Browsing by Author "Clark, James S"

Background

Methods

Results

Conclusions

In this dissertation, we present models that are developed to accommodate challenges and advance insights from modeling ecological abundance data. All the models presented in this work are fit within a Bayesian hierarchical framework. Species distribution models (SDMs) relate observed species abundance or occurrence data to geographically referenced environmental variables. In this dissertation, we focus mainly on multi-species or joint SDMs to incorporate the dependence between multiple species. We provide a dynamic mechanistic modeling framework that combines several biological and physiological processes that are known to operate within a species community. More specifically, we include the processes of local species growth as well as species movement within a geographic region. The mechanisms are represented as parameters to be estimated in our model. As an illustrative example, we first apply our model to the citizen science dataset eBird. We then provide an application to fisheries data from the Northeast Fisheries Science Center that develops a richer model for species redistribution that incorporates time-varying environmental covariates.

As ecological data often exhibit a high incidence of zeros, we also develop models that address the issue of zero-inflation. While there is a wealth of literature on zero-inflated models for count data, we focus on data with continuous support. The familiar Tobit model accommodates positive continuous data with an excess of zeros, but does not allow for multiple interpretations of a zero as the also-familiar zero-inflated Poisson model does. We address this gap in the literature by first providing spatial and non-spatial zero-inflated Beta (ZIB) regression models for data that lie on the unit interval. We also provide a multivariate zero-inflated Tobit (MVT ZI-Tobit) regression model that can capture dependence between elements at a given observation index at multiple stages of the model. For both the ZIB and MVT ZI-Tobit, we present model comparison metrics for predictive performance that specifically target a model’s ability to capture zeros or dependence between observation elements. We apply our ZIB and MV ZI-Tobit models to percent cover of plant species in the Cape Floristic Region and total basal area of trees using Forest Inventory Analysis data, respectively.

Ecologists have long been interested in the relationships between climate change and forest biodiversity. For centuries, the scientific problems remain understanding the patterns of climate variation, forest geographic distribution, and demographic dynamics. Besides scientific merits, these questions will also help forest managers and policy makers to anticipate how forests respond to global change. This dissertation tackles these problems by using statistical modeling on climate and forest inventory data in the eastern United States.

In Chapter 1, we ask the question on the observed tree range distributions in response to contemporary climate change in the eastern United States. Tree species are expected to track warming climate by shifting their ranges to higher latitudes or elevations, but current evidence of latitudinal range shifts for suites of species is largely indirect. In response to global warming, offspring of trees are predicted to have ranges extend beyond adults at leading edges and the opposite relationship at trailing edges. Large-scale forest inventory data provides an opportunity to compare present latitudes of seedlings and adult trees at their range limits. Using the USDA Forest Service's Forest Inventory and Analysis data, we directly compared seedling and tree 5th and 95th percentile latitudes for 92 species in 30 longitudinal bands for 43,334 plots across the eastern United States. We further compared these latitudes with 20th century temperature and precipitation change and functional traits, including seed size and seed spread rate. Results suggest that 58.7% of the tree species examined show the pattern expected for a population undergoing range contraction, rather than expansion, at both northern and southern boundaries. Fewer species show a pattern consistent with a northward shift (20.7%) and fewer still with a southward shift (16.3%). Only 4.3% are consistent with expansion at both range limits. When compared with the 20th century climate changes that have occurred at the range boundaries themselves, there is no consistent evidence that population spread is greatest in areas where climate has changed most; nor are patterns related to seed size or dispersal characteristics. The fact that the majority of seedling extreme latitudes are less than those for adult trees may emphasize the lack of evidence for climate-mediated migration, and should increase concerns for the risks posed by climate change.

