DETECTION OF DENSITY DEPENDENCE REQUIRES DENSITY MANIPULATIONS AND CALCULATION OF λ

Population Regulation and Density-Dependent Demography in the Trinidadian Guppy

AbstractClassic theory for density-dependent selection for delayed maturation requires that a population be regulated through some combination of adult fecundity and/or juvenile survival. We tested whether those demographic conditions were met in four experimental populations of Trinidadian guppies in which delayed maturation of males evolved when the densities of those populations became high. We used monthly mark-recapture data to examine population dynamics and demography in these populations. Three of the four populations displayed clear evidence of regulation. In all four populations, monthly adult survival rates were independent of biomass density or actually increased with increased biomass density. Juvenile recruitment, which is a combination of adult fecundity and juvenile survival, decreased as biomass density increased in all four populations. Demography showed marked seasonality, with greater survival and higher recruitment in the dry season than the wet season. Population regulation via juvenile recruitment supports the hypothesis that density-dependent selection was responsible for the evolution of delayed maturity in males. This body of work represents one of the few complete tests of density-dependent selection theory.

The Capacity of Freshwater Ecosystems to Recover from Exceedences of Aquatic Life Criteria

In the United States, national chemical water quality criteria for the protection of aquatic life assume that aquatic ecosystems have sufficient resiliency to recover from criteria exceedences occurring up to once every 3 years. This resiliency assumption was critically reviewed through two approaches: (1) synthesis of case studies, and (2) population modeling. The population modeling examined differences in recovery of species with widely different life histories. One invertebrate (Hyalella azteca) and four fish species were modeled (fathead minnow, brook trout, lake trout, and shortnose sturgeon) with various disturbance magnitudes and intervals. The synthesis of ecosystem case studies showed generally faster recoveries for insect communities rather than fish, and recoveries from pulse (acute) disturbances were often faster than recoveries from press (chronic) disturbances. When the recovery dataset excluded severe disturbances that seemed unrepresentative of common facility discharge upsets that might cause criteria exceedences, the median recovery time was 1 year, 81% of the cases were considered recovered within 3 years, and 95% were considered recovered within 10 years. The modeling projected that short-lived fish species with high recovery times could thrive despite enduring 50% mortality disturbances every other year. However, long-lived fish species had longer recovery times and declined under the one disturbance every 3 years scenario. Overall, the analyses did not refute the long-standing judgements that 3 years is generally sufficient for recovery from nonrepetitive, moderate intensity disturbances of a magnitude up to 2× the chronic criteria in waters without other pollution sources or stresses. However, these constraints may not always be met and if long-lived fish species are a concern, longer return intervals such as 5-10 years could be indicated. Environ Toxicol Chem 2022;41:2887-2910. Published 2022. This article is a U.S. Government work and is in the public domain in the USA.

Density-Dependent Adaptive Topography in a Small Passerine Bird, the Collared Flycatcher

AbstractAdaptive topography is a central concept in evolutionary biology, describing how the mean fitness of a population changes with gene frequencies or mean phenotypes. We use expected population size as a quantity to be maximized by natural selection to show that selection on pairwise combinations of reproductive traits of collared flycatchers caused by fluctuations in population size generated an adaptive topography with distinct peaks often located at intermediate phenotypes. This occurred because r- and K-selection made phenotypes favored at small densities different from those with higher fitness at population sizes close to the carrying capacity K. Fitness decreased rapidly with a delay in the timing of egg laying, with a density-dependent effect especially occurring among early-laying females. The number of fledglings maximizing fitness was larger at small population sizes than when close to K. Finally, there was directional selection for large fledglings independent of population size. We suggest that these patterns can be explained by increased competition for some limiting resources or access to favorable nest sites at high population densities. Thus, r- and K-selection based on expected population size as an evolutionary maximization criterion may influence life-history evolution and constrain the selective responses to changes in the environment.

The Net Effect of Functional Traits on Fitness

Generalizing the effect of traits on performance across species may be achievable if traits explain variation in population fitness. However, testing relationships between traits and vital rates to infer effects on fitness can be misleading. Demographic trade-offs can generate variation in vital rates that yield equal population growth rates, thereby obscuring the net effect of traits on fitness. To address this problem, we describe a diversity of approaches to quantify intrinsic growth rates of plant populations, including experiments beyond range boundaries, density-dependent population models built from long-term demographic data, theoretical models, and methods that leverage widely available monitoring data. Linking plant traits directly to intrinsic growth rates is a fundamental step toward rigorous predictions of population dynamics and community assembly.

Where Is Natural History in Ecological, Evolutionary, and Behavioral Science?

