Land degradation is reducing biodiversity and crop yields, and exacerbating the impacts of climate change, throughout the world. Monitoring land degradation is required to determine the effectiveness of land management and restoration practices, and to track progress toward reaching land degradation neutrality (LDN). It is also needed to target investments where they are most needed, and will have the greatest impact. The most useful indicators of land degradation vary among soils and climates. The United Nations Convention to Combat Desertification (UNCCD) selected three widely accepted land degradation indicators for LDN: land cover, net primary production (NPP) and soil carbon stocks. In addition to non-universal relevance, the use of these indicators has been limited by data availability, especially for carbon. This article presents an alternative monitoring framework based on the definition and ranking of states in a degradation hierarchy. Unique classifications can be defined for different regions and even different landscapes allowing, for example, perennial cropland to be ranked above a highly degraded grassland. The article concludes with an invitation to discuss the potential value of this approach and how it could be practically implemented at landscape to global scales. The ultimate objective is to support decision-making information at the local levels at which land degradation is addressed through improved management and restoration while providing the information necessary for reporting on progress toward meeting goals.

The world's rangelands and drylands are undergoing rapid change, and consequently are becoming more difficult to manage. Big data and digital technologies (digital tools) provide land managers with a means to understand and adaptively manage change. An assortment of tools-including standardized field ecosystem monitoring databases; web-accessible maps of vegetation change, production forecasts, and climate risk; sensor networks and virtual fencing; mobile applications to collect and access a variety of data; and new models, interpretive tools, and tool libraries-together provide unprecedented opportunities to detect and direct rangeland change. Accessibility to and manager trust in and knowledge of these tools, however, have failed to keep pace with technological advances. Collaborative adaptive management that involves multiple stakeholders and scientists who learn from management actions is ideally suited to capitalize on an integrated suite of digital tools. Embedding science professionals and experienced technology users in social networks can enhance peer-to-peer learning about digital tools and fulfill their considerable promise.

Wind and water erosion can severely impact natural resources and ecosystem services, making soil erosion management essential to sustaining agroecosystems. Land health assessment protocols, such as Interpreting Indicators of Rangeland Health (IIRH), provide valuable information to make decisions on managing soil erosion in vulnerable drylands. Using quantitative erosion models with land health assessments can further inform management decisions. For example, sediment transport estimates from the Aeolian EROsion (AERO) model and Rangeland Hydrology and Erosion Model (RHEM) can help in understanding the impacts of differences in soil and vegetation on wind and water erosion risk. In this article, we provide a conceptual basis for using AERO and RHEM to support IIRH assessments that are used extensively by managers across United States rangelands. We describe how using erosion models with IIRH can (1) improve understanding about potential erosion rates for different types of storm events; (2) support identifying areas at risk of erosion where erosion evidence is not (yet) significant; (3) increase land health assessment consistency by providing reproducible erosion indicators; (4) provide another line of evidence to support assessment conclusions about land health; and (5) improve understanding about potential erosion rates across ecologically similar sites and over time. Effectively using erosion models to support land health assessments will improve wind and water erosion management in drylands, thus helping to protect and restore these ecosystems.

Public land management agencies in the US are committed to using science‐informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

High-quality soil maps are urgently needed by diverse stakeholders, but errors in existing soil maps are often unknown, particularly in countries with limited soil surveys. To address this issue, we used field soil data to assess the accuracy of seven spatial soil databases (Digital Soil Map of the World, Namibian Soil and Terrain Digital Database, Soil and Terrain Database for Southern Africa, Harmonized World Soil Database, SoilGrids1km, SoilGrids250m, and World Inventory of Soil Property Estimates) using topsoil texture as an example soil property and Namibia as a case study area. In addition, we visually compared topsoil texture maps derived from these databases. We found that the maps showed the correct topsoil texture in only 13% to 42% of all test sites, with substantial confusion occurring among all texture categories, not just those in close proximity in the soil texture triangle. Visual comparisons of the maps moreover showed that the maps differ greatly with respect to the number, types, and spatial distribution of texture classes. The topsoil texture information provided by the maps is thus sufficiently inaccurate that it would result in significant errors in a number of applications, including irrigation system design and predictions of potential forage and crop productivity, water runoff, and soil erosion. Clearly, the use of these existing maps for policy- and decision-making is highly questionable and there is a critical need for better on-site estimates and soil map predictions. We propose that mobile apps, citizen science, and crowdsourcing can help meet this need.

Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.

Aeolian processes are fundamental to arid and semi-arid ecosystems, but modeling approaches are poorly developed for assessing impacts of management and environmental change on sediment transport rates over meaningful spatial and temporal scales. For model estimates to provide value, estimates of sediment flux that encapsulate intra-and inter-annual and spatial variability are needed. Further, it is important to quantify and communicate transparent estimates of model uncertainty to users. Here, we present a wind erosion and dust emission model parameterized for rangelands using a Generalized Likelihood Uncertainty Estimation framework. Modeled horizontal sediment flux was calibrated using data from five diverse grassland and shrubland sites from the USDA National Wind Erosion Research Network. Observations of wind speed, vegetation height, length of gaps between vegetation, and percent bare ground were used as model inputs. Horizontal sediment flux estimates from 10,000 independently selected parameter sets were compared to flux observations from 44 month-long collection periods to calculate a likelihood measure for each model. Results show good agreement for individual sampling periods across sites with few observations falling outside prediction bounds and a one-to-one relationship between median predictions and observations. Additionally, combined distributions of sediment flux estimates from all sample periods for a given site closely approximated the probability of observing a given flux at that site. These results suggest AERO effectively represents temporal variability in aeolian transport rates at rangeland sites and provides robust assessments suitable for assessing land health and better predicting changes in air quality and the impacts of land management activities.

Indicators of vegetation cover and structure are widely available for monitoring and managing rangeland wind erosion. Identifying which indicators are most appropriate for managers could improve wind erosion mitigation and restoration efforts. Vegetation cover directly protects the soil surface from erosive winds and reduces wind erosivity by extracting momentum from the air. The portion of the soil surface that is directly protected by vegetation is adequately described by fractional ground cover indicators. However, the aerodynamic sheltering effects of vegetation, which are more important for wind erosion than for water erosion, are not captured by these indicators. As wind erosion is a lateral process, the vertical structure and spatial distribution of vegetation are most important for controlling where, when, and how much wind erosion occurs on rangelands. These controlling factors can be described by indicators of the vegetation canopy gap size distribution and vegetation height, for which data are collected widely in the United States by standardized rangeland monitoring and assessment programs. In this paper we address why canopy gap size distribution and vegetation height are critical indicators of rangeland wind erosion and health. We review wind erosion processes to explain the physical role of these vegetation attributes. We then address the management implications including availability of data on the indicators on rangelands and needs to make the indicators and model estimates of wind erosion more accessible to the range management community.

Alternative states maintained by feedbacks are notoriously difficult, if not impossible, to reverse. Although positive interactions that modify soil conditions may have the greatest potential to alter self-reinforcing feedbacks, the conditions leading to these state change reversals have not been resolved. In a 9-yr study, we modified horizontal connectivity of resources by wind or water on different geomorphic surfaces in an attempt to alter plant-soil feedbacks and shift woody-plant-dominated states back toward perennial grass dominance. Modifying connectivity resulted in an increase in litter cover regardless of the vector of transport (wind, water) followed by an increase in perennial grass cover 2 yr later. Modifying connectivity was most effective on sandy soils where wind is the dominant vector, and least effective on gravelly soils on stable surfaces with low sediment movement by water. We found that grass cover was related to precipitation in the first 5 yr of our study, and plant-soil feedbacks developed following 6 yr of modified connectivity to overwhelm effects of precipitation on sandy, wind-blown soils. These feedbacks persisted through time under variable annual rainfall. On alluvial soils, either plant-soil feedbacks developed after 7 yr that were not persistent (active soils) or did not develop (stable soils). This novel approach has application to drylands globally where desertified lands have suffered losses in ecosystem services, and to other ecosystems where connectivity-mediated feedbacks modified at fine scales can be expected to impact plant recovery and state change reversals at larger scales, in particular for wind-impacted sites.

