Decay of plant litter represents an enormous pathway for carbon (C) into the atmosphere but our understanding of the mechanisms driving this process is particularly limited in drylands. While microbes are a dominant driver of litter decay in most ecosystems, their significance in drylands is not well understood and abiotic drivers such as photodegradation are commonly perceived to be more important. I assessed the significance of microbes to the decay of plant litter in the Sonoran Desert. I found that the variation in decay among 16 leaf litter types was correlated with microbial respiration rates (i.e. CO2 emission) from litter, and rates were strongly correlated with water-vapor sorption rates of litter. Water-vapor sorption during high-humidity periods activates microbes and subsequent respiration appears to be a significant decay mechanism. I also found that exposure to sunlight accelerated litter decay (i.e. photodegradation) and enhanced subsequent respiration rates of litter. The abundance of bacteria (but not fungi) on the surface of litter exposed to sunlight was strongly correlated with respiration rates, as well as litter decay, implying that exposure to sunlight facilitated activity of surface bacteria which were responsible for faster decay. I also assessed the response of respiration to temperature and moisture content (MC) of litter, as well as the relationship between relative humidity and MC. There was a peak in respiration rates between 35-40oC, and, unexpectedly, rates increased from 55 to 70oC with the highest peak at 70oC, suggesting the presence of thermophilic microbes or heat-tolerant enzymes. Respiration rates increased exponentially with MC, and MC was strongly correlated with relative humidity. I used these relationships, along with litter microclimate and C loss data to estimate the contribution of this pathway to litter C loss over 34 months. Respiration was responsible for 24% of the total C lost from litter – this represents a substantial pathway for C loss, over twice as large as the combination of thermal and photochemical abiotic emission. My findings elucidate two mechanisms that explain why microbial drivers were more significant than commonly assumed: activation of microbes via water-vapor sorption and high respiration rates at high temperatures.

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.

Nitrous oxide (N2O) is a major contributor to the greenhouse effect and to stratospheric ozone depletion. In soils, nitrogen reduction is performed by biotic and abiotic processes, including microbial denitrification and chemical denitrification. Chemical denitrification, or chemodenitrification, is the abiotic step-wise reduction of nitrate (NO3-), nitrite (NO2-), or nitric oxide (NO) to N2O in anoxic environments, with high turnover rates particularly in acidic soils. Chemodenitrification was identified in various environments, but the mechanism is still not understood. In this study, the factors influencing abiotic reduction of NO2- to N2O in acidic tropical peat soil are examined. These factors include pH, organic matter content, and dissolved ferrous iron. Anoxic peat soil from sites located in the Peruvian Amazon was used for incubations. The results show that peat soil (pH ~4.5) appears to reduce NO2- more quickly in the presence of lower pH and higher Fe(II) concentrations. NO2- is completely reduced in excess Fe(II), and Fe(II) is completely oxidized in excess NO2-, providing evidence for the proposed mechanism of chemodenitrification. In addition, first order reaction rate constants kFe(II) and kNO2- were calculated using concentration measurements over 4 hours, to test for the hypothesized reaction rate relationships kFe(II): kFe(II) kFe(II)~NO2- > kFe(II)>NO2- and kNO2-: kFe(II)NO2-. The NO2- k values followed the anticipated pattern, although the Fe(II) k value data was inconclusive. Organic material may also play a role in NO2- reduction through chemodenitrification, and future experimentation will test this possibility. How and to what extent the pH and the concentrations of organic matter and Fe(II) affect the kinetic rate of chemodenitrification will lend insight into the N2O production potential of natural tropical peatlands.

Functional traits research has improved our understanding of how plants respond to their environments, identifying key trade-offs among traits. These studies primarily rely on correlative methods to infer trade-offs and often overlook traits that are difficult to measure (e.g., root traits, tissue senescence rates), limiting their predictive ability under novel conditions. I aimed to address these limitations and develop a better understanding of the trait space occupied by trees by integrating data and process models, spanning leaves to whole-trees, via modern statistical and computational methods. My first research chapter (Chapter 2) simultaneously fits a photosynthesis model to measurements of fluorescence and photosynthetic response curves, improving estimates of mesophyll conductance (gm) and other photosynthetic traits. I assessed how gm varies across environmental gradients and relates to other photosynthetic traits for 4 woody species in Arizona. I found that gm was lower at high aridity sites, varied little within a site, and is an important trait for obtaining accurate estimates of photosynthesis and related traits under dry conditions. Chapter 3 evaluates the importance of functional traits for whole-tree performance by fitting an individual-based model of tree growth and mortality to millions of measurements of tree heights and diameters to assess the theoretical trait space (TTS) of “healthy” North American trees. The TTS contained complicated, multi-variate structure indicative of potential trade-offs leading to successful growth. In Chapter 4, I applied an environmental filter (light stress) to the TTS, leading to simulated stand-level mortality rates up to 50%. Tree-level mortality was explained by 6 of the 32 traits explored, with the most important being radiation-use efficiency. The multidimentional space comprising these 6 traits differed in volume and location between trees that survived and died, indicating that selective mortality alters the TTS.