Bruce E. Kendall

WHY DO POPULATIONS CYCLE? A SYNTHESIS OF STATISTICAL AND MECHANISTIC MODELING APPROACHES

Population cycles have long fascinated ecologists. Even in the most-studied populations, however, scientists continue to dispute the relative importance of various potential causes of the cycles. Over the past three decades, theoretical ecologists have cataloged a large number of mechanisms that are capable of generating cycles in population models. At the same time, statisticians have developed new techniques both for characterizing time series and for fitting population models to time-series data. Both disciplines are now sufficiently advanced that great gains in understanding can be made by synthesizing these complementary, and heretofore mostly independent, quantitative approaches. In this paper we demonstrate how to apply this synthesis to the problem of population cycles, using both long-term population time series and the often-rich observational and experimental data on the ecology of the species in question. We quantify hypotheses by writing mathematical models that embody the interactions and forces that might cause cycles. Some hypotheses can be rejected out of hand, as being unable to generate even qualitatively appropriate dynamics. We finish quantifying the remaining hypotheses by estimating parameters, both from independent experiments and from fitting the models to the time-series data using modern statistical techniques. Finally, we compare simulated time series generated by the models to the observed time series, using a variety of statistical descriptors, which we refer to collectively as “probes.” The model most similar to the data, as measured by these probes, is considered to be the most likely candidate to represent the mechanism underlying the population cycles. We illustrate this approach by analyzing one of Nicholson’s blowfly populations, in which we know the “true” governing mechanism. Our analysis, which uses only a subset of the information available about the population, uncovers the correct answer, suggesting that this synthetic approach might be successfully applied to field populations as well.

LONGEVITY CAN BUFFER PLANT AND ANIMAL POPULATIONS AGAINST CHANGING CLIMATIC VARIABILITY

Both means and year-to-year variances of climate variables such as temperature and precipitation are predicted to change. However, the potential impact of changing climatic variability on the fate of populations has been largely unexamined. We analyzed multiyear demographic data for 36 plant and animal species with a broad range of life histories and types of environment to ask how sensitive their long-term stochastic population growth rates are likely to be to changes in the means and standard deviations of vital rates (survival, reproduction, growth) in response to changing climate. We quantified responsiveness using elasticities of the long-term population growth rate predicted by stochastic projection matrix models. Short-lived species (insects and annual plants and algae) are predicted to be more strongly (and negatively) affected by increasing vital rate variability relative to longer-lived species (perennial plants, birds, ungulates). Taxonomic affiliation has little power to explain sensitivity to increasing variability once longevity has been taken into account. Our results highlight the potential vulnerability of short-lived species to an increasingly variable climate, but also suggest that problems associated with short-lived undesirable species (agricultural pests, disease vectors, invasive weedy plants) may be exacerbated in regions where climate variability decreases.

The stochastic nature of larval connectivity among nearshore marine populations

Many nearshore fish and invertebrate populations are overexploited even when apparently coherent management structures are in place. One potential cause of mismanagement may be a poor understanding and accounting of stochasticity, particularly for stock recruitment. Many of the fishes and invertebrates that comprise nearshore fisheries are relatively sedentary as adults but have an obligate larval pelagic stage that is dispersed by ocean currents. Here, we demonstrate that larval connectivity is inherently an intermittent and heterogeneous process on annual time scales. This stochasticity arises from the advection of pelagic larvae by chaotic coastal circulations. This result departs from typical assumptions where larvae simply diffuse from one site to another or where complex connectivity patterns are created by transport within spatially complicated environments. We derive a statistical model for the expected variability in larval settlement patterns and demonstrate how larval connectivity varies as a function of different biological and physical processes. The stochastic nature of larval connectivity creates an unavoidable uncertainty in the assessment of fish recruitment and the resulting forecasts of sustainable yields.