Natural history is the careful observation of nature, wherever nature is. Ultimately, it is what ecological, evolutionary, and behavioral science are supposed to explain. It is difficult to use natural history alone to test hypotheses in these fields because of the complex paths between process and pattern. Few patterns are predicted by one and only one hypothesis, so experiments are almost always necessary. However, the robustness of experimental results depends on how well experimental conditions reflect the integration of natural history. Natural history also plays a vital role in how well we can apply Krogh's principle to our work. Krogh's principle is that scientists begin with an important hypothesis and find a system (organism, habitat, species interaction) with which to test it. However, natural history is essential for knowing whether the question applies to the system or whether we are forcing the question on the system. There is value in beginning one's research not by identifying an interesting question and searching for the right system but by identifying an interesting system in which to ask the right question. This approach carries the danger of parochialism, which can be avoided only by having a command of theory as well as natural history. A command of both areas allows nature to tell us which question to ask instead of demanding that nature answer the question we find most interesting.

A critical appraisal of population viability analysis

Population viability analysis (PVA) is useful in management of imperiled species. Applications range from research design, threat assessment, and development of management frameworks. Given the importance of PVAs, it is essential that they be rigorous and adhere to widely accepted guidelines; however, the quality of published PVAs is rarely assessed. We evaluated the quality of 160 PVAs of 144 species of birds and mammals published in peer-reviewed journals from 1990 to 2017. We hypothesized that PVA quality would be lower with generic programs than with custom-built programs; be higher for those developed for imperiled species; change over time; and be higher for those published in journals with high impact factors (IFs). Each included study was evaluated based on answers to an evaluation framework containing 32 questions reflecting whether and to what extent the PVA study adhered to published PVA guidelines or contained important PVA components. All measures of PVA quality were generally lower for studies based on generic programs. Conservation status of the species did not affect any measure of PVA quality, but PVAs published in high IF journals were of higher quality. Quality generally declined over time, suggesting the quantitative literacy of PVA practitioners has not increased over time or that PVAs developed by unskilled users are being published in peer-reviewed journals. Only 18.1% of studies were of high quality (score >75%), which is troubling because poor-quality PVAs could misinform conservation decisions. We call for increased scrutiny of PVAs by journal editors and reviewers. Our evaluation framework can be used for this purpose. Because poor-quality PVAs continue to be published, we recommend caution while using PVA results in conservation decision making without thoroughly assessing the PVA quality.

Hierarchical modeling strengthens evidence for density dependence in observational time series of population dynamics

The extent to which populations in nature are regulated by density-dependent processes is unresolved. While experiments increasingly find evidence of strong density dependence, unmanipulated population time series yield much more ambiguous evidence of regulation, especially when accounting for effects of observation error. Here, we reexamine the evidence for density dependence in time series of population sizes in nature, by conducting an aggregate analysis of the populations in the Global Population Dynamics Database (GPDD). First, following the conventional approach, we fit a density-dependent and a density-independent variant of the Gompertz state-space model to each time series. Then, we conduct an aggregate analysis of the entire database by considering two random-effects density-dependent models that leverage information across data sets. When individual time series are tested independently, we find very little evidence for density dependence. However, in the aggregate, we find very strong evidence for density dependence, even though, paradoxically, estimated strengths of density dependence for individual time series tend to be weaker than when each individual time series is analyzed independently. Furthermore, a hierarchical model that accounts for taxonomic variation in the strength of density dependence reveals that density dependence is consistently stronger in insects and fish than in birds and mammals. Our findings resolve apparent inconsistencies between observational and experimental studies of density dependence by revealing that the observational record does indeed contain strong support for the hypothesis that density dependence is widespread in nature.

Size and density mediate transitions between competition and facilitation

Species simultaneously compete with and facilitate one another. Size can mediate transitions along this competition-facilitation continuum, but the consequences for demography are unclear. We orthogonally manipulated the size of a focal species, and the size and density of a heterospecific neighbour, in the field using a model marine system. We then parameterised a size-structured population model with our experimental data. We found that heterospecific size and density interactively altered the population dynamics of the focal species. Size determined whether heterospecifics facilitated (when small) or competed with (when large) the focal species, while density strengthened these interactions. Such size-mediated interactions also altered the pace of the focal's life history. We provide the first demonstration that size and density mediate competition and facilitation from a population dynamical perspective. We suspect such effects are ubiquitous, but currently underappreciated. We reiterate classic cautions against inferences about competitive hierarchies made in the absence of size-specific data.

