Elizabeth E. Crone

Herbivory: effects on plant abundance, distribution and population growth

Plants are attacked by many different consumers. A critical question is how often, and under what conditions, common reductions in growth, fecundity or even survival that occur due to herbivory translate to meaningful impacts on abundance, distribution or dynamics of plant populations. Here, we review population-level studies of the effects of consumers on plant dynamics and evaluate: (i) whether particular consumers have predictably more or less influence on plant abundance, (ii) whether particular plant life-history types are predictably more vulnerable to herbivory at the population level, (iii) whether the strength of plant–consumer interactions shifts predictably across environmental gradients and (iv) the role of consumers in influencing plant distributional limits. Existing studies demonstrate numerous examples of consumers limiting local plant abundance and distribution. We found larger effects of consumers on grassland than woodland forbs, stronger effects of herbivory in areas with high versus low disturbance, but no systematic or unambiguous differences in the impact of consumers based on plant life-history or herbivore feeding mode. However, our ability to evaluate these and other patterns is limited by the small (but growing) number of studies in this area. As an impetus for further study, we review strengths and challenges of population-level studies, such as interpreting net impacts of consumers in the presence of density dependence and seed bank dynamics.

EDGE‐MEDIATED DISPERSAL BEHAVIOR IN A PRAIRIE BUTTERFLY

Animal responses to habitat boundaries will influence the effects of habitat fragmentation on population dynamics. Although this is an intuitive and often observed animal behavior, the influences of habitat boundaries have rarely been quantified in the field or considered in theoretical models of large scale processes. We quantified movement behavior of the Fenders blue butterfly (Icaricia icarioides fenderi) as a function of distance from host-plant patches. We measured the butterflys tendency to move toward habitat patches (bias) and their tendency to continue to move in the direction they were already going (correlation). We found that butterflies significantly modify their behavior within 10–22 m from the habitat boundary. We used these data to predict large scale patterns of residence time as a function of patch size, using three dispersal models: homogeneous response to habitat, heterogeneous response to habitat, and heterogeneous response to habitat with edge-mediated behavior. We simulated movement for males and females in eight patch sizes (0.1–8 ha) and asked how residence time varies among the models. We found that adding edge-mediated behavior significantly increases the residence of Fenders blue butterflies in their natal patch. Only the model with edge-mediated behavior for females was consistent with independent mark–release–recapture (MRR) estimates of residence time; other models dramatically underestimated residence times, relative to MRR data.

Landscape Restoration: Moving from Generalities to Methodologies

Abstract Large-scale, landscape-level restoration actions are widely implemented but receive little attention from academic ecologists. We review the methods used to assess the role of these processes in past studies, and suggest ways to use past and ongoing restoration activities to increase our understanding of large-scale processes and improve restoration projects. To make better use of past restoration, we recommend the use of a number of alternative analytical approaches that have become widely applied in conservation biology and wildlife management but have yet to be adopted in restoration ecology.

How do plant ecologists use matrix population models

Matrix projection models are among the most widely used tools in plant ecology. However, the way in which plant ecologists use and interpret these models differs from the way in which they are presented in the broader academic literature. In contrast to calls from earlier reviews, most studies of plant populations are based on < 5 matrices and present simple metrics such as deterministic population growth rates. However, plant ecologists also cautioned against literal interpretation of model predictions. Although academic studies have emphasized testing quantitative model predictions, such forecasts are not the way in which plant ecologists find matrix models to be most useful. Improving forecasting ability would necessitate increased model complexity and longer studies. Therefore, in addition to longer term studies with better links to environmental drivers, priorities for research include critically evaluating relative/comparative uses of matrix models and asking how we can use many short-term studies to understand long-term population dynamics.

Causes and consequences of variation in plant population growth rate: a synthesis of matrix population models in a phylogenetic context

Explaining variation in population growth rates is fundamental to predicting population dynamics and population responses to environmental change. In this study, we used matrix population models, which link birth, growth and survival to population growth rate, to examine how and why population growth rates vary within and among 50 terrestrial plant species. Population growth rates were more similar within species than among species; with phylogeny having a minimal influence on among-species variation. Most population growth rates decreased over the observation period and were negatively autocorrelated between years; that is, higher than average population growth rates tended to be followed by lower than average population growth rates. Population growth rates varied more through time than space; this temporal variation was due mostly to variation in post-seedling survival and for a subset of species was partly explained by response to environmental factors, such as fire and herbivory. Stochastic population growth rates departed from mean matrix population growth rate for temporally autocorrelated environments. Our findings indicate that demographic data and models of closely related plant species cannot necessarily be used to make recommendations for conservation or control, and that post-seedling survival and the sequence of environmental conditions are critical for determining plant population growth rate.

