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The maintenance of ecological communities through space and time is driven by complex processes which often operate simultaneously. Understanding the mechanisms that underlie patterns of species diversity and coexistence across scale remains a key focus for ecologists. Empirical experiments across large spatial and temporal scales are critical to rigorously test prevailing ecological theory and identify context dependencies. Such studies are necessary to determine regional variation in the effects of local-scale processes, which should be explicitly incorporated into the examination of macroecological patterns. The striking richness of species concentrated at low compared to higher latitudes—known as the latitudinal diversity gradient— is one of the most well-documented patterns of global biodiversity. Ecologists continue to test hypotheses that can explain this broad-scale pattern and, recently, the biotic interactions hypothesis (BIH) has received clear empirical support in both terrestrial and marine systems. Under the BIH, the relative strength of species interactions increases toward the tropics and serves to maintain the high diversity of species observed there. Despite accruing support for the BIH, interaction outcomes can be quite variable and little is known about the extent and the drivers of variability in these community-scale processes that shape regional patterns. In my dissertation, I explore how multiple processes (e.g. predation, competition, and disturbance) shape patterns of assembly and coexistence through empirical examination of subtidal marine hard-substrate communities across varying spatial and temporal scales. To achieve this, I conducted standardized experiments in nearshore habitats across four biogeographic regions spanning 47-degrees of latitude of the eastern Pacific Ocean and across ocean basins in the tropics (Pacific and Atlantic Panama). Among my research objectives I was able to: (1) explore variation in consumer effects on prey community structure across latitude and identify key attributes of predator communities that shape impacts on prey in the tropics, (2) examine mechanisms contributing to coastal and seasonal variation in consumer pressure that underlies stronger predation in tropical communities, and (3) uncover a strong nested structure in networks of competing species across latitude that contributes to enhanced tropical coexistence. My dissertation provides novel insights into the complex nature of consumer-prey interactions across latitude, with particular focus on tropical communities, which have been identified as important hotspots for predation based on theoretical predictions and prior experimental studies. Further, results reported here improve our understanding of underlying mechanisms and the context dependencies of interactions that contribute to coexistence in diverse ecological communities. These large-scale experiments on naturally assembled communities provide critical insights into the processes that contribute to biodiversity maintenance and ecosystem functioning in a changing world. / Biology

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I studied song variation throughout the range of a Neotropical lowland bird species, the Buff-throated Woodcreeper (Xiphorhynchus guttatus ; Aves, Dendrocolaptidae), to examine support for the use of vocal characters in defining species-limits in suboscines. This species is common across most of the lowlands of Amazonia and the Atlantic forest, its populations are separated by geographic barriers well-known in regional biogeography, and vocalizations likely used in reproductive isolation presumably are innate. I present a detailed overview of woodcreeper behavior in general and of the systematics, distribution, identification, voice, behavior, and conservation of the Xiphorhynchus guttatus superspecies in particular. Analyses of my field data revealed that this species' song varies more than songs of most suboscines and that song variation within individuals is best quantified using the relative length of three song parts: the introduction, middle, and conclusion. Within each song part, the structure of component notes and the rate at which these notes are repeated vary little. I could best distinguish subspecies groups by differences in note structure and repetition rate. Using multivariate analysis of spectrogram parameters and the location of breakpoints separating song parts, I could place a song within a subspecies group with a high degree of certainty. Thus, song types correspond well with both subspecies groups and known centers of endemism in the region. Not only do subspecies groups have strikingly different songs, but songs differ among and within subspecies. Even different individuals within populations can be diagnosed on the basis of their songs. Early researchers reported that suboscine song does not vary geographically, but more recent quantitative studies have revealed geographic variation in the songs of at least four suboscine species. Even so, vocal differences among suboscine populations are more subtle than those in oscines, so rigorous sampling of large numbers of songs and of individuals is necessary to detect these differences. Unlike a recent study of antshrike vocalizations, geographic variation in voice is not correlated with geographic variation in genetics in the Xiphorhynchus guttatus complex.

