Predicting phenological shifts in a changing climate.

Phenological shifts constitute one of the clearest manifestations of climate warming. Advanced emergence is widely reported in high-latitude ectotherms, but a significant number of species exhibit delayed, or no change in, emergence. Here we present a mechanistic theoretical framework that reconciles these disparate observations and predicts population-level phenological patterns based solely on data on temperature responses of the underlying life history traits. Our model, parameterized with data from insects at different latitudes, shows that peak abundance occurs earlier in the year when warming increases the mean environmental temperature, but is delayed when warming increases the amplitude of seasonal fluctuations. We find that warming does not necessarily lead to a longer activity period in high-latitude species because it elevates summer temperatures above the upper limit for reproduction and development. Our findings both confirm and confound expectations for ectotherm species affected by climate warming: an increase in the mean temperature is more detrimental to low-latitude species adapted to high mean temperatures and low-amplitude seasonal fluctuations; an increase in seasonal fluctuations is more detrimental to high-latitude species adapted to low mean temperatures and high-amplitude fluctuations.

The importance of the timescale of the fitness metric for estimates of selection on phenotypic traits during a period of demographic change.

Although fitness is central to the evolutionary process, metrics vary by timescale. Different timescales may give rise to different estimates of selection, especially during demographic transitions caused by rapid environmental and socioeconomic change. In this study, we used a dataset of a human population in Finland from 1775 to 1950 to compare two fitness metrics and their estimates of selection pressures, before and during a demographic transition. Both metrics, lifetime reproductive success and an annual metric of individual performance, declined while selection on the ages at first and last reproduction remained nearly constant, favouring individuals with wider reproductive windows. The ability to partition the annual metric into contributions from reproduction and survival revealed the short-term effects of a famine and the reversal of selection pressure via the survival component of annual fitness. Although the metrics generally agreed, the annual metric detected the effects of environmental variation and demographic change occurring within a generation.

The importance of individual developmental variation in stage-structured population models.

Population stage structure is fundamental to ecology, and models of this structure have proven useful in many different systems. Many ecological variables other than stage, such as habitat type, site occupancy and metapopulation status are also modelled using transitions among discrete states. Transitions among life stages can be characterised by the distribution of time spent in each stage, including the mean and variance of each stage duration and within-individual correlations among multiple stage durations. Three modelling traditions represent stage durations differently. Matrix models can be derived as a long-run approximation from any distribution of stage durations, but they are often interpreted directly as a Markov model for stage transitions. Statistical stage-duration distribution models accommodate the variation typical of cohort development data, but such realism has rarely been incorporated in population theory or statistical population models. Delay-differential equation models include lags but no variation, except in limited cases. We synthesise these models in one framework and illustrate how individual variation and correlations in development can impact population growth. Furthermore, different development models can yield the same long-term matrix transition rates but different sensitivities and elasticities. Finally, we discuss future directions for estimating realistic stage duration models from data.

An approximate Bayesian computation approach to parameter estimation in a stochastic stage-structured population model.

Complex population processes may require equally complex models, which can lead to analytically intractable estimation problems. Approximate Bayesian computation (ABC) is a computational tool for parameter estimation in situations where likelihoods cannot be computed. Instead of using likelihoods, ABC methods quantify the similarities between an observed data set and repeated simulations from a model. A practical obstacle to implementing an ABC algorithm is selecting summary statistics and distance metrics that accurately capture the main features of the data. We demonstrate the application of a sequential Monte Carlo ABC sampler (ABC SMC) to parameter estimation of a general stochastic stage-structured population model with ongoing reproduction and heterogeneity in development and mortality. Individual variation in demographic traits has considerable consequences for population dynamics in many systems, but including it in a population model by explicitly allowing stage durations to follow a realistic distribution creates a complex model. We applied the ABC SMC to fit the model to a simulated representative data set with known underlying parameters to evaluate the performance of the algorithm. We also introduced a systematic method for selecting summary statistics and distance metrics, using simulated data and receiver operating characteristic (ROC) curves from classification theory. Evaluations suggest that the approach is promising for model inference in our example of realistic stage-structured population models.

Synchrony of population dynamics of two vineyard arthropods occurs at multiple spatial and temporal scales.

When populations are synchronized, they rise and fall together. Analysis of population synchrony and its relationship to distance has played a major role in population ecology but has been absent from most studies of managed populations, such as agricultural arthropods. The extent to which populations at different locations are synchronized reflects the relative roles of shared environmental impacts, such as weather, and localizing processes, such as dispersal. The strength and pattern of synchrony, and the processes generating synchrony, have direct management implications. For the first time, we bring together two major paths of population-ecology research: spatial synchrony of population dynamics, which has been studied across birds, mammals, and insects, and spatial ecology of agricultural arthropod populations. We compare and contrast synchrony of two arthropod species, a spider mite and a leafhopper, across a vineyard region spanning 30-km distances, at within-year (weekly) and between-year time scales. Despite the enormous scope of agriculture, such long-term, large-scale data sets suitable for investigating local and regional dynamics are rare. For both species, synchrony is more strongly localized for annual peak abundance across 11 years than it typically is for weekly dynamics within each year's growing season. This suggests that between-year processes such as overwintering merit greater investigation. Within each year, both localized and region-wide synchrony was found for both species, but leafhoppers showed stronger localization than spider mites, corresponding to their longer generation time and stronger dispersal ability. This demonstrates that the overall herbivore dynamics of the system occur at multiple spatial scales and that the importance of different processes generating synchrony varies by species. The analysis includes new spatiotemporal randomization and bootstrap tests that can be applied to many systems. Our results highlight the value of large-scale, long-term monitoring programs for many kinds of managed populations. They also point toward the potential to test synchrony mechanisms more directly and to synthesize synchrony and landscape analyses.