Striking a Balance between Biodiversity Conservation and Socioeconomic Viability in the Design of Marine Protected Areas

The establishment of marine protected areas is often viewed as a conflict between conservation and fishing. We considered consumptive and nonconsumptive interests of multiple stakeholders (i.e., fishers, scuba divers, conservationists, managers, scientists) in the systematic design of a network of marine protected areas along Californias central coast in the context of the Marine Life Protection Act Initiative. With advice from managers, administrators, and scientists, a representative group of stakeholders defined biodiversity conservation and socioeconomic goals that accommodated social needs and conserved marine ecosystems, consistent with legal requirements. To satisfy biodiversity goals, we targeted 11 marine habitats across 5 depth zones, areas of high species diversity, and areas containing species of special status. We minimized adverse socioeconomic impacts by minimizing negative effects on fishers. We included fine-scale fishing data from the recreational and commercial fishing sectors across 24 fisheries. Protected areas designed with consideration of commercial and recreational fisheries reduced potential impact to the fisheries approximately 21% more than protected areas designed without consideration of fishing effort and resulted in a small increase in the total area protected (approximately 3.4%). We incorporated confidential fishing data without revealing the identity of specific fisheries or individual fishing grounds. We sited a portion of the protected areas near land parks, marine laboratories, and scientific monitoring sites to address nonconsumptive socioeconomic goals. Our results show that a stakeholder-driven design process can use systematic conservation-planning methods to successfully produce options for network design that satisfy multiple conservation and socioeconomic objectives. Marine protected areas that incorporate multiple stakeholder interests without compromising biodiversity conservation goals are more likely to protect marine ecosystems.

Dispersal, Environmental Correlation, and Spatial Synchrony in Population Dynamics.

Many species exhibit widespread spatial synchrony in population fluctuations. This pattern is of great ecological interest and can be a source of concern when the species is rare or endangered. Both dispersal and spatial correlations in the environment have been implicated as possible causes of this pattern, but these two factors have rarely been studied in combination. We develop a spatially structured population model, simple enough to obtain analytic solutions for the population correlation, that incorporates both dispersal and environmental correlation. We ask whether these two synchronizing factors contribute additively to the total spatial population covariance. We find that there is always an interaction between these two factors and that this interaction is small only when one or both of the environmental correlation and the dispersal rate are small. The interaction is opposite in sign to the environmental correlation; so, in the normal case of positive environmental correlation across sites, the population synchrony will be lower than predicted by simply adding the effects of dispersal and environmental correlation. We also find that population synchrony declines as the strength of population regulation increases. These results indicate that dispersal and environmental correlation need to be considered in combination as explanations for observed patterns of population synchrony.

COMPETITION, SEED LIMITATION, DISTURBANCE, AND REESTABLISHMENT OF CALIFORNIA NATIVE ANNUAL FORBS

Invasion by exotic species is a major threat to global diversity. The invasion of native perennial grasslands in California by annual species from the southern Mediter- ranean region is one of the most dramatic invasions worldwide. As a result of this invasion, native species are often restricted to low-fertility, marginal habitat. An understanding of the mechanisms that prevent the recolonization of the more fertile sites by native species is critical to determining the prospects for conservation and restoration of the native flora. We present the results of a five-year experiment in which we used seeding, burning, and mowing treatments to investigate the mechanisms that constrain native annuals to the marginal habitat of a Californian serpentine grassland. The abundance and richness of native species declined with increasing soil fertility, and there was no effect of burning or mowing on native abundance or richness in the absence of seeding. We found that native annual forbs were strongly seed limited; a single seeding increased abundance of native forbs even in the presence of high densities of exotic species, and this effect was generally discernable after four years. These results suggest that current levels of dominance by exotic species are not simply the result of direct competitive interactions, and that seeding of native species is necessary and may be sufficient to create viable populations of native annual species in areas that are currently dominated by exotic species.

Habitat structure and population persistence in an experimental community.

