Interaction Assessment: A modeling tool for predicting population dynamics from field data

John M. Emlen; Jeffrey J. Duda; Matt D. Kirchhoff; D. Carl Freeman

doi:10.1016/j.ecolmodel.2005.07.012

Home/Archive/USGS

USGS · 70170962

Interaction Assessment: A modeling tool for predicting population dynamics from field data

John M. Emlen·Jeffrey J. Duda·Matt D. Kirchhoff·D. Carl Freeman

View original source ↗Export metadata ↓

Abstract

Interaction Assessment (INTASS) is a field and analytic methodology for constructing population dynamics models. Because data collected in generating a model for one species comprise much of the information needed for other species, a small increase in effort can result in simultaneous expressions for the dynamics of multiple species. These expressions can be used to simulate whole community responses to environmental change, including management actions. Since publication of the most recent paper in this series, the INTASS methodology has undergone a large number of developments. These include the use of conceptual models to direct field and modeling efforts and incorporation of an information theoretic approach to model selection. We review these modifications and additions, applying them to a population of Sitka black-tailed deer ( Odocoilius hemionis ) in Alaska and to cheatgrass ( Bromus tectorum ) at the Desert Experimental Range in Utah. In both cases, useful information about the species’ ecology and population trends was ascertained. INTASS is portable across a wide range of taxa, habitats and management situations.

Explore related subjects

Ecological Modelling Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

John M. Emlen, Jeffrey J. Duda, Matt D. Kirchhoff, D. Carl Freeman. 2006. Interaction Assessment: A modeling tool for predicting population dynamics from field data. https://doi.org/10.1016/j.ecolmodel.2005.07.012

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

KEEP EXPLORING

Related USGS reports

USGS2026

Modeling the temperature-mediated link between demography and biomass in ectotherms

Population models can forecast the effects of environmental change, disturbance, and management decisions on populations of interest. Most population models focus on abundance of individuals, but biomass may be a more relevant quantity at the community or ecosystem scale, especially when investigating interaction of multiple stressors and cross-ecosystem energy flows. We developed a stage-structured population model that integrates a temperature-mediated tradeoff between development rate and final body size of invertebrates, allowing projection of both population size and standing stock biomass in ecosystems that experience disturbances. We parameterized the model for four aquatic invertebrate life-history types spanning a range of lifespan and susceptibility to disturbance. We observed several emergent properties typical of invertebrate populations but not explicitly included in the model, including self-organization of cohort structure under seasonal environments, a tradeoff between lifespan duration and rate of post-disturbance population recovery, and chaotic population dynamics under high growth rates. Sensitivity analysis revealed that although elevated mean temperature increased population size, total population biomass remained unchanged or even decreased due to declining individual biomass, which has implications for ecosystem processes under a changing climate. The seasonal timing of disturbance showed a strong interaction with temperature regime, with summer versus winter pulse disturbances affecting biomass and abundance in characteristically different ways. Linking invertebrate abundance and biomass dynamics to abiotic drivers through this time-varying matrix population model reveals how life-history shapes aquatic invertebrate response to shifting seasons, temperatures, and disturbance, which is key to understanding the impacts of climate change on aquatic ecosystems.

Ecological Modelling↗

USGS2026

Bird migration and energetics simulations incorporating oil spill effects

Oil spills are well-known for causing acute mortality of birds, but sublethal and delayed impacts are less understood. Focusing on the mallard ( Anas platyrhynchos ), we used simulation modeling to explore how sublethal oiling may affect avian survival and breeding ground body condition. We used empirically informed migration and energetics simulations to model hypothetical spills occurring in northern Arkansas, USA occurring in either January to simulate thermoregulatory stress or March to simulate pre-migration effects. We modeled trace and lightly oiled female mallards (≤5% or 6 to 20% of feather area oiled, respectively), incorporating oiling-induced energetic effects on thermoregulation, flight, and energetic gain. We found that mortality was generally higher for simulated spills occurring in January versus March. In the simulations, mallards lost body mass due to oiling, but surviving individuals could partially recover body mass before arriving at the breeding grounds. Including oiling-induced energetic gain effects in simulations increased mortality as well as increased overall variability of simulation results. This modeling effort identified an important gap in knowledge regarding oiled bird energetics, specifically a need to better quantify oiling-induced energetic gain changes. Although the model is currently limited to a specific species and geographic area, it serves as a proof-of-concept for future research and modeling efforts aimed at understanding more broadly the impacts of oil spills on avian populations.

Prairie Pothole region↗

USGS2025

Foraging of wading birds on a patchy landscape: Simulating effects of social information, interference competition, and patch selection on prey intake and individual distribution

Foragers on patchy landscapes must acquire sufficient resources despite uncertainty in the location and amount of the resources. Optimal Foraging Theory posits that foragers deal with this uncertainty by using strategies that optimize resource intake within foraging periods. For species such as wading birds, this optimization is closely linked to their survival and reproductive success. Understanding the influence of patch selection on individual resource intake and foraging distribution is therefore crucial. In this study, we simulated how resource distribution, interference competition, and social cues—such as aggregation behaviors—influence resource intake and foraging spatial distribution. We employed an individual-based model simulating wading bird foraging behaviors, with 900 individuals simultaneously foraging across a landscape with unknown resource distribution. Birds employed one of three patch-finding strategies: random, cue-searching, or hybrid, which uses both searching strategies. Each bird decided whether to remain in a patch based on a prey density threshold. We compared the daily resource intake and foraging distribution of birds across different modeled patch-finding strategies, resource distribution patterns, and the presence or absence of interference competition. Wading birds exhibiting aggregation behavior displayed increased intake rates when resources were concentrated and interference minimal. Aggregation behavior led to a closer match with the ideal free distribution when the prey density threshold was optimal. These findings provide theoretical support that aggregation behavior is effective in scenarios where resources are concentrated in a few patches, social cues are used by relatively few individuals, and interference competition is limited.

Ecological Modelling↗