Spatial Imaging and Screening for Regime Shifts

Abstract

Screening is a strategy for detecting undesirable change prior to manifestation of symptoms or adverse effects. Although the well-recognized utility of screening makes it commonplace in medicine, it has yet to be implemented in ecosystem management. Ecosystem management is in an era of diagnosis and treatment of undesirable change, and as a result, remains more reactive than proactive and unable to effectively deal with today's plethora of non-stationary conditions. In this paper, we introduce spatial imaging-based screening to ecology. We link advancements in spatial resilience theory, data, and technological and computational capabilities and power to detect regime shifts (i.e., vegetation state transitions) that are known to be detrimental to human well-being and ecosystem service delivery. With a state-of-the-art landcover dataset and freely available, cloud-based, geospatial computing platform, we screen for spatial signals of the three most iconic vegetation transitions studied in western USA rangelands: (1) erosion and desertification; (2) woody encroachment; and (3) annual exotic grass invasion. For a series of locations that differ in ecological complexity and geographic extent, we answer the following questions: (1) Which regime shift is expected or of greatest concern? (2) Can we detect a signal associated with the expected regime shift? (3) If detected, is the signal transient or persistent over time? (4) If detected and persistent, is the transition signal stationary or non-stationary over time? (5) What other signals do we detect? Our approach reveals a powerful and flexible methodology, whereby professionals can use spatial imaging to verify the occurrence of alternative vegetation regimes, image the spatial boundaries separating regimes, track the magnitude and direction of regime shift signals, differentiate persistent and stationary transition signals that warrant continued screening from more concerning persistent and non-stationary transition signals, and leverage disciplinary strength and resources for more targeted diagnostic testing (e.g., inventory and monitoring) and treatment (e.g., management) of regime shifts. While the rapid screening approach used here can continue to be implemented and refined for rangelands, it has broader implications and can be adapted to other ecological systems to revolutionize the information space needed to better manage critical transitions in nature.

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

“…The fractional cover of functional groups and cover types in rangelands reflect numerous ecosystem processes and ecosystem services. Changes in one functional group has predictable ecological impacts on other groups and the services they provide (Uden et al, 2019). For example, woody plant encroachment into grasslands constrains herbaceous grass cover and diminishes forage production and wildlife habitat (Archer et al, 2017), whereas annual grass invasion reduces perennial herbaceous plants and shrubs (Davies, 2008).…”

Resilience to Large, “Catastrophic” Wildfires in North America's Grassland Biome

“…For instance, the NASA Soil Moisture Active Passive and European Space Agency Soil Moisture Ocean Salinity instrument provides soil moisture estimates but with relatively low‐spatial resolution (~25 km). That said, new remotely sensed observations, ecological transition identification methods (Uden et al, 2019), and increasingly fine‐scale, large‐extent remotely sensed information (Jones et al, 2018) continue to advance our ability to study large‐scale ecosystem complexity and can build upon the initial exploration of the 1,390 wildfires analyzed in this study.…”

Panarchy: opportunities and challenges for ecosystem management

“…The colors in (a) correspond to the colors and associated values in (b). New data products are now available that better capture changes in woody plant abundance over time, and further confirm the vulnerability of the region to further grassland displacement and tree expansion (Jones et al 2018;Uden et al 2019). kirtlandii] after it was discovered that the bird species depends on periodic fires in its breeding areas), the reliance on chemical or mechanical techniques to target emergent "weed" species and to serve as a replacement for historical disturbances (irrespective of native or non-native status), and the use of reseeding techniques to accelerate ecological succession and restore idealized critical functionality back to a high-biomass condition.…”

“…For example, there is a need to link laws and policies to quantitative measures of system condition (Garmestani and Allen 2014). Several approaches appear promising in this respect for improving ecosystem management, as they are based on a systems perspective; these include discontinuity analysis (Nash et al 2014), multivariate timeseries modeling (Angeler et al 2011), spatial analysis for early warning indicators (Roberts et al 2019), and advanced screening techniques for regime shift detection (Uden et al 2019).…”

“…2019), and advanced screening techniques for regime shift detection (Uden et al . 2019). Further application of such methods may provide additional insight into how coupled systems of humans and nature function, and how to better manage them (Soranno et al .…”