation. Advisors reported increased confidence, but acquisition of prairie knowledge and skills resulted in flat to lower scores. The paper explores the discrepancy of lower cognitive scores (knowledge and skills) compared to higher confidence. Explanations explore the phenomena of satisficing and perceived self-efficacy to explain the differential.

Cover crops (CCs) can reduce nitrogen (N) loss to subsurface drainage and can be reimagined as bioenergy crops for renewable natural gas production and carbon (C) benefits (fossil fuel substitution and C storage). Little information is available on the large-scale adoption of winter rye for these purposes. To investigate the impacts in the North Central US, we used the Root Zone Water Quality Model to simulate corn-soybean rotations with and without winter rye across 40 sites. The simulations were interpolated across a five-state area (IA, IL, IN, MN, and OH) with counties in the Mississippi River basin, which consists of ∼8 million ha with potential for rye CCs on artificially drained corn-soybean fields (more than 63 million ha total). Harvesting fertilized rye CCs before soybean planting in this area can reduce N loads to the Gulf of Mexico by 27% relative to no CCs, and provide 18 million Mg yr −1 of biomass-equivalent to 0.21 EJ yr −1 of biogas energy content or 3.5 times the 2022 US cellulosic biofuel production. Capturing the CO 2 in biogas from digesting rye in the region and sequestering it in underground geologic reservoirs could mitigate 7.5 million Mg CO 2 yr −1 . Nine clusters of counties (hotspots) were identified as an example of implementing rye as an energy CC on an industrial scale where 400 Gg yr −1 of rye could be sourced within a 121 km radius. Hotspots consisted of roughly 20% of the region’s area and could provide ∼50% of both the N loss reduction and rye biomass. These results suggest that large-scale energy CC adoption would substantially contribute to the goals of reducing N loads to the Gulf of Mexico, increasing bioenergy production, and providing C benefits.

The restoration of soil organic matter (SOM, as measured by soil organic carbon (SOC)) within the world’s agricultural soils is imperative to sustaining crop production and restoring other ecosystem services. We compiled long-term studies on the effect of management practices on SOC from Iowa, USA—an agricultural region with relatively high-quality soil data—to highlight constraints on detecting changes in SOC and inform research needed to improve SOC measurement and management. We found that strip-tillage and no-tillage increased SOC by 0.25–0.43 Mg C ha−1 yr−1 compared to losses of 0.24 to 0.46 Mg C ha−1 yr−1 with more intensive tillage methods. The conversion of cropland to perennial grassland increased SOC by 0.21–0.74 Mg C ha−1 yr−1. However, diversifying crop rotations with extended rotations, and supplementing synthetic fertilizer with animal manure, had highly variable and inconsistent effects on SOC. The improved prediction of changes in SOC requires: the use of methods that can identify and disentangle multiple sources of variability; looking beyond total SOC and toward systematic collection of data on more responsive and functionally relevant fractions; whole-profile SOC monitoring; monitoring SOC in long-term studies on the effect of multiple conservation practices used in combination; and deeper collaboration between field soil scientists and modelers.

Successful modeling of the carbon (C) cycle requires empirical data regarding species‐specific root responses to edaphic characteristics. We address this need by quantifying annual root production of three bioenergy systems (continuous corn, triticale/sorghum, switchgrass) in response to variation in soil properties across a toposequence within a Midwestern agroecosystem. Using ingrowth cores to measure annual root production, we tested for the effects of topography and 11 soil characteristics on root productivity. Root production significantly differed among cropping systems. Switchgrass root productivity was lowest on the floodplain position, but root productivity of annual crops was not influenced by topography or soil properties. Greater switchgrass root production was associated with high percent sand, which explained 45% of the variation. Percent sand was correlated negatively with soil C and nitrogen and positively with bulk density, indicating this variable is a proxy for multiple important soil properties. Our results suggest that easily measured soil parameters can be used to improve model predictions of root productivity in bioenergy switchgrass, but the edaphic factors we measured were not useful for predicting root productivity in annual crops. These results can improve C cycling modeling efforts by revealing the influence of cropping system and soil properties on root productivity.

Loss of biodiversity and degradation of ecosystem services from agricultural lands remain important challenges in the United States despite decades of spending on natural resource management. To date, conservation investment has emphasized engineering practices or vegetative strategies centered on monocultural plantings of nonnative plants, largely excluding native species from cropland. In a catchment-scale experiment, we quantified the multiple effects of integrating strips of native prairie species amid corn and soybean crops, with prairie strips arranged to arrest run-off on slopes. Replacing 10% of cropland with prairie strips increased biodiversity and ecosystem services with minimal impacts on crop production. Compared with catchments containing only crops, integrating prairie strips into cropland led to greater catchment-level insect taxa richness (2.6-fold), pollinator abundance (3.5-fold), native bird species richness (2.1-fold), and abundance of bird species of greatest conservation need (2.1-fold). Use of prairie strips also reduced total water runoff from catchments by 37%, resulting in retention of 20 times more soil and 4.3 times more phosphorus. Corn and soybean yields for catchments with prairie strips decreased only by the amount of the area taken out of crop production. Social survey results indicated demand among both farming and nonfarming populations for the environmental outcomes produced by prairie strips. If federal and state policies were aligned to promote prairie strips, the practice would be applicable to 3.9 million ha of cropland in Iowa alone.

The US Cornbelt leads North American production of intensively managed, row-crop corn and soybeans. While highly productive, agricultural management in the region is often linked with nonpoint source nutrient pollution that negatively impacts water quality. Presently, conservation programs designed to install best management practices (BMPs) to mitigate agricultural nonpoint source pollution have not been targeted to those areas of the landscape that contribute disproportionately to surface water quality concerns. We used an innovative spatially targeted conservation protocol coupled with a GIS-based landscape planning tool to evaluate the cost and effect on water quality from nitrate-nitrogen loss under alternative landscape scenarios in an Iowa watershed. Outputs indicate large reductions in watershed-level nitrate-nitrogen loss could be achieved through coordinated placement of BMPs on high-contributing parcels with limited reduction of cultivated land, resulting in improved surface water quality at relatively low economic costs. For example, one scenario, which added wetlands, cover crops, and saturated buffers in the watershed, required the removal of <5% of cultivated area to reduce nitrate-nitrogen loss by an estimated 49%, exceeding the Iowa Nutrient Reduction Strategy goal for enhancing water quality. Annualized establishment and management costs of landscape scenarios that met the nonpoint source nitrogen reduction goal varied from $3.16 to $3.19 million (2017 US dollars). These results support our hypothesis that water quality can be improved by targeting high-contributing parcels, and highlights the potential to minimize tradeoffs by coupling targeted conservation and planning tools to help stakeholders achieve water quality outcomes within agricultural landscapes.