R angelands have garnered attention for their potential to store carbon (C) and have been included in France's 4 per 1,000 initiative ([Minasny et al. 2017][1]), methods for maintaining or increasing C in grassland soils ([American Carbon Registry 2013][2]; [Verified Carbon Standard 2017][3]), and

Humans and rangelands have a complex and intertwined history. Rangelands provide many goods and services to humans, and humans have altered rangelands through their activities. Land potential describes the capacity for production of ecosystem services utilizing the inherent properties, resistance, and resilience of a location. The alteration of land potential by humans has led to changes in how these landscapes function and the ecosystem services they provide. Understanding current and future human needs along with the history of a landscape allows for land potential to act as a filter for management decisions. By combining inherent properties of a site with resistance and resilience along with knowledge about past management activities, land potential can help managers identify not only limitations but also opportunities for investment of resources that are both ecologically and economically positive on the landscape.

Regular monitoring and evaluation of rangeland restoration outcomes is necessary for accountability, adaptive management throughout the restoration process, and informing future project design. Monitoring and evaluating outcomes can help restoration practitioners and land managers identify restoration successes and failures. Often information about differences in potential vegetation productivity in restored areas is not collected, but it can help to understand and predict these different outcomes. Here, we provide a novel decision-tree based framework for designing monitoring programs for restoration projects. We emphasize the need to collect land potential information to help evaluate and contextualize restoration outcomes. We then highlight a new mobile phone application that can be used to collect basic land potential information with minimal time and training requirements.

Wind erosion and blowing dust threaten food security, human health and ecosystem services across global drylands. Monitoring wind erosion is needed to inform management, with explicit monitoring objectives being critical for interpreting and translating monitoring information into management actions. Monitoring objectives should establish quantitative guidelines for determining the relationship of wind erosion indicators to management benchmarks that reflect tolerable erosion and dust production levels considering impacts to, for example, ecosystem processes, species, agricultural production systems and human well-being. Here we: 1) critically review indicators of wind erosion and blowing dust that are currently available to practitioners; and 2) describe approaches for establishing benchmarks to support wind erosion assessments and management. We find that while numerous indicators are available for monitoring wind erosion, only a subset have been used routinely and most monitoring efforts have focused on air quality impacts of dust. Indicators need to be related to the causal soil and vegetation controls in eroding areas to directly inform management. There is great potential to use regional standardized soil and vegetation monitoring datasets, remote sensing and models to provide new information on wind erosion across landscapes. We identify best practices for establishing benchmarks for these indicators based on experimental studies, mechanistic and empirical models, and distributions of indicator values obtained from monitoring data at historic or existing reference sites. The approaches to establishing benchmarks described here have enduring utility as monitoring technologies change and enable managers to evaluate co-benefits and potential trade-offs among ecosystem services as affected by wind erosion management.

Arid and semi-arid rangelands support a significant portion of the world's human population, as well as its biodiversity. These landscapes are threatened by degradation, through loss of vegetation, increasing spread of invasive or undesirable species, or both. Efforts to halt or reverse degradation exist, but lack of monitoring and reporting of restoration outcomes hampers efforts to replicate and upscale effective practices to other areas. This paper demonstrates how monitoring can inform future efforts through retrospective analysis of restoration projects on Acacia reficiens invaded rangelands in northern Kenya. A. reficiens has encroached into productive rangeland undermining both livestock production and endangered wildlife species conservation. Using a mobile phone application, LandPKS, we assessed 22 plots across 13 restoration sites in Westgate and Kalama conservancies in Northern Kenya that had been cleared of A. reficiens and reseeded with Cenchrus ciliaris. We found that these restoration treatments led to increases of more than 25% in overall ground cover, 34% in perennial grass cover, and 60% in standing herbaceous biomass. We therefore suggest that manual clearing of A. reficiens, when carried out in the late dry season and combined with both reseeding and prudent pre- and post-treatment seed and soil conservation practices, has the potential to provide an efficient and cost-effective solution to help reverse habitat losses. Our use of mobile phone applications allowed rapid assessment of restoration outcomes, and the resulting data are already being used to help design restoration projects on rangelands in northern Kenya.

