1. Anthropogenic stressors affect the ecosystems upon which humanity relies. In some cases when resilience is exceeded, relatively small linear changes in stressors can cause relatively abrupt and nonlinear changes in ecosystems. 2. Ecological regime shifts occur when resilience is exceeded and ecosystems enter a new local equilibrium that differs in its structure and function from the previous state. Ecological resilience, the amount of disturbance that a system can withstand before it shifts into an alternative stability domain, is an important framework for understanding and managing ecological systems subject to collapse and reorganization. 3. Recently, interest in the influence of spatial characteristics of landscapes on resilience has increased. Understanding how spatial structure and variation in relevant variables in landscapes affects resilience to disturbance will assist with resilience quantification, and with local and regional management. 4. Synthesis and applications. We review the history and current status of spatial resilience in the research literature, expand upon existing literature to develop a more operational definition of spatial resilience, introduce additional elements of a spatial analytical approach to understanding resilience, present a framework for resilience operationalization and provide an overview of critical knowledge and technology gaps that should be addressed for the advancement of spatial resilience theory and its applications to management and conservation.

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Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform ( https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species' geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species-which may not be at equilibrium within recipient environments and often exhibit rapid transformations-are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Abstract. Ecological reserves provide important wildlife habitat in many landscapes, and the functional connectivity of reserves and other suitable habitat patches is crucial for the persistence and resilience of spatially structured populations. To maintain or increase connectivity at spatial scales larger than individual patches, conservation actions may focus on creating and maintaining reserves and/or influencing management on non-reserves. Using a graph-theoretic approach, we assessed the functional connectivity and spatial distribution of wetlands in the Rainwater Basin of Nebraska, USA, an intensively cultivated agricultural matrix, at four assumed, but ecologically realistic, anuran dispersal distances. We compared connectivity in the current landscape to the historical landscape and putative future landscapes, and evaluated the importance of individual and aggregated reserve and non-reserve wetlands for maintaining connectivity. Connectivity was greatest in the historical landscape, where wetlands were also the most densely distributed. The construction of irrigation reuse pits for water storage has maintained connectivity in the current landscape by replacing destroyed wetlands, but these pits likely provide suboptimal habitat. Also, because there are fewer total wetlands (i.e., wetlands and irrigation reuse pits) in the current landscape than the historical landscape, and because the distribution of current wetlands is less clustered than that of historical wetlands, larger and longer dispersing, sometimes nonnative species may be favored over smaller, shorter dispersing species of conservation concern. Because of their relatively low number, wetland reserves do not affect connectivity as greatly as non-reserve wetlands or irrigation reuse pits; however, they likely provide the highest quality anuran habitat. To improve future levels of resilience in this wetland habitat network, management could focus on continuing to improve the conservation status of non-reserve wetlands, restoring wetlands at spatial scales that promote movements of shorter dispersing species, and further scrutinizing irrigation reuse pit removal by considering effects on functional connectivity for anurans, an emblematic and threatened group of organisms. However, broader conservation plans will need to give consideration to other wetland-dependent species, incorporate invasive species management, and address additional challenges arising from global change in social-ecological systems like the Rainwater Basin.