Kurt E. Anderson

WHAT DETERMINES THE STRENGTH OF A TROPHIC CASCADE

Trophic cascades have been documented in a diversity of ecological systems and can be important in determining biomass distribution within a community. To date, the literature on trophic cascades has focused on whether and in which systems cascades occur. Many biological (e.g., productivity : biomass ratios) and methodological (e.g., experiment size or duration) factors vary with the ecosystem in which data were collected, but ecosystem type, per se, does not provide mechanistic insights into factors controlling cascade strength. Here, we tested various hypotheses about why trophic cascades occur and what determines their magnitude using data from 114 studies that measured the indirect trophic effects of predators on plant community biomass in seven aquatic and terrestrial ecosystems. Using meta-analysis, we examined the relationship between the indirect effect of predator ma- nipulation on plants and 18 biological and methodological factors quantified from these studies. We found, in contrast to predictions, that high system productivity and low species diversity do not consistently generate larger trophic cascades. A combination of herbivore and predator metabolic factors and predator taxonomy (vertebrate vs. invertebrate) explained 31% of the variation in cascade strength among all 114 studies. Within systems, 18% of the variation in cascade strength was explained with similar predator and herbivore char- acteristics. Within and across all systems, the strongest cascades occurred in association with invertebrate herbivores and endothermic vertebrate predators. These associations may result from a combination of true biological differences among species with different phys- iological requirements and bias among organisms studied in different systems. Thus, al- though cascade strength can be described by biological characteristics of predators and herbivores, future research on indirect trophic effects must further examine biological and methodological differences among studies and systems.

Instream flow needs in streams and rivers: the importance of understanding ecological dynamics

Resource managers have traditionally had to rely on simple hydrological and habitat-association methods to predict how changes in river flow regimes will affect the viability of instream populations and communities. Yet these systems are characterized by dynamic feedbacks among system components, a high degree of spatial and temporal variability, and connectivity between habitats, none of which can be adequately captured in the commonly employed management methods. We argue that process-oriented ecological models, which consider dynamics across scales and levels of biological organization, are better suited to guide flow regime management. We review how ecological dynamics in streams and rivers are shaped by a combination of the flow regime and internal feedbacks, and proceed to describe ecological modeling tools that have the potential to characterize such dynamics. We conclude with a suggested research agenda to facilitate the inclusion of ecological dynamics into instream flow needs assessments.

INDUCED VS. CONSTITUTIVE RESISTANCE AND THE SPATIAL DISTRIBUTION OF INSECT HERBIVORES AMONG PLANTS

Because herbivores can move away from plants of low quality, induced resistance should affect the spatial distribution of herbivore damage (or herbivores) within or among plants. We used a spatially explicit simulation model and data from a field experiment to examine the effect of induced resistance on the distribution of herbivores and their damage among plants within a population. The model is appropriate only for rapid (as opposed to delayed) induced resistance, assumes that resistance affects herbivore behavior but not performance, and assumes no interplant communication. It is also appro- priate only for induced resistance that decays in the absence of herbivore damage. The simulation tracks herbivores on a linear array of plants or plant parts with reflecting bound- aries and allows manipulation of the timing of induced resistance and the initial distribution of herbivores. Our model suggests that increasing lags and thresholds for the production of induced resistance causes increasing aggregation of herbivores and their damage, but in the absence of either a lag or a threshold, induced resistance can lead to an even distribution of herbivores. The formation of even or aggregated distributions of herbivores depends not on initial distributions, but on the characteristics of the induced resistance. In the field experiment, we measured the degree of aggregation of Mexican bean beetle larvae among plants within experimental soybean populations consisting of soybean varieties that had no resistance (low constitutive, low inducible resistance), induced resistance (and low con- stitutive resistance), or constitutive resistance (and low inducible resistance). In general agreement with qualitative predictions of the model, we found that larvae on soybean varieties with induced resistance remained significantly more aggregated than larvae on varieties with no or high constitutive resistance.

On the estimation of dispersal kernels from individual mark-recapture data

We present a new method for estimating a distribution of dispersal displacements (a dispersal kernel) from mark-recapture data. One conventional method of calculating the dispersal kernel assumes that the distribution of displacements are Gaussian (e.g. resulting from a diffusion process) and that individuals remain within sampled areas. The first assumption prohibits an analysis of dispersal data that do not exhibit the Gaussian distribution (a common situation); the second assumption leads to underestimation of dispersal distance because individuals that disperse outside of sampling areas are never recaptured. Our method eliminates these two assumptions. In addition, the method can also accommodate mortality during a sampling period. This new method uses integrodifference equations to express the probability of spatial mark-recapture data; associated dispersal, survival, and recapture parameters are then estimated using a maximum likelihood method. We examined the accuracy of the estimators by applying the method to simulated data sets. Our method suggests designs for future mark-recapture experiments.

Population persistence in river networks.

Organisms inhabiting river systems contend with downstream biased flow in a complex tree-like network. Differential equation models are often used to study population persistence, thus suggesting resolutions of the ‘drift paradox’, by considering the dependence of persistence on such variables as advection rate, dispersal characteristics, and domain size. Most previous models that explicitly considered network geometry artificially discretized river habitat into distinct patches. With the recent exception of Ramirez (J Math Biol 65:919–942, 2012), partial differential equation models have largely ignored the global geometry of river systems and the effects of tributary junctions by using intervals to describe the spatial domain. Taking advantage of recent developments in the analysis of eigenvalue problems on quantum graphs, we use a reaction–diffusion–advection equation on a metric tree graph to analyze persistence of a single population in terms of dispersal parameters and network geometry. The metric graph represents a continuous network where edges represent actual domain rather than connections among patches. Here, network geometry usually has a significant impact on persistence, and occasionally leads to dramatically altered predictions. This work ranges over such themes as model definition, reduction to a diffusion equation with the associated model features, numerical and analytical studies in radially symmetric geometries, and theoretical results for general domains. Notable in the model assumptions is that the zero-flux interior junction conditions are not restricted to conservation of hydrological discharge.

