Molecular biologists have extensively studied Dictyostelium discoideum and consider it a model organism for the study of cellular differentiation but paradoxically many aspects of the natural life and evolution of this organism are unknown. My study demonstrates there is high clonal diversity in nature and that different clones coexist in the same small soil sample. Thus, amoebae with different genotypes can join in the same multicellular organism making a genetic chimera in nature. I also show that a linear dominance hierarchy describes the interactions of genetically distinct clones in competition for survival in the multicellular stage. In fact, during this stage the amoebae differentiate into different types of cells allowing the pseudoplasmodium to form a fruiting body consisting of two principle cell types: the spore and the stalk cells. The formation of the fruiting body probably guarantees a better survival and dispersion of the spore but requires the death of 20% of the cells that initially comprise the pseudoplasmodium that differentiate into the stalk and the basal disc. Contributions of two clones in a chimera to spore and stalk are often unequal, with one clone taking advantage of the other's stalk contribution. To assess whether there was a hierarchy of exploitation among clones, I competed all possible pairs among seven clones. I found a clear linear hierarchy with one clone being most dominant, and the bottom clone losing in competition to all the others. The hierarchy at an earlier stage, evaluated with prespore and prestalk cells in the slug, was not as clear. These results suggest that there is a single principal mechanism for differential contribution to the spore and that it involves more than spore/stalk competition. My results legitimate the use of chimeric D. discoideum as a model organism for the investigation of issues relating to coexistence and conflict between cells during organismal development and thus as a simple model for the relationship between social organisms.

<p> Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my coauthors and I apply metabolic scaling theory (MST) to examine scaling behavior and structural patterns of semi-arid conifer forests in Arizona and New Mexico. We conceptualize a linkage to mechanistic drivers of forest assembly that incorporates the effects of low-intensity disturbance, and physiologic and resource limitations as an extension of MST. We use both aerial LiDAR data and field observations to quantify changes in forest structure from the sub-meter to landscape scales. We found: (1) semi-arid forest structure exhibits MST-predicted behaviors regardless of disturbance and that MST can help to quantitatively measure the level of disturbance intensity in a forest, (2) the application of a power law to a forest overstory frequency distribution can help predict understory presence/absence, (3) local indicators of spatial association can help to define first order effects (e.g. topographic changes) and map where recent disturbances (e.g. logging and fire) have altered forest structure. Lastly, we produced a comprehensive set of above-ground biomass and carbon models for five distinct forest types and ten common species of the southwestern US that are meant for use in aerial LiDAR forest inventory projects. This dissertation presents both a conceptual framework and applications for investigating local scales (stands of trees) up to entire ecosystems for diagnosis of current carbon balances, levels of departure from historical norms, and ecological stability. These tools and models will become more important as we prepare our ecosystems for a future characterized by increased climatic variability with an associated increase in frequency and severity of ecological disturbances. </p>

<p> The rice stink bug, <i>Oebalus pugnax</i>(F.), is an important late season pest of rice that is noted for causing grain yield and quality reductions in the United States. This study investigated rice injury using field cages in two rice cultivars ('Cocodrie' and 'Wells') at bloom, milk, and soft dough stages and <i>O. pugnax</i> ecology in the Delta Region of Mississippi. </p><p> Specific objectives were: 1) to determine the impact of adult <i> O. pugnax</i> infestation on rice yield and grain quality at bloom, milk, and soft dough stages of rice development; 2) to determine the impact of adult <i> O. pugnax</i> gender and infestation duration on rice yield and grain quality at the milk stage of panicle development; 3) to identify and examine the seasonal abundance and phenology of <i>O. pugnax</i>on non-cultivated host grasses; and 4) to evaluate feeding preference and development of <i> O. pugnax</i> on host grasses. </p><p> Rice injury increased as <i>O. pugnax</i> density increased. The bloom and milk stages were the most vulnerable to blank and discolored kernels, respectively. <i>O. pugnax</i> feeding injury was significant after 3 d of infestation duration during the milk stage of panicle development. Female <i>O. pugnax</i> caused a greater percentage of blank kernels compared to males. </p><p> A survey of <i>O. pugnax</i> hosts indicated that Italian ryegrass, <i> Lolium perenne</i> L. ssp. <i>multiflorum</i> and winter wheat, <i> Triticum aestivum</i> L., were important hosts during spring and early summer. Junglerice, <i>Echinochloa colona</i> (L.) Link; crabgrass spp., <i>Digitaria</i> spp. Haller; southwestern cupgrass, <i> Eriochloa acuminata</i> (J. Presl) Kunth; and praire cupgrass, <i> Eriochloa contracta</i> (Hitchc.), were important hosts for <i> O. pugnax</i> during early to mid-summer. Browntop millet, <i>Urochloa ramosa</i>, and broadleaf signalgrass, <i>Urochloa platyphylla</i>, supported adult <i>O. pugnax</i> prior to overwintering. In a choice test of wild host grasses, junglerice was the most preferred over 10 other host grasses. In the no-choice test, mean development time was shorter and survival was greater for <i>O. pugnax</i> nymphs reared on rice, <i> Oryza sativa</i> L., compared to dallisgrass, <i>Paspalum dilatatum </i> Poir and junglerice. These results provide biological and ecological information on which new <i>O. pugnax</i> integrated pest management practices can be developed.</p>

