Due to habitat fragmentation, many of the populations in nature have been broken into smaller subpopulations that are connected by migration (i.e., metapopulation). Subpopulation synchrony within a metapopulation is of practical importance because it has consequences for the conservation of species. Moran effect and dispersal are the main causes of metapopulation synchrony, but spatial distribution of subpopulations has also been shows to influence synchrony and persistence in metapopulations. In population ecology, synchrony has been shown to negatively influence persistence in metapopulations. In chapter 1 of this dissertation, I review how synchrony is studied in ecology with the aim of identifying a unifying role of synchrony across ecological processes. In this chapter, I showed a novel framework for classifying synchrony across ecological processes. I referred to synchrony that is within a single trophic level as horizontal synchrony and synchrony that takes place between species at different trophic levels as vertical synchrony. This framework classified vertical synchrony into antagonistic synchrony (predator-prey and parasite-host) and synergetic synchrony (mutualism and commensalism). The horizontal synchrony was categorized as intraspecific synchrony (i.e., synchrony within a population), and interspecific synchrony (i.e., among species synchrony). In chapter 2, I ran theoretical simulations to investigate how spatial distribution of subpopulations (i.e., homogeneous vs heterogeneous metapopulation networks) influences persistence in metapopulations. I showed that there appears to be an intermediate optimal amount of heterogeneity but in my study intermediate and high heterogeneity were fairly similar and both were better for persistence than homogeneous metapopulation networks. I also showed that more dispersal appears to be more beneficial than less dispersal. In chapter 3, I ran theoretical simulations to investigate the role of positive (red noise) and negative (blue noise) autocorrelations of environmental variation in large heterogeneous metapopulation networks. I showed that the when the autocorrelation of environmental noise shifts from positive (red noise) to negative (blue noise), this may benefit the persistence of a species in large heterogeneous metapopulation networks. Higher dispersal between patches increased occupancy and persistence. Overall, this dissertation summarizes the role of synchrony in ecological interactions and could this be a useful resource for educational purposes. It also contributes to conservation science by allowing the conservationists involved in decision making to optimally design reserves under varying natural conditions.

Understanding species responses to climate change is a topic of increasing concern given climate change projections. Niche models evaluate species vulnerabilities to climate change using current locations to project future habitat suitability under climate scenarios. However, these models are simplified and ignore other factors such as life history traits, catastrophes, or variability of vital rates. Therefore, in these three studies, I have used spatially explicit metapopulation models to evaluate species responses to global changes and variability in vital rates. The first study linked metapopulation models including stochastic fire events with niche models to evaluate the response of an obligate fire seeding shrub to simultaneous altered fire frequencies and shifting habitat due to climate change. For this species, altered fire regimes greatly reduced expected minimum abundances (EMAs). Climate change, on the other hand, only negatively affected the species under extreme scenarios. Therefore, altered fire regimes were the bigger threat to the species. The second study integrated fecundity and survival information from a translocation experiment into metapopulation models incorporating habitat suitability changes from a niche model. While the niche model projected overall increases in habitat for the species, the metapopulation model projected declining abundances within currently occupied patches due to declines in habitat suitability. Increased fecundity and survival rates sometimes mitigated the impact of these declines. The third study was an extensive sensitivity analyses of metapopulation models for two species, one obligate fire seeding shrub and one resprouter. Changes in the variability and means of vital rates, as well as changes in fire regime, dispersal, and variability of carrying capacity were integrated in separate scenarios. The obligate seeder was more vulnerable to altered fire regimes while the resprouter was more vulnerable to changes in vital rates. Both species were sensitive to increased variation of carrying capacity. Overall, all of the three studies indicate increasing the complexity of models can change the direction of results, and that different factors are influential for different species. Species were vulnerable to altered fire regimes and vital rates in particular, while habitat suitability changes caused by climate change sometimes affected minimum abundances.

