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On dryland hillslopes, vegetation water availability is often subsidized by the redistribution of rainfall runoff from bare soil (sources) to vegetation patches (sinks). In regions where rainfall volumes are too low to support spatially continuous plant growth, such functional connectivity between bare soil and vegetated areas enables the establishment and persistence of dryland ecosystems. Increasing the connectivity within bare soil areas can intensify runoff and increase water losses from hillslopes, disrupting this redistribution and reducing the water available to sustain ecosystem function. Inferring functional connectivity (from bare to vegetated, or within bare areas) from structural landscape features is an attractive approach to enable rapid, scalable characterization of dryland ecosystem function from remote observations. Such inference, however, would rely on metrics of structural connectivity, which describe the contiguity of bare soil areas. Several studies have observed non-stationarity in the relations between functional and structural connectivity metrics as rainfall conditions vary. Consequently, the suitability of using structural connectivity to provide a reliable proxy for functional connectivity remains uncertain and motivates the work here. Rainfall-runoff simulations across a wide range of dryland hillslopes, under varying soil and rainfall conditions, are used to establish relations between structural and functional connectivity metrics. The model results identify that the relations vary between two hydrologic limits -- a `local' limit, in which functional connectivity is related to structural connectivity, and a ‘global’ limit, in which functional connectivity is most related to the hillslope vegetation fraction regardless of the structural connectivity of bare soil areas. The transition between these limits within the simulations depends on rainfall intensity and duration, and soil permeability. While the local limit may strengthen positive feedbacks between vegetation and water availability, the implications of these limits for dryland functioning need further exploration, particularly considering the timescale separation between storm runoff production and vegetation growth.

In dryland ecosystems, connectivity of bare soil patches is recognized as a key pattern attribute controlling resource conservation and structure-function relationships. Runoff redistribution from bare to vegetated patches concentrates water, enhancing vegetation growth and biomass. Conversely, a reduction in vegetation patches can lead to highly connected bare patches, triggering a threshold-like response with a large increase in hillslope runoff. Patterns of dryland vegetation are often used as indicators of landscape vulnerability, and there is increasing interest in using vegetation indices to predict connectivity-mediated abrupt shifts. One of the challenges to this goal lies in relating structural measures of connectivity – e.g., Flowlength – to functional measures, such as the source-to-sink path length of flow or the contributing source area. To address this challenge, a series of virtual runoff experiments on a patchily vegetated hillslope is presented with varying length scales and spatial configurations of vegetation, and rainfall intensity and duration. Particle tracer methods are used to relate (i) the runoff coefficient to the contributing source area, and (ii) Flowlength as a measure of structural connectivity to source-sink path lengths, as a measure of functional connectivity. The results suggest a power-law relation between runoff coefficient and contributing source area that is stable across storm and vegetation characteristics. The relation between Flowlength and functional connectivity varies between storm intensities and durations, and is strongest for low-intensity storms. The results have practical implications for tracer studies, and support incorporating rainfall intensity into the use of vegetation patterns to predict landscape stability thresholds.

The Rational Method remains one of the most widely used approaches for estimating peak discharge in small catchments. In one widely used interpretation of the Rational Method, the maximum p...

Forest cover loss in the tropics is well known to cause warming at deforested sites, with maximum temperatures being particularly sensitive. Forest loss causes warming by altering local energy balance and surface roughness, local changes that can propagate across a wide range of spatial scales. Consequently, temperature increases result from not only changes in forest cover at a site, but also by the aggregate effects of non-local forest loss. We explored such non-local warming within Brazil’s Amazon and Cerrado biomes, the region with the world’s single largest amount of forest loss since 2000. Two datasets, one consisting of in-situ air temperature observations and a second, larger dataset consisting of ATs derived from remotely-sensed observations of land surface temperature, were used to quantify changes in maximum temperature due to forest cover loss at varying length-scales. We considered undisturbed forest locations (1 km2 in extent), and forest loss trends in annuli (‘halos’), located 1–2 km, 2–4 km, 4–10 km and 10–50 km from these undisturbed sites. Our research finds significant and substantial non-local warming, suggesting that historical estimates of warming due to forest cover loss under-estimate warming or mis-attribute warming to local change, where non-local changes also influence the pattern of temperature warming.