<p> Various models of density dependence predicted different evolutionary outcomes for <i>Helicoverpa zea, Diabrotica virgifera,</i> and <i> Ostrinia nubilalis</i> using simple and complex resistance evolution models, different dose assumptions and refuge proportions. Increasing available refuge increased durabilities of pyramided Plant-Incorporated-Protectants (PIPs), especially between 1&ndash;5%. For some models of density dependence and pests, additional refuge resulted in faster adaptation rates. Significant considerations should be given to a pest's intra-specific competition in simple and complex theoretical models when designing insect resistance management plans. </p><p> Life-history, refuge, and dose characteristics of a PIP had different effects on the adaptation rate of a generic pest of Bt, and unexpected outcomes occurred. Intrinsic growth rate 'R₀' was the strongest evolutionary force, and large R₀'s reduced time to resistance for a high dose PIP to similar levels as projected for a low dose PIP. This was caused by differential density dependent effects in refuge and Bt fields that elevated generational resistance increases beyond those from selection alone. Interactions between density dependence and R₀ were always present and further affected the life-time of the PIPs. Varying 'average dispersal distance' did not affect evolutionary outcomes; however, increasing the proportion of the population engaging in dispersal often increased the durability of high dose PIPs. When resistance genes spread from a hypothetical hotspot, local resistance phenomena developed in the immediate surroundings. Higher growth rates lead resistance to spread faster through the landscape than lower rates. Increasing available refuges slowed adaptation rates to single PIPs and low dose pyramids, although non-linear trends were possible. </p><p> Integrated Pest Management (IPM) practices at the onset of PIP commercialization slowed pest adaptation rates. For corn rootworm, interspersing non-selective periods with IPM+IRM delayed resistance evolution, yet crop rotation was the best strategy to delay resistance. For bollworm inclusion of isoline corn as an IPM tool did not increase the life-time of the PIP. A local resistance phenomenon for rootworm was maintained immediately surrounding the hotspot; random selection of mitigatory strategies in the landscape slowed adaptation rates while mitigation in the hotspot alone did not. Mitigation extended the life-time of the pyramid minimally for both corn rootworm and bollworm.</p>