Native insect herbivory overwhelms context dependence to limit complex invasion dynamics of exotic weeds

Understanding the role of consumers in density-dependent plant population dynamics is a long-standing goal in ecology. However, the generality of herbivory effects across heterogeneous landscapes is poorly understood due to the pervasive influence of context-dependence. We tested effects of native insect herbivory on the population dynamics of an exotic thistle, Cirsium vulgare, in a field experiment replicated across eight sites in eastern Nebraska. Using hierarchical Bayesian analysis and density-dependent population models, we found potential for explosive low-density population growth (λ > 5) and complex density fluctuations under herbivore exclusion. However, herbivore access drove population decline (λ < 1), suppressing complex fluctuations. While plant-herbivore interaction outcomes are famously context-dependent, we demonstrated that herbivores suppress potentially invasive populations throughout our study region, and this qualitative outcome is insensitive to environmental context. Our novel use of Bayesian demographic modelling shows that native insect herbivores consistently prevent hard-to-predict fluctuations of weeds in environments otherwise susceptible to invasion.

Harvesting wildlife affected by climate change: a modelling and management approach for polar bears

The conservation of many wildlife species requires understanding the demographic effects of climate change, including interactions between climate change and harvest, which can provide cultural, nutritional or economic value to humans.We present a demographic model that is based on the polar bear Ursus maritimus life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity (K). Using this model, we develop a state-dependent management framework to calculate a harvest level that (i) maintains a population above its maximum net productivity level (MNPL; the population size that produces the greatest net increment in abundance) relative to a changing K, and (ii) has a limited negative effect on population persistence.Our density-dependent relationships suggest that MNPL for polar bears occurs at approximately 0·69 (95% CI = 0·63-0·74) of K. Population growth rate at MNPL was approximately 0·82 (95% CI = 0·79-0·84) of the maximum intrinsic growth rate, suggesting relatively strong compensation for human-caused mortality.Our findings indicate that it is possible to minimize the demographic risks of harvest under climate change, including the risk that harvest will accelerate population declines driven by loss of the polar bear's sea-ice habitat. This requires that (i) the harvest rate - which could be 0 in some situations - accounts for a population's intrinsic growth rate, (ii) the harvest rate accounts for the quality of population data (e.g. lower harvest when uncertainty is large), and (iii) the harvest level is obtained by multiplying the harvest rate by an updated estimate of population size. Environmental variability, the sex and age of removed animals and risk tolerance can also affect the harvest rate. Synthesis and applications. We present a coupled modelling and management approach for wildlife that accounts for climate change and can be used to balance trade-offs among multiple conservation goals. In our example application to polar bears experiencing sea-ice loss, the goals are to maintain population viability while providing continued opportunities for subsistence harvest. Our approach may be relevant to other species for which near-term management is focused on human factors that directly influence population dynamics within the broader context of climate-induced habitat degradation.

Local environment and density-dependent feedbacks determine population growth in a forest herb

Linking spatial variation in environmental factors to variation in demographic rates is essential for a mechanistic understanding of the dynamics of populations. However, we still know relatively little about such links, partly because feedbacks via intraspecific density make them difficult to observe in natural populations. We conducted a detailed field study and investigated simultaneous effects of environmental factors and the intraspecific density of individuals on the demography of the herb Lathyrus vernus. In regression models of vital rates we identified effects associated with spring shade on survival and growth, while density was negatively correlated with these vital rates. Density was also negatively correlated with average individual size in the study plots, which is consistent with self-thinning. In addition, average plant sizes were larger than predicted by density in plots that were less shaded by the tree canopy, indicating an environmentally determined carrying capacity. A size-structured integral projection model based on the vital rate regressions revealed that the identified effects of shade and density were strong enough to produce differences in stable population sizes similar to those observed in the field. The results illustrate how the local environment can determine dynamics of populations and that intraspecific density may have to be more carefully considered in studies of plant demography and population viability analyses of threatened species. We conclude that demographic approaches incorporating information about both density and key environmental factors are powerful tools for understanding the processes that interact to determine population dynamics and abundances.

Effects of density and fire on the vital rates and population growth of a perennial goldenaster

In a novel analysis, a regression-design life-table response experiment was used to determine how the interaction of fire and density affected vital rates of the perennial composite Pityopsis aspera, and ultimately how these changes in vital rates contributed to differences in estimated population growth rates.

Intraspecific density effects are generally associated with other factors, like disturbance. Therefore, the ways in which density effects might interact with disturbance to modify the relationships between vital rates and population growth must be understood. I quantified the effects of density on the life-history stages of the perennial composite Pityopsis aspera over 3 years, the span of which included years in which fire did and did not occur. In an experimental study, I estimated the survival, growth and reproduction for shoots in plots established across a natural range of densities in Florida, USA. In a novel analysis, a regression-design life-table response experiment was used to determine which transitions were associated with density, how they contributed to differences in estimated population growth rates and how this relationship differed as a result of fire. The shape of the relationship between population growth rate (λ) and density was modified by fire, primarily as a result of contributions from adult flowering stasis and survival, and first-year survival probabilities. Fire modified and even reversed the effect of extreme densities on adult flowering stasis and survival and of first-year survival, resulting in more positive contributions from these transitions to λ at the lowest and highest density values. These results demonstrate the first application of a regression-design life-table response experiment to elucidating the interactive effects of density and fire. They highlight the utility of this approach for both capturing the complex dynamics of populations and establishing a means of determining how vital rates might contribute to differences in demography across densities.

