Geology ReportsSearch

USGS · 70034364

Uni-directional consumer-resource theory characterizing transitions of interaction outcomes

Abstract

A resource is considered here to be a biotic population that helps to maintain the population growth of its consumers, whereas a consumer utilizes a resource and in turn decreases its growth rate. Bi-directional consumer–resource (C–R) interactions have been the object of recent theory. In these interactions, each species acts, in some respects, as both a consumer and a resource of the other, which is the basis of many mutualisms. In uni-directional C–R interactions between two species, one acts as a consumer and the other as a material and/or energy resource, while neither acts as both. The relationship between insect pollinator/seed parasites and the host plant is an example of the latter interaction type of C–R, as the insect provides no material resource to the plant (though it provides a pollination service). In this paper we consider a different variation of the uni-directional C–R interaction, in which the resource species has both positive and negative effects on the consumer species, while the consumer has only a negative effect on the resource. A predator–prey system in which the prey is able to kill or consume predator eggs or larvae is an example. Our aim is to demonstrate mechanisms by which interaction outcomes of this system vary with different conditions, and thus to extend the uni-directional C–R theory established by Holland and DeAngelis (2009) . By the analysis of a specific two-species system, it is shown that there is no periodic solution of the system, and the parameter (factor) space can be divided into six regions, which correspond to predation/parasitism, amensalism, and competition. The interaction outcomes of the system transition smoothly when the parameters are changed continuously in the six regions and/or initial densities of the species vary in a smooth fashion. Varying a pair of parameters can also result in the transitions. The analysis leads to both conditions under which the species approach their maximal densities, and explanations for phenomena in experiments by Urabe and Sterner (1996) .

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Y. Wang, D.L. DeAngelis, J.N. Holland. 2011. Uni-directional consumer-resource theory characterizing transitions of interaction outcomes. https://doi.org/10.1016/j.ecocom.2011.04.002

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

The practice of prediction: What can ecologists learn from applied, ecology-related fields?

The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.

Ecological Complexity

Tree island pattern formation in the Florida Everglades

The Florida Everglades freshwater landscape exhibits a distribution of islands covered by woody vegetation and bordered by marshes and wet prairies. Known as “tree islands”, these ecogeomorphic features can be found in few other low gradient, nutrient limited freshwater wetlands. In the last few decades, however, a large percentage of tree islands have either shrank or disappeared in apparent response to altered water depths and other stressors associated with human impacts on the Everglades. Because the processes determining the formation and spatial organization of tree islands remain poorly understood, it is still unclear what controls the sensitivity of these landscapes to altered conditions. We hypothesize that positive feedbacks between woody plants and soil accretion are crucial to emergence and decline of tree islands. Likewise, positive feedbacks between phosphorus (P) accumulation and trees explain the P enrichment commonly observed in tree island soils. Here, we develop a spatially-explicit model of tree island formation and evolution, which accounts for these positive feedbacks (facilitation) as well as for long range competition and fire dynamics. It is found that tree island patterns form within a range of parameter values consistent with field data. Simulated impacts of reduced water levels, increased intensity of drought, and increased frequency of dry season/soil consuming fires on these feedback mechanisms result in the decline and disappearance of tree islands on the landscape.

Florida

Persistence and diversity of directional landscape connectivity improves biomass pulsing in expanding and contracting wetlands

In flood-pulsed ecosystems, hydrology and landscape structure mediate transfers of energy up the food chain by expanding and contracting in area, enabling spatial expansion and growth of fish populations during rising water levels, and subsequent concentration during the drying phase. Connectivity of flooded areas is dynamic as waters rise and fall, and is largely determined by landscape geomorphology and anisotropy. We developed a methodology for simulating fish dispersal and concentration on spatially-explicit, dynamic floodplain wetlands with pulsed food web dynamics, to evaluate how changes in connectivity through time contribute to the concentration of fish biomass that is essential for higher trophic levels. The model also tracks a connectivity index (DCI) over different compass directions to see if fish biomass dynamics can be related in a simple way to topographic pattern. We demonstrate the model for a seasonally flood-pulsed, oligotrophic system, the Everglades, where flow regimes have been greatly altered. Three dispersing populations of functional fish groups were simulated with empirically-based dispersal rules on two landscapes, and two twelve-year time series of managed water levels for those areas were applied. The topographies of the simulations represented intact and degraded ridge-and-slough landscapes (RSL). Simulation results showed large pulses of biomass concentration forming during the onset of the drying phase, when water levels were falling and fish began to converge into the sloughs. As water levels fell below the ridges, DCI declined over different directions, closing down dispersal lanes, and fish density spiked. Persistence of intermediate levels of connectivity on the intact RSL enabled persistent concentration events throughout the drying phase. The intact landscape also buffered effects of wet season population growth. Water level reversals on both landscapes negatively affected fish densities by depleting fish populations without allowing enough time for them to regenerate. Testable, spatiotemporal predictions of the timing, location, duration, and magnitude of fish concentration pulses were produced by the model, and can be applied to restoration planning.

Ecological Complexity