In Chapter 2, we ask the question on tree abundance within geographic range responding to climate variation in the eastern United States. Tree species are predicted to track future climate by shifting their geographic distributions, but climate-mediated migrations are not apparent in a recent continental-scale analysis (Chapter 1). To better understand the mechanisms of a possible migration lag, we analyzed relative recruitment patterns by comparing juvenile and adult tree abundances in climate space. One would expect relative recruitment to be higher in cold and dry climates as a result of tree migration with juveniles located further poleward than adults. Alternatively, relative recruitment could be higher in warm and wet climates as a result of higher tree population turnover with increased temperature and precipitation. Using the USDA Forest Service's Forest Inventory and Analysis data at regional scales, we jointly modeled juvenile and adult abundance distributions for 65 tree species in climate space of the eastern United States. We directly compared the optimal climate conditions for juveniles and adults, identified the climates where each species has high relative recruitment, and synthesized relative recruitment patterns across species. Results suggest that for 77% and 83% of the tree species, juveniles have higher optimal temperature and optimal precipitation, respectively, than adults. Across species, the relative recruitment pattern is dominated by relatively more abundant juveniles than adults in warm and wet climates. These different abundance-climate responses through life history are consistent with faster population turnover and inconsistent with the geographic trend of large-scale tree migration. Taken together, this juvenile-adult analysis suggests that tree species might respond to climate change by having faster turnover as dynamics accelerate with longer growing seasons and higher temperatures, before there is evidence of poleward migration at biogeographic scales.

In Chapter 3, we ask the question on the demographic dynamics of density dependence at the individual tree level in eastern US forests. Density dependence could maintain diversity in forests, but studies disagree on its importance. Part of the disagreement results from the fact that different studies evaluate different responses (per-seedling or per-adult survival or growth) of different stages (seeds, seedlings, or adults) to different inputs (density of seedlings, density or distance to adults). Most studies are conducted on a single site and thus are difficult to generalize. Using USDA Forest Service's Forest Inventory and Analysis data, we analyzed over a million seedling-to-sapling recruitment observations of 50 species for both per-tree (adult) and per-seedling recruitment rates, controlling for climate effects in eastern US forests. We focused on per-tree recruitment as it is most likely to promote diversity at the population level, and it is most likely to be identified in observational or experimental data. To understand the prevalence of density dependence, we quantified the proportion of species with significant positive or negative effects. To understand the strength of density dependence, we determined the magnitude of effects among conspecifics and heterospecifics, and how it changes with overall species abundance. We found that the majority of the 50 species have significant density dependence effects, mostly negative, on both per-tree and per-seedling recruitment. Per-tree recruitment is positively associated with conspecific seedlings, saplings, and heterospecific saplings, negatively associated with heterospecific seedlings, conspecific and heterospecific trees. Per-seedling recruitment is positively associated with conspecific and heterospecific saplings, but negatively associated with conspecific and heterospecific seedlings and trees. Furthermore, for both per-tree and per-seedling recruitment, density dependence effects are stronger for conspecific than heterospecific neighbors. However, the strength of these effects does not vary with species abundance. We conclude that density dependence is pervasive, especially for per-tree recruitment, and its strength among conspecifics and heterospecifics is consistent with the predictions of the Janzen-Connell hypothesis.

Unprecedented rates of warming and an inability to curtail greenhouse gas production

has fueled the discussion of how to mitigate climatic impacts. Climate impacts

on forests are coarsely understood. A large number of interacting environmental

variables affect every aspect of forest life cycles, and studies incorporating local

factors are scarce. For this study, a large manipulative climate experiment in both

northern(Massachusetts) and southern(North Carolina) sites was used to examine the

effect of climate change on demographic and physiological rates of 11 tree species

representative of the Eastern Deciduous Forest.

First, to clarify how environmental conditions of the next century will alter

seedling carbon assimilation, a hierarchical multivariate model that synthesizes over

16,000 instantaneous carbon exchange measurements from 285 trees of four species

was developed. Estimates of species-level light response curve parameters were used

to predict individual-level seasonal carbon budgets. This model revealed how the

balance between respiration and photosynthesis shifts with temperature, moisture,

and overstory canopy status. Furthermore, it showed that elevated temperatures

(3C and 5C) shift the seasonal species carbon budget allowing some Lirodendron

tulipifera to grow as much a 5.5 times more massive in elevated temperatures.