Decoupling of component and ensemble density feedbacks in birds and mammals

A component density feedback represents the effect of change in population size on single demographic rates, whereas an ensemble density feedback captures that effect on the overall growth rate of a population. Given that a population's growth rate is a synthesis of the interplay of all demographic rates operating in a population, we test the hypothesis that the strength of ensemble density feedback must augment with increasing strength of component density feedback, using long-term censuses of population size, fertility, and survival rates of 109 bird and mammal populations (97 species). We found that compensatory and depensatory component feedbacks were common (each detected in approximately 50% of the demographic rates). However, component feedback strength only explained <10% of the variation in ensemble feedback strength. To explain why, we illustrate the different sources of decoupling between component and ensemble feedbacks. We argue that the management of anthropogenic impacts on populations using component feedbacks alone is ill-advised, just as managing on the basis of ensemble feedbacks without a mechanistic understanding of the contributions made by its components and environmental variability can lead to suboptimal decisions.

Temporal variation in the carrying capacity of a perennial grass population

Density dependence and, therefore, K (carrying capacity, equilibrium population size) are central to understanding and predicting changes in population size (N). Although resource levels certainly fluctuate, K has almost always been treated as constant in both theoretical and empirical studies. We quantified temporal variation in K by fitting extensions of standard population dynamic models to 16 annual censuses of a population of the perennial bunchgrass Bouteloua rigidiseta. Variable-K models provided substantially better fits to the data than did models that varied the potential rate of population increase. The distribution of estimated values of K was skewed, with a long right tail (i.e., a few "jackpot" years). The population did not track K closely. Relatively slow responses to changes in K combined with large, rapid changes in K sometimes caused N to be far from K. In 13%-20% of annual intervals, K was so much larger than N that the population's dynamics were best described by geometric growth and the population was, in effect, unregulated. Explicitly incorporating temporal variation in K substantially improved the realism of models with little increase in model complexity and provided novel information about this population's dynamics. Similar methods would be applicable to many other data sets.

The ecogenetic link between demography and evolution: can we bridge the gap between theory and data?

Calls to understand the links between ecology and evolution have been common for decades. Population dynamics, i.e. the demographic changes in populations, arise from life history decisions of individuals and thus are a product of selection, and selection, on the contrary, can be modified by such dynamical properties of the population as density and stability. It follows that generating predictions and testing them correctly requires considering this ecogenetic feedback loop whenever traits have demographic consequences, mediated via density dependence (or frequency dependence). This is not an easy challenge, and arguably theory has advanced at a greater pace than empirical research. However, theory would benefit from more interaction between related fields, as is evident in the many near-synonymous names that the ecogenetic loop has attracted. We also list encouraging examples where empiricists have shown feasible ways of addressing the question, ranging from advanced data analysis to experiments and comparative analyses of phylogenetic data.

THE SCALE AND CAUSE OF SPATIAL HETEROGENEITY IN STRENGTH OF TEMPORAL DENSITY DEPENDENCE

The importance of density dependence in natural communities continues to spark much debate because it is fundamental to population regulation. We used temporal manipulations of density to explore potentially stabilizing density dependence in early survivorship among six local populations of a tropical damselfish (Dascyllus flavicaudus). Specifically, we tested the premise that spatial heterogeneity in the strength of temporal density dependence would reflect variation in density of predators, the agent of mortality. Our field manipulations revealed that mortality among successive cohorts of young fishes was density dependent at each reef, but that its strength varied by approximately 1.5 orders of magnitude. This spatial heterogeneity was well predicted by variation among the six reefs in the density of predatory fishes that consume juvenile damselfishes. Because density dependence arose from competition for enemy-free space within a shelter coral, the mortality consequence of the competition depended on the neighborhood density of predators. Thus, the scale of heterogeneity in the density dependence largely reflected attributes of the environment that shaped the local abundance of predators. These results have important implications for how ecologists explore regulatory processes in nature. Failure to account for spatial variation could frequently yield misleading conclusions regarding density dependence as a stabilizing process, obscure underlying mechanisms influencing its strength, and provide no insight into the spatial scale of the heterogeneity. Further, models of population dynamics will be improved when experimental approaches better estimate the magnitude and causes of variation in strength of stabilizing density dependence.