<p> In this work, I answer timely questions regarding tree growth, tree survival, and community change in California tree species, using a variety of sophisticated statistical and remote sensing tools. In Chapter 1, I address tree growth for a single tree species with a thorough explanation of hierarchical state-space models for forest inventory data. Understanding tree growth as a function of tree size is important for a multitude of ecological and management applications. Determining what limits growth is of central interest, and forest inventory permanent plots are an abundant source of long-term information but are highly complex. Observation error and multiple sources of shared variation make these data challenging to use for growth estimation. I account for these complexities and incorporate potential limiting factors into a hierarchical state-space model. I estimate the diameter growth of white fir in the Sierra Nevada of California from forest inventory data, showing that estimating such a model is feasible in a Bayesian framework using readily available modeling tools. In this forest, white fir growth depends strongly on tree size, total plot basal area, and unexplained variation between individual trees. Plot-level resource supply variables do not have a strong impact on inventory-size trees. This approach can be applied to other networks of permanent forest plots, leading to greater ecological insights on tree growth. </p><p> In Chapter 2, I expand my state-space modeling to examine survival in seven tree species, as well as investigating the results of modeling them in aggregate and comparing with the individual species models. Declining tree survival is a complex, well-recognized problem, but studies have been largely limited to relatively rare old-growth forests or low-diversity systems, and to models which are species-aggregated or cannot easily accommodate yearly climate variables. I estimate survival models for a relatively diverse second-growth forest in the Sierra Nevada of California using a hierarchical state-space framework. I account for a mosaic of measurement intervals and random plot variation, and I directly include yearly stand development variables alongside climate variables and topographic proxies for nutrient limitation. My model captures the expected dependence of survival on tree size. At the community level, stand development variables account for decreasing survival trends, but species-specific models reveal a diversity of factors influencing survival. Species time trends in survival do not always conform to existing theories of Sierran forest dynamics, and size relationships with survival differ for each species. Within species, low survival is concentrated in susceptible subsets of the population and single estimates of annual survival rates do not reflect this heterogeneity in survival. Ultimately only full population dynamics integrating these results with models of recruitment can address the potential for community shifts over time. </p><p> In Chapter 3, I combine statistical modeling with remote sensing techniques to investigate whether topographic variables influence changes in woody cover. In the North Coast of California, changes in fire management have resulted in conversion of oak woodland into coniferous forest, but the controls on this slow transition are unknown. Historical aerial imagery, in combination with Object-Based Image Analysis (OBIA), allows us to classify land cover types from the 1940s and compare these maps with recent cover. Few studies have used these maps to model drivers of cover change, partly due to two statistical challenges: 1) appropriately accounting for spatial autocorrelation and 2) appropriately modeling percent cover which is bounded between 0 and 100 and not normally distributed. I study the change in woody cover in California's North Coast using historical and recent high-spatial-resolution imagery. I classify the imagery using eCognition Developer and aggregate the resulting maps to the scale of a Digital Elevation Model (DEM) in order to understand topographic drivers of woody cover change. I use Generalized Additive Models (GAMs) with a quasi-binomial probability distribution to account for spatial autocorrelation and the boundedness of the percent woody cover variable. I find that historical woody cover has a consistent positive effect on current woody cover, and that the spatial term in the model is significant even after controlling for historical cover. Specific topographic variables emerge as important for different sites at different scales, but no overall pattern emerges across sites or scales for any of the topographic variables I tested. This GAM framework for modeling historical data is flexible and could be used with more variables, more flexible relationships with predictor variables, and larger scales. Modeling drivers of woody cover change from historical ecology data sources can be a valuable way to plan restoration and enhance ecological insight into landscape change. </p><p> I conclude that these techniques are promising but a framework is needed for sensitivity analysis, as modeling results can depend strongly on variable selection and model structure. (Abstract shortened by UMI.)</p>

<p> A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. <i>Every</i> location has a unique and constantly changing climate so that <i>any</i> distribution <i> could</i> be explained by some aspect of climate. </p><p> Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. </p><p> Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. </p><p> In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. </p><p> Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. </p><p> Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.) </p>

<p> Every interaction between species occurs in a heterogeneous environment that presents countless contexts that shape the interaction over time and space. The consequences of these interactions can regulate populations, as they trickle down to influence the genes that an individual passes on to its offspring, and then, in turn, scale back up to influence the genetic and phenotypic composition of future populations. In this work, I sought to uncover how these principles play out in the interactions between an invertebrate vector of human disease and the disease agent it carries. Disease vectors are often considered in a context that is faithful to the word as it is used in physics, where the vector is viewed as public transportation that moves the pathogen between hosts, experiencing no consequences of parasite infection. However, vectors face the challenge of how to maximize individual fitness in a stochastic environment with limited resources just as all other species do, so why would they be exempt from the effects of being parasitized? As such, I investigated the triatomine bug species <i>Rhodnius prolixus</i> when infected with the parasite <i>Trypanosoma cruzi</i> (etiological agent of Chagas disease), and co-infected with <i>T. cruzi</i> and its sister species, <i>T. rangeli.</i> I asked, does <i>T. cruzi</i> affect <i>R. prolixus</i> fitness, and under what contexts does this effect vary? I found a large range of variation in <i> R. prolixus</i> fitness when infected with <i>T. cruzi,</i> with the outcome being influenced by parasite strain, co-infection with <i> T. rangeli,</i> parasite dose, and the timing and order of infection. These factors did not act alone, but seemed to be dependent on one another: it was better to have a co-infection at lower <i>T. rangeli</i> doses, but at high <i>T. rangeli</i> doses, it was better to be infected with <i>T. cruzi</i> first, suggesting an interaction between dose, order and timing. These results illustrate the interactions across scales of both biological and spatio-temporal complexity that can be revealed when studying infectious disease through an ecological lens. Moreover, this work emphasizes the importance of taking into account the ecology of vector-borne neglected tropical diseases such as Chagas disease.</p>