In addition, for certain species, demographic rates of seedlings can be scaled to

above-ground growth using short-term physiological responses.

Second, the relationship between seedling size and water-use was examined.

Trees grow from environmentally sensitive seedlings to large canopy individuals

capable of buffering environmental stress. At some intermediate size, a threshold is reached

where greater resilience results when increased resource gain overcomes the added

costs of size. For two seasons of this manipulative warming experiment, 123 external

heat pulse sapflow sensors were applied to 4 species (Acer rubrum, Lirodendron tulipifera,

Quercus alba, and Quercus rubra). The experimental seedlings, which vary in

mass from less than a tenth of a gram to 41 grams, were included to demonstrate

that both size and species influence water use. While larger size leads to increased

transpiration, reduced soil moisture paired with larger size leads to unpredictable

reductions in sapflow. Small seedlings were predictably reactive, but large seedlings

were both the least and most reactive to soil moisture reductions. When soil moisture

improved, after periods of moisture limitations, small individuals quickly recovered

and large individuals to a lesser extent. These results suggest that the seedlings of

this experiment were not consistently big enough to gain an advantage in water-use

like their larger canopy counter parts.

Lastly, this climate-warming experiment was expanded to include 4000 seedlings

of 11 total species across both the northern and southern sites. High-resolution subannual

growth measurements and a hierarchal Bayesian state-space model provided

a more accurate picture of seedling growth responses to sub-annual climatic variation,

by focusing on determinate vs. indeterminate growers and the interactions

between growth phenology, temperature tolerances, and climatic shifts. Determinate

species enhanced annual growth by shifting growth earlier in the season when

temperatures were more suitable, avoiding hot and dry conditions of summer. Indeterminate

species annual growth, which is focused within the summer, is dependent

on their ability to maintain growth during increasingly warmer and dryer summers.

Co-occurring species may respond differently and competitive regimes are shifted by

how growth phenology aligns with the seasonal patterns of climate change.

Questions of forest responses to climate change are multi-scaled. Responses depend

on local conditions, life-stage, natural history, and the scale of inference. Climate

change does not occur in isolation all factors must be weighed when evaluating

a response. For this study a manipulative climate experiment was used to address

these questions and investigate the effect of climate change on trees of the Eastern

Deciduous Forest.

Rising temperatures with increased drought pose three challenges for management of future biodiversity. First, are the species expected to be vulnerable concentrated in specific regions and habitats? Second, are the impacts of drought and warming varying across regions? Third, could recent advances in remote sensing techniques help us in monitoring the impacts in real-time? This dissertation is an effort to address the above questions in the three chapters.

First, I used foliar chemistry as a proxy for drought vulnerability. I used soil and moisture gradients to quantify habitat variation that could be critical for alleviating drought. I used a large dataset of forest plots covering the eastern united states to understand how community weighted mean foliar nitrogen and phosphorus vary across climate and soil gradients. I exploited trends in these variables between species, traits, and habitats to evaluate sensitivity. Critical to our approach is the capacity to jointly model trait responses. Our data showed that nutrient demanding species strongly respond to environmental gradients. I identified a wide range of sites across low to high latitudes threatened by drought. The sensitivity of species to high temperatures is largely explained by soil variations. Drought vulnerability of nutrient and moisture demanding species could be amplified depending on local soil and moisture gradients. Although local soil moisture may dampen drought-induced stress for species with large leaves and high water use, nutrient demanding species remain vulnerable in wet regions during droughts. Phosphorus demanding species adapted to dry sites are drought resilient compared to communities in wet sites. This research is consistent with the studies that supports declining nutrient demanding species with increasing temperature and decreasing moisture. I also detected strong soil effects on shaping community weighted traits across a large geographical and environmental range. Our data showed that soil effects on controlling foliar traits strongly vary across different climates. The findings are critical for conservations and maintaining the biodiversity.