Understanding spatial population dynamics is fundamental for many questions in ecology and conservation. Many theoretical mechanisms have been proposed whereby spatial structure can promote population persistence, in particular for exploiter–victim systems (host–parasite/pathogen, predator–prey) whose interactions are inherently oscillatory and therefore prone to extinction of local populations. Experiments have confirmed that spatial structure can extend persistence, but it has rarely been possible to identify the specific mechanisms involved. Here we use a model-based approach to identify the effects of spatial population processes in experimental systems of bean plants (Phaseolus lunatus), herbivorous mites (Tetranychus urticae) and predatory mites (Phytoseiulus persimilis). On isolated plants, and in a spatially undivided experimental system of 90 plants, prey and predator populations collapsed; however, introducing habitat structure allowed long-term persistence. Using mechanistic models, we determine that spatial population structure did not contribute to persistence, and spatially explicit models are not needed. Rather, habitat structure reduced the success of predators at locating prey outbreaks, allowing between-plant asynchrony of local population cycles due to random colonization events.

Estimating individual contributions to population growth: evolutionary fitness in ecological time

Ecological and evolutionary change is generated by variation in individual performance. Biologists have consequently long been interested in decomposing change measured at the population level into contributions from individuals, the traits they express and the alleles they carry. We present a novel method of estimating individual contributions to population growth and changes in distributions of quantitative traits and alleles. An individuals contribution to population growth is an individuals realized annual fitness. We demonstrate how the quantities we develop can be used to address a range of empirical questions, and provide an application to a detailed dataset of Soay sheep. The approach provides results that are consistent with those obtained using lifetime estimates of individual performance, yet is substantially more powerful as it allows lifetime performance to be decomposed into annual survival and fecundity contributions.

Single-species models for many-species food webs.

Most species live in species-rich food webs; yet, for a century, most mathematical models for population dynamics have included only one or two species. We ask whether such models are relevant to the real world. Two-species population models of an interacting consumer and resource collapse to one-species dynamics when recruitment to the resource population is unrelated to resource abundance, thereby weakening the coupling between consumer and resource. We predict that, in nature, generalist consumers that feed on many species should similarly show one-species dynamics. We test this prediction using cyclic populations, in which it is easier to infer underlying mechanisms, and which are widespread in nature. Here we show that one-species cycles can be distinguished from consumer–resource cycles by their periods. We then analyse a large number of time series from cyclic populations in nature and show that almost all cycling, generalist consumers examined have periods that are consistent with one-species dynamics. Thus generalist consumers indeed behave as if they were one-species populations, and a one-species model is a valid representation for generalist population dynamics in many-species food webs.

The dual nature of community variability

Author(s): Micheli, Fiorenza; Cottingham, Kathryn L.; Bascompte, Jordi; Bjornstad, Ottar N.; Eckert, Ginny L.; Fischer, Janet M.; Keitt, Timothy H.; Kendall, Bruce E.; Klug, Jennifer L.; Rusak, James A | Abstract: Community variability has a dual nature. On the one hand, there is compositional variability, changes in the relative abundance of component species. On the other hand, there is aggregate variability, changes in summary properties such as total abundance, biomass, or production. Although these two aspects of variability have received much individual attention, few studies have explicitly? related the compositional and aggregate variability of natural communities. In this paper, we show how simultaneous consideration of both aspects of community variability might advance our understanding of ecological communities.We use the distinction between compositional and aggregate variability to develop an organizational framework for describing patterns of community variability. At their extremes, compositional and aggregate variability combine in four different ways: (I) stasis, low compositional and low aggregate variability; (2) synchrony, low compositional and high aggregate variability; (3) asynchrony, high compositional and high aggregate variability; and (4) compensation, high compositional and low aggregate variability. Each of these patterns has been observed in natural communities, and can be linked to a suite of abiotic and biotic mechanisms. We give examples of the potential relevance of variability patterns to applied ecology, and describe the methodological developments needed to make meaningful comparisons of aggregate and compositional variability across communities. Finally, we provide two numerical examples of how our approach can be applied to natural communities.