Variation in crop yields has significant impacts on food supply in many developing nations and on global food prices. I applied a recently quantified link between spatial and temporal variation to gain general insights on the dynamics of food production, as well as to test whether a prediction that relies on space-for-time substitution applies for crop yields, and at which spatial scale. I analyzed patterns of variation on global yield for 77 crops recorded in 212 countries over 22 years (1990 – 2012). I found that if we know how crop yields vary in space, we could predict variation in crop yields over time at various scales. Specifically, spatial variation can substitute for temporal variation in predicting the variability of yield of certain staple crops when synchrony and persistence (persistence = consistent differences in mean yield values among locations or regions) are taken into account. This space-time substitutability has potential to forecast temporal stability of food production from its spatial data alone, which should allow countries and various agencies to improve agricultural policies and production forecasts to ensure stability in local and global food supply. I also found that a crop’s preferred climatic conditions were strong predictors of synchrony between countries at the continental scale. This provided insights on the type of crops that are good candidates for effective use of spatial variability to predict their regional temporal variability in yields. These include crops that have high preferred-germination-soil temperature, low minimum crop water needs, and low minimum growing period. Lastly, as global warming increases crop yield synchrony, the total variability of global food supply increases, which results in lower stability in global food supply and exacerbates food insecurity. Combined with the predicted higher frequencies of climate extremes, the findings in this study reinforce the current view that climate change will have negative consequences on the global food supply. / Thesis / Master of Science (MSc) / Fluctuation in crop yields has significant impacts on food supply in many developing nations and on global food prices. I analyzed patterns of variation on global yield of 77 crops recorded in 212 countries over 22 years. I found that if we know how crop yields vary in space, we could predict fluctuation in crop yields over time at various scales. Since crop yields are the most important aspect in raising global food supplies, the ability to accurately forecast how much they will fluctuate would aid governing bodies in dealing with uncertainties and make informed decisions to ensure stability in local and global food supply. I also found that a crop’s preferred climatic conditions were strong predictors of its simultaneous drop (or rise) in adjacent countries. This helps to decide which crops are good candidates to use spatial variability in predicting their regional temporal variability in yields.

Spatial and temporal changes in the distribution of food organisms potentially available to curlew sandpipers Calidris ferruginea at Langebaan Lagoon (33°s, 18°E), South Africa, are described for the period February 1974 - March 1975. Seasonal changes in the diet of curlew sandpipers foraging in the intertidal sandflats and marshes were studied, and the food taken by male and female, and immature and adult, birds was compared. The daily and seasonal activity of curlew sandpipers was monitored during March 1974 - March 1975 and this also provided information on the birds' foraging behaviour and foraging techniques, their use of microhabitat and their foraging related to shore level. Variations during the austral summer in the density and the foraging of curlew sandpipers related to the density of their prey was investigated in the light of Royama's (1971) theory of profitability. The foraging behaviour and spatial distribution of foraging male and female curlew sandpipers at Kommetjie (34 o8°s, 18 19°E) was compared, since curlew sandpipers show sexual dimorphism with females having-longer culmens. The energy requirements and energy intake of curlew sandpipers at Langebaan Lagoon are described. The gross annual production of the benthic invertebrates potentially available to the birds was estimated, as well as the birds' impact on this.

In the United States, the total confirmed and probable cases of Lyme disease have more than doubled in the past decade. The increase in human incidence has been attributed, in part, to the range expansion of the principal vector of the bacterial pathogen, the black-legged tick (Ixodes scapularis). The tick life cycle includes three distinct hematophagous stages, each with different temporal and spatial influence on tick infection and human exposure. Therefore, a model that accurately predicts the dynamics of all life stages would be more accurate in describing the risk of encountering a tick-borne disease (TBD). To this end, I sought out to develop process-based models grounded in ecological theory and community ecology to make quantitative predictions of questing tick populations. Furthermore, the ultimate goal was to produce iterative, short (< 31 days) to intermediate (6 month - 1 year) forecasts on a daily basis in areas of the United States where Lyme disease is endemic. In Chapter 1, I built stage-structured population models in a data fusion framework that incorporates environmental variables such as the host population, relative humidity, and temperature, to predict the questing population of each life stage. I found that a four-stage model that includes the ecologically relevant dormant overwintering nymph state outperforms other models. The interplay between weather and host populations was also predictive. In Chapter 2, I describe a data-assimilation scheme developed to update the tick population model iteratively and evaluate forecast uncertainty and sensitivities. Larval abundances were spatially heterogeneous, likely due to their limited dispersal capacity, and sampling efforts at this stage were less likely to reduce forecast uncertainty than efforts at later stages. Chapter 3 evaluates the transferability and the structural components of this model for I. scapularis and Amblyomma americanum populations at NEON. A. americanum is arguably the second-most medically important tick species in the US. In general, forecasts were biased and tended to overpredict both species, this trend was on a latitudinal gradient, and forecasts for I. scapularis were more skillful than for A. americanum. Given the model framework, it appears that mouse abundance is less predictive of ticks at NEON than at Cary. In Chapter 4, I estimated tick density at NEON sites and is used these estimates to constrain the parasitism state of mice through time, which has important implications for TBD management. Knowing when mice are parasitized could lead to management actions for mice removal and is another proxy for disease risk as this information tells us when ticks are active. Overall, this dissertation focused on building mechanistic ecological forecasts from the ground up. I started with model calibration, then built a data assimilation scheme, and tested it at sites across the US. Therefore, this work represents the first of its kind pipeline from ecological model calibration to forecast implementation.