Next, I used space-borne remotely sensed vegetation indices to monitor the process of leaf development across climate gradients and ecoregions in the southeastern United States. A hierarchical state-space Bayesian model was developed to quantify how air temperature, drought severity, and canopy thermal stress contribute to changes in leaf opening from mountainous to coastal regions. I synthesized daily field climate data with daily remotely sensed vegetation indices and canopy surface temperature during spring green-up season. The study was focused on observation of leaf phenology at 59 sites in the southeast United States between 2001 to 2012. Our results suggest strong interaction effects between ecosystem properties and climate variables across ecoregions. The findings showed that despite the much faster spring green-up in the mountains, coastal forests express a larger sensitivity to inter-annual anomaly in temperature than mountain sites. In spite of the decreasing trend in sensitivity to warming with temperature in all regions, there is an ecosystem interaction: Deciduous-dominated forests are less sensitive to warming than are those with few deciduous trees, possibly due to the presence of developed leaves in evergreen species throughout the season. The findings revealed mountainous forests are more susceptible to intensifying drought and moisture deficit, while coastal areas are relatively resilient. I found that increasing canopy thermal stress, defined as canopy-air temperature difference, slows the leaf-development following a dry year, accelerates it after a wet year.

Finally, I demonstrate how space-borne canopy “thermal stress”, i.e. surface-air temperature difference, could be used as a surrogate for drought-induced stress to estimate forest transpiration. Using physics-based relationships that accommodates uncertainties, I showed how changes in canopy water flux may be reflected in surface energy balance and in remotely-sensed thermal stress. Validating with field measurements of canopy transpiration in the southeastern US, I quantified sensitivity of transpiration to thermal stress in a range of atmospheric and climate conditions. I found that a 1 mm change in daily transpiration may cause 3 to 4 °C of thermal stress, depending on site conditions. The cooling effect is large when solar radiation is high or wind speed is low. The effect has the highest control on water-use during warm and dry seasons, when monitoring drought is essential. I applied our model to available satellite and metrological data to detect patterns of drought. Using only air and surface temperatures, I predicted anomaly in water-use across the contiguous United States over the past 15 years, and then compared with anomaly in soil water content and conventional drought indices. Our simple model showed a reliable accuracy in compare to the state-of-the-art general circulation models. The technique can be used in varying time-scales to monitor surface water-use and drought in large scales.

Under the increasing threat of climate change, it is imperative to understand the impact that environmental phenomena have on the demography and behavior of natural populations. In the last few decades an ever increasing body of research has documented dramatic changes in mortality rates and breeding phenology for a large number of species. A number of these have been attributed to the current trends in climate change, which have been particularly conspicuous in bird populations. However, datasets associated to these natural populations as well as to the environmental variables that affect their biology tend to be partial and incomplete. Thus, ecological research faces the urgent need to tackle these questions while at the same time develop inferential models that can handle the complex structure of these datasets and their associated uncertainty. Therefore, my dissertation research has focused on two main objectives: 1) to understand the relationship that demographic rates and breeding phenology of a colony of seabirds has with the environment in the context of climate change; and 2) to use and develop models that can encompass the complex structure of these natural systems, while also extending the process not only to inference but to building predictions. I divided this work in three research projects; for the first one I developed a hierarchical Bayesian model for age-specific survival for long lived species with capture-recapture data that allows the use of incomplete data (i.e. left-truncated and right-censored), and builds predictions of years of birth and death for all individuals while also drawing inference on the survivorship function. I compared this method to more traditional ones and address their limitations and advantages. My second research chapter makes use of this method to determine the age-specific survivorship of the Dry Tortugas sooty tern population, and explores the effect of changes in sea surface temperature on their cohort mortality rates. Finally, my third research chapter addresses the dramatic shift in breeding season experienced by the Dry Tortugas sooty tern colony, the most unprecedented shift reported for any bird species. I explore the role of climatic and weather variables as triggering mechanisms.