Species extinction is increasing due to anthropogenic threats such as climate change and land-use change. Thus, there is increasing interest in predicting the future fate of species and implementing effective management strategies. In this study, we used spatially-explicit stochastic population models to simulate future projections of three Monkeyflower species, Erythranthe cardinalis, Erythranthe lewisii, and Erythranthe guttata, under climate and land-use change in their regional habitat range in the California Floristic Province. We compared future population projections of two of the three Monkeyflower species, sub-divided into lower and higher elevation ranges, to examine the role of elevational differences in life history parameters in the persistence of the species under projected habitat changes. Lastly, due to the appearance of oscillations and declines in population trajectories of one Monkeyflower species, we explored the role of small, colonized patches on population trajectories. The modeling framework linked species distribution models (SDMs) with population models and dispersal modes parametrized with a combination of multi-year population census data, information from the literature, and publicly available environmental data, including temperature and precipitation projections under two climate scenarios and two climate models. Due to high population growth rates, all three species were limited by changes in habitat due to climate and land-use change. However, subpopulations of E. cardinalis had a low population growth rate at lower elevational ranges leading to extirpation in that region. Conversely, E. lewisii had a high population growth rate but experienced substantial declines in suitable habitat. In the population trajectories of E. lewisii, damped oscillations were observed stemming from a combination of high growth rates and colonization of new small patches which paradoxically reduced the overall population size across the metapopulation. This study highlights the importance of examining small-scale local spatial and demographic characteristics and dynamics, as opposed to large-scale regional habitat and population projections, in understanding the drivers of declines and extinction.

The spread of human settlement has imperiled fresh waterbodies; however, it has also led to the generation of novel water conservation strategies, including the reuse of treated wastewater, or effluent. Effluent reuse is an increasingly common aspect of watershed management, and thus far, research has been concentrated on its effects to water quality and efforts to describe effects to wildlife species have been relatively piecemealed. In this study, we evaluate the overlap between wastewater treatment plants and federal and state-listed endangered and threatened wildlife species in order to present a holistic view of the intersection of effluent and species management and the potential need for effluent considerations in species conservation. We show that there is substantial overlap between the presence of species and the presence of treatment plants in California watersheds, and with this overlap, a large potential for unintended consequences. As such, species conservation goals should be considered when making decisions related to effluent reuse.

Global biodiversity is fundamental for human welfare as ecosystem services, agricultural crops, and even human health depend on its preservation. Identifying strengths and shortcomings of current conservation risk assessment practices is of great importance given the current biodiversity crisis. Population viability analyses (PVA) are quantitative tools used to perform such risk assessments by modeling population dynamics. Variation in PVAs includes the type of population model used and the quantity and quality of the data available to parameterize the models. In this dissertation, I use computer simulations to evaluate the performance of two commonly used models (Matrix and Scalar) that have different data requirements. The first study evaluates the combined effects of environmental variability, measurement error and data quantity on the percent population decline estimates generated using matrix and scalar PVA for two different life histories. It was observed that measurement error has a stronger detrimental effect on projected decline than data quantity. Additionally, scalar models projected declines quite well relative to matrix models. The latter tend to be over-precautionary. The second study expanded the findings from the first by evaluating if the same results hold on a widely used decision-making framework—Red List Category of the International Union for the Conservation of Nature (IUCN). Results supported previous conclusions and provided evidence that scalar models can successfully be used in conservation decision-making with moderate levels of variability and uncertainty. The third study evaluates the reliability of population decline projections and their subsequent use in the Red List in the face of variability and uncertainty across life histories with different generation times. It was observed that increments in generation time could either increase or decrease the reliability of model predictions depending on the underlying growth rate. Specifically, both matrix and scalar models are more suitable for organisms with “slow” life histories than organisms with “fast” life histories. Overall, these studies highlight three important conclusions regarding the use of matrix and scalar models under high levels of variability and uncertainty: 1) percent population declines estimated with scalar models tend to be more accurate than for matrix models, 2) matrix models tend to over-estimate population declines, and 3) variability leads to greater errors in IUCN Red List classifications than measurement error for both models.

We review the roles that plant species traits and biogeography play in species’ exposure and vulnerability to decline or extinction under global change, focusing on separate and combined impacts of multiple threats – climate change, land-use change, and altered disturbance regimes. We establish a conceptual framework and research agenda for identifying the spatial characteristics of species ranges, as well as the life history and functional traits, that are associated with extinction risk for plant species with functional attributes emblematic of fire-prone, winter-precipitation Mediterranean-type ecosystems (MTEs). MTEs worldwide are characterized by their high plant diversity and unique floras, historical and contemporary high rates of land use change, and strong interactions between climate, fire, and land use. We focus on the California Floristic Province (CFP), an MTE that is a global plant diversity hotspot, and show how our framework can be used to understand the relationships between vulnerability to multiple global change drivers, species traits, and biogeography. Vulnerability can be assessed across species using linked distribution and population models that forecast plant responses to global change scenarios. Our overarching hypothesis is that species-specific vulnerability to global change in MTEs is a function of interactions between species and spatial traits: the nature of this interaction will depend on the type of global change process.