<p> The exotic annual <i>Bromus tectorum</i> (cheatgrass) commonly occurs in dense, near-monocultures in the Great Basin, U.S.A. after diverse native plant communities have been mostly extirpated. Efforts to reestablish native species via direct seeding, typically with commercially produced, non-local seeds, are often unsuccessful. In addition to abiotic factors that often limit establishment, <i>B. tectorum</i> competition can impede native establishment in highly invaded communities, and commercially produced seeds may differ from local genotypes in their responses to these limitations. The phenomenon of complete <i>B. tectorum</i> stand failure, or 'die-off', can leave areas within near-monocultures devoid of growth for one or more years. Such areas may represent restoration opportunities if native seeds can establish within them. In October 2012, local and nonlocal (commercial) sources of <i>Poa secunda</i> (Sandberg bluegrass) and <i> Elymus elymoides</i> (bottlebrush squirreltail) were precision-planted in a recent die-off and adjacent near-monoculture (control) in northern Nevada under six treatments: litter removal, fungicide application, and no treatment; each with and without added simulated precipitation. I addressed the following questions: 1) Can native species be successfully restored in recent <i> B. tectorum</i> die-offs, and is establishment related to seedbed treatments and competition with <i>B. tectorum</i>? 2) Do local and nonlocal materials differ in their performance as restoration material, and if so, are these differences consistent across seedbed treatments and in and out of a recent die-off? Seeded plots were monitored nine times throughout two growing seasons for emergence and seedling activity, and seedling growth was measured in May of the first season. Emergence of native seeds was significantly lower in die-off plots, but there were significantly more actively growing seedlings of both species in die-off plots than in adjacent control plots by the end of the first growing season, and seedlings in the die-off exhibited more leaves, increase late season vigor, and, for <i>E. elymoides</i>, increased height. Second year survival patterns also suggested greater establishment in die-off plots. Local <i>P. secunda</i> demonstrated improved performance over nonlocal material ('Mt. Home' germplasm) in both seasons, whereas nonlocal <i>E. elymoides</i> (`Toe Jam Creek' germplasm) demonstrated aspects of higher performance than the local collection in the first year but not the second. Litter removal had a positive influence on seedling activity for both species, but only affected the survival of <i> P. secunda</i>. Late autumn (early growing season) water addition affected emergence timing for both species and resulted in more <i>E. elymoides </i> seedlings, but this affect was equal across controls and die-offs. Although these results are representative of conditions at only one site, they suggest that <i>B. tectorum</i> die-off may support increased establishment of native species regardless of seedbed treatment, and may therefore represent valuable opportunities for restoration. Also, they indicate that local and nonlocal seeds differ in performance in important but idiosyncratic ways, which supports the belief that seed source should be considered as a factor affecting restoration success but contradicts the idea of generalizable local vs. nonlocal performance patterns.</p>

<p> The global issues of acid deposition and climate change call for a greater understanding of the relative influence of broad gradients of acid deposition, climate, soil, and stand characteristics in montane temperate forests. At each of 30 sites along the Appalachian Trail, I measured overstory composition and density (including snags) using the point-centered quarter method (9 plots) and characterized understory species composition and cover (27 plots, 1 m2 each). Analytical approaches included NMS ordination, multiple linear regression, and beta regression. Spruce-fir sites had lower understory richness, lower understory cover, higher cover of strongly acidophytic understory species, and greater regeneration of canopy trees. Temperature affected understory composition and precipitation increased understory cover. The proportion of snags among canopy trees was highest on cool sites with dense canopies. The impact of nitrogenous deposition was limited, but it may have a fertilizer effect. Sites with acidified (high Al) soil had poor canopy regeneration. </p>

<p> This dissertation evaluates freshwater wetland impact avoidance and mitigation resulting from the New York State Department of Environmental Conservation (NYSDEC) permitting program within Central New York. Concurrent with this, is an effort to ascertain wetland functionality through a rapid assessment approach to wetland evaluation. Three primary techniques were employed: First, NYSDEC permit decisions were compared to the NYSDEC Freshwater Wetland Regulation Guidelines on Compensatory Mitigation (NYSDEC 1993), to determine whether or not the Guidance was adhered to. Second, NYSDEC permit requirements were compared to the actual mitigation efforts conducted by a permittee in the field to determine whether or not the permittee complied with imposed requirements. And third, a rapid assessment approach comparing functions and values at wetland mitigation sites to the corresponding natural wetland that was impacted by NYSDEC permit issuance was used to determine whether or not the functions and values provided by the mitigation adequately replaced those lost at the original impacted wetland site. The results of this review indicate that the majority of wetland mitigation guidelines are not followed the majority of time. For example, less than one third of the time was mitigation based on plans providing short or long term goals or measurable performance criteria. Often permittees do not comply with imposed freshwater wetland permit requirements related to mitigation. More specifically, thirty five percent of the time, permit requirements for mitigation were not met for those files sampled. As for the functions and values being replaced, that is not happening with six out of nine measured functions: open space and aesthetic resources; erosion control; pollution treatment; protection of subsurface water resources; wildlife habitat; and flood control. The three functions found to be replaced by mitigation include recreation; sources of nutrients in freshwater food cycles and nursery grounds / sanctuaries for freshwater fish; and education and scientific research.</p>