Understanding how tropical forests respond to changes in the abiotic environment and human disturbance is critical for preserving biodiversity, mitigating climate change, and maintaining ecosystem services in the coming century. The lowland rainforests of Central Africa in particular are expected to lose 41% of present dense forest cover in the next 50 years to forest clearing, due in large part to forest loss resulting from the expansion of subsistence agriculture and logging. Deforestation also contributes a net increase in carbon dioxide to the atmosphere, exacerbating forest losses via increased tree mortality from drought, fire, and dispersal failure. Despite these grim circumstances, we know little about how Paleotropical tree communities are likely to respond to predicted changes in disturbance and climate.

To evaluate the unique response of Afrotropical forests to changes in the abiotic environment and disturbance, I employ diverse data including species inventories, seed rain, species traits, remotely sensed historic climatic data, future climate predictions, and soil nutrient data collected from 134 1-ha plots arrayed in two large-scale observational experiments spanning the central African countries of Gabon and the Republic of Congo (Brazzaville). I then combine these diverse data using novel modeling methods to 1) determine the relative roles of climate and human disturbance on tree community composition, 2) quantify the relative effects of human disturbance and the abiotic environment on tree fecundity and seed dispersal, and 3) forecast future tree community change given predicted changes in climate.

This work demonstrates that Afrotropical plant communities are more sensitive to human disturbance than to climate, with particular sensitivities to hunting and distance to village (a proxy for other human activities, including tree-cutting, gathering, etc.). These pressures have meaningful long-term effects on seed dispersal, increasing dispersal distances for animal dispersed seeds in disturbed forests. Finally, We forecast a 3 - 8% decrease in Afrotropical forest species richness by the end of the century, in contrast to the 30-50% loss of plant diversity predicted to occur with equivalent warming in the Neotropics.

This work reveals that community forecasts are not generalizable across regions, and more representative studies are needed in understudied biomes like the Afrotropics. Nascent data sets, increased availability of high quality remote sensing data, and new statistical techniques capable of synthesizing these various data will help in further resolving the fate of the world’s ecosystems. This study serves as an important counterpoint to work done in the Neotropics by providing contrasting predictions for Afrotropical forests with substantially different ecological, evolutionary, and anthropogenic histories.

Understanding how tropical forests respond to changes in the abiotic environment and human disturbance is critical for preserving biodiversity, mitigating climate change, and maintaining ecosystem services in the coming century. The lowland rainforests of Central Africa in particular are expected to lose 41% of present dense forest cover in the next 50 years to forest clearing, due in large part to forest loss resulting from the expansion of subsistence agriculture and logging. Deforestation also contributes a net increase in carbon dioxide to the atmosphere, exacerbating forest losses via increased tree mortality from drought, fire, and dispersal failure. Despite these grim circumstances, we know little about how Paleotropical tree communities are likely to respond to predicted changes in disturbance and climate.

To evaluate the unique response of Afrotropical forests to changes in the abiotic environment and disturbance, I employ diverse data including species inventories, seed rain, species traits, remotely sensed historic climatic data, future climate predictions, and soil nutrient data collected from 134 1-ha plots arrayed in two large-scale observational experiments spanning the central African countries of Gabon and the Republic of Congo (Brazzaville). I then combine these diverse data using novel modeling methods to 1) determine the relative roles of climate and human disturbance on tree community composition, 2) quantify the relative effects of human disturbance and the abiotic environment on tree fecundity and seed dispersal, and 3) forecast future tree community change given predicted changes in climate.

