Reconstructing the origins and evolutionary journey of humans is a central piece of biology. Complementary to archeology, population genetics studying genetic variation among individuals in extant populations has made considerable progress in understanding the evolution of our species. Particularly, studies in indigenous humans provide valuable insights on the prehistory of humans because their life history closely resembles that of our ancestors. Despite these efforts, it can be difficult to disentangle population genetic inferences because of the interplay among evolutionary forces, including mutation, recombination, selection, and demographic processes. To date, few studies have adopted a comprehensive framework to jointly account for these confounding effects. The shortage of such an approach inspired this dissertation work, which centered on the development of model-based analysis and demonstrated its importance in population genetic inferences. Indigenous African Pygmy hunter-gatherers have been long studied because of interest in their short stature, foraging subsistence strategy in rainforests, and long-term socio-economic relationship with nearby farmers. I proposed detailed demographic models using genomes from seven Western African Pygmies and nine Western African farmers (Appendix A). Statistical evidence was shown for a much deeper divergence than previously thought and for asymmetric migrations with a larger contribution from the farmers to Pygmies. The model-based analyses revealed significant adaption signals in the Pygmies for genes involved in muscle development, bone synthesis, immunity, reproduction, etc. I also showed that the proposed model-based approach is robust to the confounding effects of evolutionary forces (Appendix A). Contrary to the low-latitude African homeland of humans, the indigenous Siberians are long-term survivors inhabiting one of the coldest places on Earth. Leveraging whole exome sequencing data from two Siberian populations, I presented demographic models for these North Asian dwellers that include divergence, isolation, and gene flow (Appendix B). The best-fit models suggested a closer genetic affinity of these Siberians to East Asians than to Europeans. Using the model-based framework, seven NCBI BioSystems gene sets showed significance for polygenic selection in these Siberians. Interestingly, many of these candidate gene sets are heavily related to diet, indicating possible adaptations to special dietary requirements in these populations in cold, resource-limited environments. Finally, I moved beyond studying the history of extant humans to explore the origins of our species in Africa (Appendix C). Specifically, with statistical analyses using genomes only from extant Africans, I rejected the null model of no archaic admixture in Africa and in turn gave the first whole-genome evidence for interbreeding among human species in Africa. Using extensive simulation analyses under various archaic admixture models, the results suggest recurrent admixture between the ancestors of archaic and modern Africans, with evidence that at least one such event occurred in the last 30,000 years in Africa.

Cooperation presents a major challenge for evolutionary theory: how can competition favor a trait that imposes a cost on the individual expressing it while benefitting another? This challenge has been answered by theory that emphasizes the importance of assortment between individuals that tend to cooperate and those who tend to behave selfishly, or `cheat'. Microbial cooperation remains puzzling, given the generally high genetic and taxonomic diversity of most microbial communities. Many microbial populations rely on shared, beneficial extracellular products for an array of functions in nature. However, when these lineages are maintained in liquid cultures, many are invaded and outcompeted by spontaneous `cheater' mutants that forego investments in these products while benefitting from those produced by neighbors. The apparent evolutionary instability of microbial investments in extracellular products in well-mixed laboratory cultures finds a natural parallel in the phenomenon of toxic microalgal blooms. These extremely dense populations of often free-living microalgae destroy populations of competing microalgae and grazing zooplankton that normally control population densities. Bloom populations of planktonic microalgae are unstructured, and seem ill suited for the evolution of cooperation. In this thesis, I have established a new theoretical framework for understanding the evolution of microbial external goods. This framework highlights the importance of cell-level structure in the distribution of these external products, as well as genetic structuring in populations. This perspective informed an investigation into the social niche of a biofilm-dwelling regulatory mutant of the important biocontrol strain Pseudomonas chlororaphis. In the highly self-structured environment of a bacterial biofilm, a surprising mutualistic association between this mutant and the wild type emerged, underscoring the importance of microbial ecology in understanding the evolution of niche construction. Extending these lessons to the evolutionary problem of exotoxins in free-swimming microalgae yields the novel possibility that fluctuations in density of toxic strains shift a cell-level functioning exotoxin into a true public good that may be exploited by cheaters. I show that exotoxicity can serve cell-level functions in Prymnesium parvum. Despite these cell-level benefits, the existence of nontoxic lineages within toxic blooms hints at a complex interaction between rapid evolutionary and ecological changes in toxic blooms.

Canopy structure has long been thought to influence the productivity and ecological dynamics of tropical forests by altering the availability of light to leaves. Theories and methods that can connect detailed quantitative observations of canopy structure with forest dynamics, however, have been lacking. There is urgent need to resolve this uncertainty because human-caused climate change may alter canopy structure and function in the Amazon. This work addresses this problem by, first, developing methods based on LiDAR remote sensing of fine-scale structural variation to predict the spatial structure of leaf area and light in forest canopies of the central Amazon (Appendices B&C). I show that LiDAR-based leaf area and light estimates can be used to predict the productivity of tree size groups and one-hectare forest plots--as well as differences between 2 sites separated by 500km (App. B). Sites also differed in canopy structure and the distribution of tree frequencies over size (size or diameter distribution). A model based on tree architecture, however, was able to connect observed differences in canopy architecture with size distributions to predict plot and site differences (App. D). This model showed that tree architecture is plastic in different light environments. While plasticity may increase light absorption, the smallest size groups appeared light limited. Absorption over size groups in one site, but not the other, agreed with the hypothesis of energetic equivalence across size structure. Ultimately, the performance of individual trees of different sizes in different canopy environments links forest demography with canopy structure and ecosystem function--I present a study aimed at improving tests of individual level theories for the role of light dependence in tree growth (App. A). Together, this work quantitatively connects canopy structure with forest carbon dynamics and demographic structure and further develops LiDAR as premier tool for studying forest ecological dynamics. Assessing variation in biomass growth and demographic structure over tropical landscapes with remote sensing will improve understanding of ecosystem function and the role of the Amazon in global Carbon dynamics.