Fire management, managed relocation, and land conservation options for long-lived obligate seeding plants under global changes in climate, urbanization, and fire regime.

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long-lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire-prone ecosystems, including the biodiversity hotspots of Mediterranean-type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long-lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land-use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land-use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored.

Directional biases and resource-dependence in dispersal generate spatial patterning in a consumer-producer model.

Directional dispersal plays a large role in shaping ecological processes in diverse systems such as rivers, coastlines and vegetation communities. We describe an instability driven by directional dispersal in a spatially explicit consumer-producer model where spatial patterns emerge in the absence of external environmental variation. Dispersal of the consumer has both undirected and directed components that are functions of producer biomass. We demonstrate that directional dispersal is required for the instability, while undirected diffusive dispersal sets a lower bound to the spatial scale of emerging patterns. Furthermore, instability requires indirect feedbacks affecting consumer per capita dispersal rates, and not activator-inhibitor dynamics affecting production and mortality as is described in previous theory. This novel and less-restrictive mechanism for generating spatial patterns can arise over realistic parameter values, which we explore using an empirically inspired model and data on stream macroinvertebrates.

LARGE-SCALE MOVEMENT PATTERNS BETWEEN SONG DIALECTS IN BROWN-HEADED COWBIRDS (MOLOTHRUS ATER)

Abstract Extensive past research has attempted to determine whether song dialects represent reproductively isolated social systems, with individuals tending to spend their entire lives in a single dialect. We addressed that issue by analyzing banding data for Brown-headed Cowbirds (Molothrus ater) on the eastern slope of the Sierra Nevada of California. For 14 years, 1,393 juveniles and 2,568 mature individuals were banded along a 40-km span encompassing three dialects. Of those juvenile and mature birds, 7.9% and 12.1%, respectively, were recaptured in a later year. All classes of mature birds (second-year males, older males, and females) had significantly higher recapture rates than birds banded as juveniles, but there were no differences among the mature classes. Overall, 22.7% of 110 juveniles recaptured in a subsequent year were trapped in a dialect region other than the one in which they were banded, as compared with 8.1% of 310 mature birds. Neither juvenile nor mature birds showed sex-related differences in proportions recaptured in subsequent years in different dialect regions. Birds in all sex-age classes were more likely to have moved to a new dialect region when recaptured in a subsequent year than when recaptured within the year, which suggests that apparent movements between years were cases of dispersal, rather than short-term foraging trips. Although our banding data cannot confirm gene flow, the high levels of movement they show agree with genetic and morphometric studies indicating high levels of gene flow among these cowbird dialects. Patrones de Movimiento de Gran Escala entre Dialectos del Canto de Molothrus ater

Spatial Scaling of Consumer‐Resource Interactions in Advection‐Dominated Systems

Ecologists studying consumer‐resource interactions in advection‐dominated systems such as streams and rivers frequently seek to link the results of small‐scale experiments with larger‐scale patterns of distribution and abundance. Accomplishing this goal requires determining the characteristic scale, termed the response length, at which there is a shift from local dynamics dominated by advective dispersal to larger‐scale dynamics dominated by births and deaths. Here, we model the dynamics of consumer‐resource systems in a spatially variable, advective environment and show how consumer‐resource interactions alter the response length relative to its single‐species value. For one case involving a grazer that emigrates in response to high predator density, we quantify the changes using published data from small‐scale experiments on aquatic invertebrates. Using Fourier analysis, we describe the responses of advection‐dominated consumer‐resource systems to spatially extended environmental variability in a way that involves explicit consideration of the response length. The patterns we derive for different consumer‐resource systems exhibit important similarities in how component populations respond to spatial environmental variability affecting dispersal as opposed to demographic parameters.

Combined influences of model choice, data quality, and data quantity when estimating population trends

Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in population risk assessments, but their combined impact has not been thoroughly investigated. We tested the ability of scalar and matrix PVA models to predict percent decline over a ten-year interval, selected to coincide with the IUCN Red List criterion A.3, using data simulated for a hypothetical, short-lived organism with a simple life-history and for a threatened snail, Tasmaphena lamproides. PVA performance was assessed across different time series lengths, population growth rates, and levels of process and measurement error. We found that the magnitude of effects of measurement error, process error, and time series length, and interactions between these, depended on context. We found that high process and measurement error reduced the reliability of both models in predicted percent decline. Both sources of error contributed strongly to biased predictions, with process error tending to contribute to the spread of predictions more than measurement error. Increasing time series length improved precision and reduced bias of predicted population trends, but gains substantially diminished for time series lengths greater than 10–15 years. The simple parameterization scheme we employed contributed strongly to bias in matrix model predictions when both process and measurement error were high, causing scalar models to exhibit similar or greater precision and lower bias than matrix models. Our study provides evidence that, for short-lived species with structured but simple life histories, short time series and simple models can be sufficient for reasonably reliable conservation decision-making, and may be preferable for population projections when unbiased estimates of vital rates cannot be obtained.