This work demonstrates that Afrotropical plant communities are more sensitive to human disturbance than to climate, with particular sensitivities to hunting and distance to village (a proxy for other human activities, including tree-cutting, gathering, etc.). These pressures have meaningful long-term effects on seed dispersal, increasing dispersal distances for animal dispersed seeds in disturbed forests. Finally, We forecast a 3 - 8% decrease in Afrotropical forest species richness by the end of the century, in contrast to the 30-50% loss of plant diversity predicted to occur with equivalent warming in the Neotropics.

This work reveals that community forecasts are not generalizable across regions, and more representative studies are needed in understudied biomes like the Afrotropics. Nascent data sets, increased availability of high quality remote sensing data, and new statistical techniques capable of synthesizing these various data will help in further resolving the fate of the world’s ecosystems. This study serves as an important counterpoint to work done in the Neotropics by providing contrasting predictions for Afrotropical forests with substantially different ecological, evolutionary, and anthropogenic histories.

Over the next century, global change is expected to fundamentally alter ecological communities. Forecasting the consequences of this change requires an understanding of current drivers of ecosystem form and function, yet the scale of available data is often mismatched to the scale of the ecological processes of interest. In this dissertation, I employ novel statistical modeling on continent-spanning observational datasets, national forest inventories from temperate regions, with the aim to understand how forest communities may respond to future climate. In each chapter, the methodological focus on scale is conceptually linked with the ecological questions posed.

In the first two research chapters, we investigated the relationship between forest biomass and environment across stages of stand succession and levels of species richness. These complementary analyses both estimate that climate exerts strong controls on productivity, and that these controls are dependent on complex interactions. When these interactions are taken into account, we find that differences in plot-level productivity across levels of species richness are small in comparison to the effects of climate, disturbance, and forest management (Ch. 2). Chapter 3 takes a different approach to estimating biomass and biomass productivity through a forest structure framework. The forest structure approach estimates changes in water availability could be a dominant control on future forest biomass, but that the impacts of climate change may be spatially variable across the eastern U.S. because they depend on stand age.

Finally, we synthesized eight national forest inventory datasets from North America and Western Europe to determine whether community-weighted mean (CWM) traits have congruent and predictable relationships with environment. Combining species-level mean traits extracted from the literature with a multivariate species distribution modeling approach, we show that variation in traits can be better explained by environmental covariates in North America than Western Europe. As a result, predictions of CWM traits on one continent based on the model fit from the other tend to have high predictive error and are weakly correlated with observed values. We conclude that differences in evolutionary history and human management may weaken the generality of CWM trait responses to environment in temperate forests.

Overall, this dissertation offers insights into how temperate forests may respond to climate change. Bayesian hierarchical modeling is demonstrated to be an effective way to align the disparate scales between data and ecological process. From an ecological perspective, these results suggest that changes in climatic water availability and drought-related disturbances may be the dominant force driving the function of future temperate forests.

The effects of climate change on forest dynamics will be determined by tree responses at different life-stages and different scales -- from establishment to maturity and from individuals to populations. Studies incorporating local factors, such as natural enemies, competition, or tree physiology, with sufficient variation in climate are lacking. The importance of global and regional climate variation vs. local conditions and responses is poorly understood and may only be addressed with large datasets capturing sufficient environmental variation. This dissertation uses several large datasets to examine tree demographic and ecophysiological responses to light, moisture, predation, and climate in eastern temperate forests of North Carolina.

First, I use a 19-yr seed rain record from 13 forest plots in the piedmont, transition zone, and mountains to examine how climate-mediated seed maturation and density-dependent seed predation processes increase population reproductive variation in nine temperate tree species (Chapter 1). I address several hypotheses explaining interannual reproductive variation, such as resource matching, predator satiation, and pulse resource dynamics. My results indicate that (1) interannual reproductive variation increased as a result of seed maturation and seed predation processes, (2) seed maturation rates increased under warm, wet conditions, and (3) seed predation rates exhibited negative and positive density-dependence, depending of tree species and type of seed predator (specialist insects vs. generalist vertebrates). Because positive density-dependent seed predation dampened and negative density-dependent seed predation amplified the effects of climate-mediated maturation on reproductive variation, this study showed evaluations of tree reproduction need to incorporate both climate and seed predation.

