Remotely sensed albedo allows the identification of two ecosystem states along aridity gradients in Africa

Abstract

Empirical verification of multiple states in drylands is scarce, impeding the design of indicators to anticipate the onset of desertification. Remote sensing‐derived indicators of ecosystem states are gaining new ground due to the possibilities they bring to be applied inexpensively over large areas. Remotely sensed albedo has been often used to monitor drylands due to its close relationship with ecosystem status and climate. Here, we used a space‐for‐time‐substitution approach to evaluate whether albedo (averaged from 2000 to 2016) can identify multiple ecosystem states in African drylands spanning from the Saharan desert to tropical Africa. By using latent class analysis, we found that albedo showed two states (low and high; the cut‐off level was 0.22 at the shortwave band). Potential analysis revealed that albedo exhibited an abrupt and discontinuous increase with increased aridity (1 − [precipitation/potential evapotranspiration]). The two albedo states co‐occurred along aridity values ranging from 0.72 to 0.78, during which vegetation cover exhibited a rapid, continuous decrease from ~90% to ~50%. At aridity values of 0.75, the low albedo state started to exhibit less attraction than the high albedo state. Low albedo areas beyond this aridity value were considered as vulnerable regions where abrupt shifts in albedo may occur if aridity increases, as forecasted by current climate change models. Our findings indicate that remotely sensed albedo can identify two ecosystem states in African drylands. They support the suitability of albedo indices to inform us about discontinuous responses to aridity experienced by drylands, which can be linked to the onset of land degradation.

Remotely-Sensed Identification of a Transition for the Two Ecosystem States Along the Elevation Gradient: A Case Study of Xinjiang Tianshan Bogda World Heritage Site

“…However, above the ending elevation, there were mainly alpine meadows and a few shrubs ( Figure 14). In addition, the albedo of the shrubs is higher than that of the alpine meadows but lower than that of the coniferous forests [76,86], and this may explain why the albedo states can show such a trend in Figure 12. Therefore, elevation is a key factor in the altitudinal structure of vegetation in mountainous ecosystems [29].…”

“…In addition, ecosystems can be regarded as composed of multiple state modes, and each mode tends to present the most similar one with the adjacent state. Thus, when different state variables vary abruptly and exhibit an area of coexistence along the environmental gradient, a critical transition may occur between these states [29,76]. Potential analysis is a technique, which is used to establish a link between environmental gradients and state variables.…”

“…The bandwidth that controls the smoothness of the estimator is calculated as 1.06s/n 1/5 (s and n are the standard deviation and the length of the data set, respectively; see References [69,76,77]). The abrupt nature of a shift in LST states along the elevation gradient was studied by tracking the local minimum potential energy (local minimum potential energy correspond to the different states [69,76,77,79]). In the ascending order of elevation, using the moving window (the window size was 100 [76]) to calculate the potential energy and local minimum for each iteration.…”

“…The abrupt nature of a shift in LST states along the elevation gradient was studied by tracking the local minimum potential energy (local minimum potential energy correspond to the different states [69,76,77,79]). In the ascending order of elevation, using the moving window (the window size was 100 [76]) to calculate the potential energy and local minimum for each iteration. Then, the potential energy and the number of states shift with increasing elevation were depicted by mapping the variation of LST along elevation gradients.…”

Aridity Thresholds Determine the Relationships Between Ecosystem Functioning and Remotely Sensed Indicators Across Patagonia

“…Remotely sensed vegetation indices (VIs), such as the normalized difference vegetation index (NDVI), have been used to monitor ecosystem functioning in drylands worldwide at multiple scales, from local [20]- [22] to regional [23]- [25] and global [26], [27] scales. Remotely sensed albedo (defined as the ratio of upwelling to downwelling radiative flux at the surface) is another commonly used indicator to monitor dryland degradation due to its close relationship with land surface changes [28]- [32]. Zhao et al [26] found significant correlations between broadband albedo metrics and ecosystem multifunctionality (i.e., a proxy of the capacity of the ecosystem to provide multiple functions simultaneously) in global drylands.…”