The trait based approach has been proposed as a way to reconcile community ecology. Despite recent advances in trait based ecology, such as the development of global trait databases and standardized methodology for trait collections, it remains unclear to what degree traits vary across individuals, species, and communities. In addition, the drivers of trait variation may shed light on the underlying processes that maintain species diversity and community assembly at local to continental scales yet these have been poorly studied. In this study, I examine both the magnitude of trait variation as well as the patterns of trait variation at local to continental scales in order to understand the drivers of diversity patterns across environmental gradients. First, I quantified the magnitude of trait variation at local scales in a dry tropical forest and determined that intraspecific variation is not negligible and can be quite large for compound-leaved species. However, I showed that the sample sizes necessary for quantifying trait variation are tractable and should encourage the adoption of trait variation in trait based ecology. Second, I tested whether climatic variables are predominantly responsible for observed trait variation across dry tropical forests in the Americas. I showed that climatic variability, specifically variability in precipitation, explained a large degree of observed trait variation across dry tropical forests and may provide a unique approach for classifying dry tropical forests based on their inherent degree of climatic seasonality. Third, I quantified patterns of trait variation at continental scales across elevational gradients at high to low latitudes. I showed that climatic variables largely drive patterns of trait variation at high latitudes while biotic factors largely drive patterns of trait variation at low, tropical latitudes. This finding has implications for understanding large-scale patterns of species diversity across elevational and latitudinal gradients. Finally, I apply trait variation to life history theory by quantifying variation in two life history traits (growth and reproduction) in a tropical tree species using a legacy dataset. I showed that variation in these two life history traits is due to both resource availability and allometric related effects on both traits. In sum, this study advances our understanding of the magnitude and underlying drivers of trait variation at local to continental scales.

Predicting the interactions between climate change and ecosystems remains a core problem in global change research; tropical forest ecosystems are of particular importance because of their disproportionate role in global carbon and water cycling. Amazonia is unique among tropical forest ecosystems, exhibiting a high degree of coupling with its regional hydrometeorology, such that the stability of the entire forest-climate system is dependent on the functioning of its component parts. Belowground ecohydrological interactions between soil moisture environments and the roots which permeate them initiate the water transport pathway to leaf stomata, yet despite the disproportionate role they play in vegetation-atmosphere coupling in Amazonian forest ecosystems, the impacts of climate variability on the belowground environment remain understudied. The research which follows is designed to address critical knowledge gaps in our understanding of root functioning in Amazonian tropical forests as it relates to seasonality and extremes in belowground moisture regime as well as discerning which ecohydrological mechanisms govern ecosystem-level processes of carbon and water flux. A secondary research theme is the evaluation and use of models of ecosystem function as applied to Amazonia - these models are the "knowledge boxes" which build in the ecohydrological hypotheses (some testable than others) deemed to be most important for the forest ecosystems of Amazonia. In what follows, I investigate (i) which mechanisms of water supply (from the soil environment) and water demand (by vegetation) regulate the magnitude and seasonality of evapotranspiration across broad environmental gradients of Amazonia, (ii) how specific hypotheses of root function are or are not corroborated by soil moisture measurements conducted under normal seasonal and experimentally-induced extreme drought conditions, and (iii) the linkage between an extreme drought event with associated impacts on root zone soil moisture, the inferred response of root water uptake, and the observed impacts on ecosystem carbon and water flux in an east central Amazonian forest.

Species diversity and coexistence have long been central foci of ecology, but field studies are often limited to describing diversity patterns, while theory frequently ignores environmental variation. Scale transition theory is an ideal framework in which to study species diversity, as it explicitly accounts for this environmental variability and allows for the quantification of coexistence mechanisms. Each coexistence mechanism arises from specific types of biotic and abiotic interactions. Moreover, mechanism magnitudes provide information about how these interactions contribute to coexistence. By studying how the natural history of a community determines these biotic and abiotic interactions, insight can be gained into how that natural history influences coexistence. Environmental variation is a central hypothesis for the maintenance of diversity in both desert annual plants and streams. This dissertation is broadly interested in the way differences in the environmental responses of species interact with the structure of the environmental conditions to affect coexistence. I use scale transition theory to develop theoretical understanding of how life history and environmental structure in these communities influence coexistence mechanisms and diversity. In desert annual plants, the focus is on the environmental response itself: how germination depends on environmental conditions. I analyze how this life history interacts with variation in the environment to affect coexistence. The germination responses of desert annual plants to an unstudied type of environmental variation, duration of soil moisture after rainfall, generate species-specific but highly structured patterns of germination variation. Although this germination variation is one-dimensional, the nonlinearities that arise due to germination biology generate sufficient germination variation to promote coexistence by the temporal storage effect. In stream communities, I examine how the physical structure of stream environments affects coexistence given that species’ performance is environmentally dependent. This dissertation demonstrates that patterns of diversity along the stream are related to the strength of coexistence. The downstream drift of organisms has relatively minor effects on coexistence despite asymmetric shifts in the distribution of organism in the stream. This study identifies conditions that eliminate the effects of the branched structure of stream networks on coexistence. Branching has no effect on community dynamics if (a) tributaries have identical environmental conditions, (b) habitat size increases additively at confluences, and (c) demographic stochasticity is unimportant. Any effects of branching on coexistence caused by violating the environmental condition are asymptotically eliminated as streams increase in size. These studies provide a theoretical, mechanistic foundation for the study of stream communities that addresses environmental and life history factors long recognized as important by empirical stream ecologists.

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