Next, I use an 11-yr record of annual tree seedling growth and survival in 20 tree species planted in the piedmont and mountains to quantify individual tree seedling growth and survival responses to spatial variation in resources and temporal variation in climate (Chapter 2). First, I tested whether height-mediated growth provides an advantage to large individuals in all environments by amplifying responses to light and moisture or only when those resources were plentiful. Second, I tested whether allometric and survival responses differed among species based on life-history strategies. Individual height amplified tree seedling growth. However, some species exhibited amplification at moderate to high resource levels as well as depression of growth in large individuals growing in low light and moisture environments. Shade intolerant species exhibited an increasing ratio of height to diameter growth and increasing survival probability with both increasing light and moisture resources. Conversely, shade tolerant species exhibited decreasing height to diameter ratio with increasing light, possibly because of biomass allocation toward acquisition of limiting light resources. Despite relative small effects of drought and winter temperature of tree seedling demography, the results of this study indicate that individual tree seedlings sensitive to light and moisture environments, such as large seedlings and seedlings of shade intolerant species, growing in shaded or xeric sites may be particularly vulnerable to climate induced mortality.

Finally, I examine interannual and interspecific variation in canopy conductance using four years of environmental (vapor pressure deficit, above canopy light, and soil moisture) and stem sap flux data from heat dissipation probes for six co-occurring tree species. I developed a state-space modeling framework for predicting canopy conductance and transpiration which incorporates uncertainty in canopy and observation uncertainty. This approach is used to evaluate the degree to which co-occur deciduous tree species exhibited drought tolerating and drought avoiding canopy responses and whether these patterns were maintained in the face of interannual variation in environmental drivers. Comparisons of canopy conductance responses to environmental forcing across species and years highlighted the importance of tree sensitivity to moisture limitation, both in terms of high vapor pressure deficit and low soil moisture, and tree hydraulic characteristics within diverse forest communities. The state-space model produced similar parameter estimates to the more traditional boundary line analysis, performed well in terms of in-sample and out-of-sample prediction of sap flux observations, and provided for coherent incorporation of parameter, process, and observation errors in predicting missing data (i.e., gap-filling), canopy conductance, and transpiration.

Much needs to be learned about forest community responses to climate change, however these responses depend on local growing conditions (light and moisture), the life-stage being examined (seedlings, juveniles, or mature trees), and the scale of inference (individuals, canopies, or populations). Because climate change will not occur in isolation from other factors, such as stand age or disturbance, studies must characterize tree responses across multidimensional gradients in growing conditions. This dissertation addresses these challenges using large demographic and ecophysiological datasets well-suited for global change research.

Forests change with changes in their environment based on the physiological responses of individual trees. These short-term reactions have cumulative impacts on long-term demographic performance. For a tree in a forest community, success depends on biomass growth to capture above- and belowground resources and reproductive output to establish future generations. Here we examine aspects of how forests respond to changes in moisture and light availability and how these responses are related to tree demography and physiology.

First we address the long-term pattern of tree decline before death and its connection with drought. Increasing drought stress and chronic morbidity could have pervasive impacts on forest composition in many regions. We use long-term, whole-stand inventory data from southeastern U.S. forests to show that trees exposed to drought experience multiyear declines in growth prior to mortality. Following a severe, multiyear drought, 72% of trees that did not recover their pre-drought growth rates died within 10 years. This pattern was mediated by local moisture availability. As an index of morbidity prior to death, we calculated the difference in cumulative growth after drought relative to surviving conspecifics. The strength of drought-induced morbidity varied among species and was correlated with species drought tolerance.