Long transients in ecology: Theory and applications.

This paper discusses the recent progress in understanding the properties of transient dynamics in complex ecological systems. Predicting long-term trends as well as sudden changes and regime shifts in ecosystems dynamics is a major issue for ecology as such changes often result in population collapse and extinctions. Analysis of population dynamics has traditionally been focused on their long-term, asymptotic behavior whilst largely disregarding the effect of transients. However, there is a growing understanding that in ecosystems the asymptotic behavior is rarely seen. A big new challenge for theoretical and empirical ecology is to understand the implications of long transients. It is believed that the identification of the corresponding mechanisms along with the knowledge of scaling laws of the transient's lifetime should substantially improve the quality of long-term forecasting and crisis anticipation. Although transient dynamics have received considerable attention in physical literature, research into ecological transients is in its infancy and systematic studies are lacking. This text aims to partially bridge this gap and facilitate further progress in quantitative analysis of long transients in ecology. By revisiting and critically examining a broad variety of mathematical models used in ecological applications as well as empirical facts, we reveal several main mechanisms leading to the emergence of long transients and hence lays the basis for a unifying theory.

Evaluating the potential for prezygotic isolation and hybridization between landlocked and anadromous alewife (Alosa pseudoharengus) following secondary contact.

The recent increase in river restoration projects is altering habitat connectivity for many aquatic species, increasing the chance that previously isolated populations will come into secondary contact. Anadromous and landlocked alewife (Alosa pseudoharengus) are currently undergoing secondary contact as a result of a fishway installation at Rogers Lake in Old Lyme, Connecticut. To determine the degree of prezygotic isolation and potential for hybridization between alewife life history forms, we constructed spawning time distributions for two anadromous and three landlocked alewife populations using otolith-derived age estimates. In addition, we analyzed long-term data from anadromous alewife migratory spawning runs to look for trends in arrival date and spawning time. Our results indicated that anadromous alewife spawned earlier and over a shorter duration than landlocked alewife, but 3%-13% of landlocked alewife spawning overlapped with the anadromous alewife spawning period. The degree of spawning time overlap was primarily driven by annual and population-level variation in the timing of spawning by landlocked alewife, whereas the timing and duration of spawning for anadromous alewife were found to be relatively invariant among years in our study system. For alewife and many other anadromous fish species, the increase in fish passage river restoration projects in the coming decades will re-establish habitat connectivity and may bring isolated populations into contact. Hybridization between life history forms may occur when prezygotic isolating mechanisms are minimal, leading to potentially rapid ecological and evolutionary changes in restored habitats.

Transient phenomena in ecology.

The importance of transient dynamics in ecological systems and in the models that describe them has become increasingly recognized. However, previous work has typically treated each instance of these dynamics separately. We review both empirical examples and model systems, and outline a classification of transient dynamics based on ideas and concepts from dynamical systems theory. This classification provides ways to understand the likelihood of transients for particular systems, and to guide investigations to determine the timing of sudden switches in dynamics and other characteristics of transients. Implications for both management and underlying ecological theories emerge.

Small-scale intraspecific life history variation in herbivorous spider mites (Tetranychus pacificus) is associated with host plant cultivar.

Life history variation is a general feature of arthropod systems, but is rarely included in models of field or laboratory data. Most studies assume that local processes occur identically across individuals, ignoring any genetic or phenotypic variation in life history traits. In this study, we tested whether field populations of Pacific spider mites (Tetranychus pacificus) on grapevines (Vitis vinifera) display significant intraspecific life history variation associated with host plant cultivar. To address this question we collected individuals from sympatric vineyard populations where either Zinfandel or Chardonnay were grown. We then conducted a "common garden experiment" of mites on bean plants (Phaseolus lunatus) in the laboratory. Assay populations were sampled non-destructively with digital photography to quantify development times, survival, and reproductive rates. Two classes of models were fit to the data: standard generalized linear mixed models and a time-to-event model, common in survival analysis, that allowed for interval-censored data and hierarchical random effects. We found a significant effect of cultivar on development time in both GLMM and time-to-event analyses, a slight cultivar effect on juvenile survival, and no effect on reproductive rate. There were shorter development times and a trend towards higher juvenile survival in populations from Zinfandel vineyards compared to those from Chardonnay vineyards. Lines of the same species, originating from field populations on different host plant cultivars, expressed different development times and slightly different survival rates when reared on a common host plant in a common environment.