Drylands, though one of the largest biomes, are also one of the most understudied biomes on the planet. This leaves scientists with limited understanding of unique life forms that have adapted to live in these arid environments. One such life form is the hypolithic microbial community; these are autotrophic cyanobacteria colonies that can be found on the underside of translucent rocks in deserts. With the light that filters through the rock above them, the microbes can photosynthesize and fix carbon from the atmosphere into the soil. In this study I looked at hypolith-like rock distribution in the Namib Desert by using image recognition software. I trained a Mask R-CNN network to detect quartz rock in images from the Gobabeb site. When the method was analyzed using the entire data set, the distribution of rock sizes between the manual annotations and the network predictions was not similar. When evaluating rock sizes smaller than 0.56 cm2 the method showed statistical significance in support of being a promising data collection method. With more training and corrective effort on the network, this method shows promise to be an accurate and novel way to collect data efficiently in dryland research.

Rising temperatures and increased droughts caused by climate change are threatening tropical forests through leaf thermal damage and subsequent thermal mortality. As temperatures are predicted to continue rising, understanding what mechanisms tropical tree species have to cool their leaves is important. Therefore, this study examines whether the rate of stem sap flow is significantly driven by changes in leaf temperature, other climate variables, and leaf size. Thermal videos of five different tropical tree species were collected at San Lorenzo National Park (Panama), alongside sap flow, weather, and leaf trait data. These data sets were used to estimate average leaf temperatures, rates of sap flow, leaf level vapor pressure deficit (VPD), and average leaf area for each tree species. In an initial analysis, average leaf temperatures and leaf level VPD were compared to rates of sap flow using nonlinear least squares regression. The greatest rate of change in the increase of the rate of sap flow as leaf temperature increased, (kTleaf), was compared to the average leaf areas in a second analysis using linear regression. For the first analysis, there was a positive correlation between the rate of sap flow and average leaf temperature, which implied that leaf temperature did partially drive changes in the rate of sap flow. The positive correlation between rates of sap flow and leaf level VPD demonstrated that VPD affected sap flow, but only up to certain values of VPD. The plateau of sap flow rates also suggested that individual root and vascular systems limited the volume of water that could be transported at once. For the second analysis, there was no correlation between leaf area and changes in rates of sap flow. These results imply that tropical tree species with the largest maximum rates of sap flow will be able to evaporatively cool in hotter climates. Furthermore, the lack of relationship between increased average leaf area and kTleaf for the analyzed species suggests that different measurements should be used to study the relationship boundary layers and the rate of sap flow in future, or that there potentially was an unidentified variable that influenced this relationship.