Next, we investigate differences among tree species in reproductive output relative to biomass growth with changes in light availability. Previous studies reach conflicting conclusions about the constraints on reproductive allocation relative to growth and how they vary through time, across species, and between environments. We test the hypothesis that canopy exposure to light, a critical resource, limits reproductive allocation by comparing long-term relationships between reproduction and growth for trees from 21 species in forests throughout the southeastern U.S. We found that species had divergent responses to light availability, with shade-intolerant species experiencing an alleviation of trade-offs between growth and reproduction at high light. Shade-tolerant species showed no changes in reproductive output across light environments.

Given that the above patterns depend on the maintenance of transpiration, we next developed an approach for predicting whole-tree water use from sap flux observations. Accurately scaling these observations to tree- or stand-levels requires accounting for variation in sap flux between wood types and with depth into the tree. We compared different models with sap flux data to test the hypotheses that radial sap flux profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in new settings. We outline a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies.

Finally, we estimated tree water balances during drought with a statistical time-series analysis. Moisture limitation in forest stands comes predominantly from water use by the trees themselves, a drought-stand feedback. We show that drought impacts on tree fitness and forest composition can be predicted by tracking the moisture reservoir available to each tree in a mass balance. We apply this model to multiple seasonal droughts in a temperate forest with measurements of tree water use to demonstrate how species and size differences modulate moisture availability across landscapes. As trees deplete their soil moisture reservoir during droughts, a transpiration deficit develops, leading to reduced biomass growth and reproductive output.

This dissertation draws connections between the physiological condition of individual trees and their behavior in crowded, diverse, and continually-changing forest stands. The analyses take advantage of growing data sets on both the physiology and demography of trees as well as novel statistical techniques that allow us to link these observations to realistic quantitative models. The results can be used to scale up tree measurements to entire stands and address questions about the future composition of forests and the land’s balance of water and carbon.

Understanding the ecological and evolutionary responses of plant species to shifts in climate (and other rapid environmental perturbations) will require an improved knowledge of interactions between ecological and evolutionary processes as mediated by reproduction and gene flow. This dissertation research examines the processes of seed dispersal, intra- and inter-specific gene flow, and reproductive success in two red oak populations in North Carolina; the variation in these processes from site to site; and their influence on genetic structure, population dynamics, and migration potential.

Using genetic and ecological data collected from two large long-term study sites, I develop a hierarchical Bayesian model to identify the parents of sampled seedlings and characterize the scale of effective seed and pollen dispersal. I examine differences in scale of dispersal between the Appalachian and Piedmont sites in light of the spatial genetic structure and ecological differences of the two sites. I then use the pedigree and dispersal estimates derived from these analyses to examine variation in reproductive success and to test hypotheses about the causes and consequences of such variation. Using parentage estimates and measures of genetic differentiation between species, I study the likely extent of hybridization in these mixed-species secondary forests. Finally, using the SLIP stand simulator, I explore the implications of new genetic dispersal estimates for migration potential in oaks.

I find that effective seed dispersal distances are longer than estimated using seed trap data. While at the Piedmont site the large number of seedling found >100 m from their mother trees suggests that animal dispersers play a vital role, at the Appalachian site seedling distributions conform more closely to the original gravity-created pattern of seed density. Individual trees vary widely in their reproductive success. Seedling production was found to be positively associated with annual seed production, but exhibited hump-shaped or reversing relationships with age (suggesting the effect of senescence) and growth rate (suggesting tradeoffs in allocation). Germination fraction was negatively associated with fecundity, suggesting that density-dependent mortality may be acting on the high concentrations of seeds near highly fecund adults. Due to overlapping generations and variation in individual reproductive success, effective population size is estimated to be less than half the size that numbers of "adult" individuals would suggest, with consequences for the relative strength of drift and selection. Hybridization may boost effective population size somewhat; my analyses suggest that inter-specific gene flow is common at both study sites. Finally, simulations show that dispersal has a relatively stronger effect on migration rate and population growth than fecundity or size at maturity, and that genetic estimates of seed dispersal can yield significantly higher rates of migration and/or population persistence than seed-trap based estimates under both competitive and non-competitive conditions.