IS SURVIVORSHIP A BETTER FITNESS SURROGATE THAN FECUNDITY

Abstract Although fitness depends on both survivorship and fecundity, we tend to assume fecundity relates to fitness more directly than survivorship. In fact, several recent ecological studies suggest fitness depends more heavily on annual survivorship than annual fecundity for most taxa with lifespans longer than one year. These studies review elasticities of transition matrices for a broad range of taxa. Elasticities covary monotonically with selection gradients for demographic rates and are identical to selection gradients for traits rescaled to have mean values of zero and variance of one. For all taxa except semelparous perennial plants, adult survivorship has consistently higher elasticity than other suites of demographic rates. Fecundity only rarely has the highest elasticity. Thus, differences in yearly survival affect fitness disproportionately more than differences in yearly fecundity, even in many exponentially growing populations. This pattern reinforces the importance of interpreting the contribution of vital rates to fitness in the context of life history and population dynamics.

Testing Simple Indices of Habitat Proximity

Simple measures of habitat proximity made primarily on the basis of land cover are widely used in the ecological literature to infer habitat connectivity, or the potential for animal movement among resource patches. However, such indices rarely have been tested against observations of animal movement or against more detailed biological models. We developed a priori expectations as to the types of study systems and organisms for which various habitat proximity indices would be best suited. We then used data from three study systems and four species to test which, if any, of the indices were good predictors of population‐level responses. Our a priori expectations about index performance were not upheld. The indices that consider both habitat area and distance from the focal patch were highly correlated with each other, suggesting that they do index similar quantities. However, none of the indices performed well in predicting population response variables. The results suggest that the pattern of habitat cover alone may be insufficient to predict the process of animal movement.

How do plants know when other plants are flowering? Resource depletion, pollen limitation and mast-seeding in a perennial wildflower.

Mast-seeding is the synchronous and periodic reproduction by plant populations. This phenomenon has been widely studied from a community-level perspective, but we know extremely little about how plants are able to synchronize reproduction. Here, we present the first experimental test of proximate mechanisms of mast-seeding, by preventing reproduction in an iteroparous, mast-seeding wildflower. Through a series of experiments, we show that mobile carbohydrate stores (NSC) control alternate-year flowering by individual plants; seed set depletes NSC which prevents flowering the following year. Plants are synchronized by density-dependent pollen limitation; when plants flower asynchronously, they set fewer seeds, which prevents NSC depletion. Therefore, these individual plants flower in subsequent years and become synchronized. Because mast-seeding is a consequence of physiological controls of reproduction, differences in plant resource acquisition and allocation could dramatically change patterns of seed production, and changes in plant consumers and pollinators could change selection on physiological and developmental pathways.

Masting in whitebark pine (Pinus albicaulis) depletes stored nutrients

• In masting trees, synchronized, heavy reproductive events are thought to deplete stored resources and to impose a replenishment period before subsequent masting. However, direct evidence of resource depletion in wild, masting trees is very rare. Here, we examined the timing and magnitude (local vs individual-level) of stored nutrient depletion after a heavy mast event in Pinus albicaulis. • In 2005, the mast year, we compared seasonal changes in leaf and sapwood nitrogen (N) and phosphorus (P) concentrations and leaf photosynthetic rates in cone-bearing branches, branches that never produced cones, and branches with experimentally removed cones. We also compared nutrient concentrations in cone branches and branches that had never had cones between 2005 and 2006, and measured tree ring width and new shoot growth during 2005. • During the mast year, N or P depletion occurred only in tissue fractions of reproductive branches, where photosynthetic rates were reduced. However, by the end of the following year, nutrients were depleted in all branches, indicating individual-level resource depletion. New shoot and radial growth were not affected by masting. • We provide direct evidence that mast events in wild trees deplete stored nutrients. Our results highlight the importance of evaluating reproductive costs over time and at the individual level.

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.