The response hierarchy of "Avoid > reduce > reverse" is increasingly acknowledged as the best strategy for prioritizing actions designed to address land degradation at hectare to national scales. This hierarchy is based on the assumption that the economic return on investment (ROI) will usually be higher for actions that help avoid degradation than for those required to restore already degraded land. While a useful first step, the hierarchy fails to account for how differences in land potential, defined as its potential to sustainably generate ecosystem services, may affect the ROI of actions at each level of the response hierarchy. The objective of this paper is to present a strategy for improving ROI at the landscape scale and above by systematically applying a more holistic understanding of land potential to the identification and prioritization of land investments. This objective is addressed in three sections. The first section explains how the potential short- and long-term resistance and resilience of the land can be used together with its potential productivity to prioritize actions designed to avoid, reduce and reverse degradation. In the second section we explain how this prioritization can be further optimized based on an understanding of degradation risk as indicated by the land's potential to generate relatively high short-term profits under management systems that are likely to increase degradation, or result in degradation of restored land. This potential, and land managers' perception of it, depend on a wide variety of factors including markets, infrastructure, and access to technology. Together these first two sections provide a framework for increasing ROI, while reducing the risk of failure at hectare to national scales. In the final section we briefly describe the Land-Potential Knowledge System (LandPKS), a modular mobile app that makes it possible for virtually anyone with a smartphone to make the land potential determinations necessary to apply the framework described in the first two sections.

•Plant phenology—timing of seasonal life cycle events—is a primary control on ecosystem productivity.•Phenology data can be used to design better management systems by adjusting the timing of grazing or managed burns relative to growth stages of key species and planning restoration activities, such as targeted grazing.•Tower-mounted digital cameras (phenocams) provide a cost-effective way to collect data to capture phenology metrics for vegetation greenness.•Phenocam greenness values can provide canopy-level metrics in real time for a fraction of the cost of field observations and link field and satellite observations to reveal species contributions to greenness.

Desert ecosystems are primarily limited by water availability. Within a climatic regime, topography, soil characteristics, and vegetation are expected to determine how the combined effects of precipitation, temperature, and evaporative demand of the atmosphere shape the spatial and temporal patterns of water within the soil profile and across a landscape. To forecast how desert landscapes may respond to future dimatic conditions, it is imperative to improve our understanding of these ecohydrologic processes. Here, we report on 27 yr of monthly soil volumetric water content (VWC) measurements and associated soils data from a site in the northern Chihuahuan Desert of North America. The dataset includes VWC and soil properties measured to 3 m in depth across 15 locations that encompass a range of Chihuahuan Desert vegetation types. We use this unique dataset (1) to generate insights into general temporal and depth patterns in VWC, (2) to analyze how VWC corresponds to measures of climatic conditions, and (3) to qualitatively evaluate the relative importance of soils, topographic setting, and vegetation type in mediating temporal patterns in VWC. Analyses of this unique dataset emphasize the importance of soil and topographic setting in determining depth and temporal patterns in VWC across time. Results emphasize the episodic nature of deep wetting events in our study system-essentially limited to three large events over the 27-yr record driven primarily by wetter than normal winters. Comparison of soil water dynamics between mesquite shrub coppice dunes and interspace soils suggests the "island of fertility" concept does not extend to soil water. Median VWC was strongly coupled to climatic conditions over surprisingly long windows at most locations (6-18 months), suggesting that soil water at depth is decoupled from short climatic pulses. However, VWC dynamics and VWC-climate relationships varied among locations, depths, and seasons, with unexpected similarities in ecohydrologic dynamics observed among very different vegetation types (e.g., an eroded creosote shrubland and a playa grassland). These results further underscore the importance of ecohydrological investigations in these ecosystems, given forecasts for a warmer and more variable climate in deserts globally.

This editorial represents a clarion call for the aeolian research community to provide increased scientific input to the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Convention to Combat Desertification (UNCCD) and an invitation to apply for ISAR funding to organize a working group to support this engagement.