Remote‐sensing‐derived fractures and shrub patterns to identify groundwater dependence

Abstract

The identification and location of groundwater‐dependent ecosystems are the first steps in protecting and managing them. Such identifications are challenging where the surface expressions of groundwater are not obvious. This work presents a remote‐sensing‐based approach to infer the groundwater dependence of semiarid shrubs from their association with fractures that facilitate root access to groundwater. As a case study, we used the Ziziphus lotus matorral in south‐east Spain, a priority conservation habitat in the European Union (Habitat 5220*, Directive 92/43/EEC) that is highly threatened by agricultural and urban sprawl. The approach combines object‐based image analysis of high‐resolution orthoimages to map Ziziphus individuals, geomorphometric analysis of a lidar‐derived terrain model to map bedrock fractures, and spatial statistics to assess the association between Ziziphus and fractures. Electrical resistivity tomography was used to validate the identified fractures, and the seasonal dynamics of the normalized difference vegetation index was used to prove that Z. lotus maintained higher greenness during the summer drought and was less coupled with precipitation than the nearby nonphreatophytic vegetation. A majority (61%) of the Ziziphus patches, particularly the smallest ones, occurred within 50 m of faults. This spatial association between phreatophyte shrubs and fractures contributes to the identification of groundwater‐dependent ecosystems. This approach offers several advantages because it is simple, low cost, and non‐destructive. In addition, the differentiation of shrubs into size classes provided insights into the long‐term environmental controls underlying the establishment of Ziziphus individuals. The evidence of groundwater dependence by Z. lotus in Habitat 5220* indicates the need for its urgent protection under the Water Framework Directive.

Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study

“…During recent decades, several studies reported that Ziziphus lotus is declining in SE Spain, Sicily and Cyprus ( [49]). In Europe, the largest population occurs in the Cabo de Gata-Níjar Natural Park (SE Spain), where an increased mortality of individual shrubs of all ages was observed in the last decade ( [50,51]). …”

“…However, in test-zone-2 some trees do coexist, whose presence may affect the detection accuracies. In those cases, the learning of the CNN-model can be improved by using more spectral bands or temporal information, e.g., including Near Infrared, Digital Surface Model (DSM) or the seasonal NDVI dynamics [51,58].…”

A Multi-Temporal Object-Based Image Analysis to Detect Long-Lived Shrub Cover Changes in Drylands

“…Ziziphus lotus (L.) Lam, a long-lived shrub from Mediterranean drylands [27], shows characteristics for a multi-temporal analysis of the spatial distribution in its populations with OBIA. This shrub species depends on groundwater [28], forms fertility islands, and is considered an engineering species [29] of an ecosystem of interest for conservation at the European level (Directive 92/43/CEE). The main European population of the shrub species is located in a flat coastal area surrounded by greenhouses in the Cabo de Gata-Níjar Natural Park, Spain.…”

“…Since 1944, several studies have evaluated this community of Z. lotus. Shrub patterns to identify groundwater dependence [28], the formations of shrubs in dunes [37], shrub spatial aggregation and consequences for reproductive success [29], and mutual positive effects between shrubs [38] have been researched. Yet, the monitoring of the shrub population dynamics has never been studied.…”

Biohydrology—Walking on drylands and swimming through pores

“…Although an emerging body of literature in the last decades has focused on researching dryland ecosystems, there is a surprisingly weak understanding of biohydrological processes. One of the processes is groundwater access by vegetation, which Guirado et al () studied using a non‐destructive low‐cost remote‐sensing‐based approach. This approach combined object‐based image analysis of high‐resolution orthoimages to map shrub individuals with geomorphometric analysis of a lidar‐derived terrain model to map fractures that roots use to access groundwater.…”