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Forecasting the geography of fish invasions in the lower Colorado River basin

Duration

August 2006 - July 2011

Narrative

Invasive species have caused major global change, harming indigenous species and communities throughout the world and inflicting enormous economic and ecological damage. Anticipating the future threatens posed by invasive species requires a predictive, proactive approach that forecasts potential distributions to further inform the identification and prioritization of critical conservation areas and endemic species at risk. Innovative analytical approaches, coupled with fast micro-computers, enable reliable large-scale nonparametric analyses to predict species distributions from geographical and ecological data. The attached research proposal addresses this pressing need by developing predictive models for forecasting the potential distributions of freshwater non-indigenous fish species in the Lower Colorado River Basin. This project addresses 3 fundamental questions that are critical for effectively managing invasive species in the Lower Colorado River Basin: (1) Will non-indigenous species already established continue to spread throughout the basin, or do they already occupy most of their potential range?; (2) If they continue to spread, what regions of the basin are likely to experience the greatest rates of invasion?; and (3) Do regions of high invasion susceptibility contain highly diverse and vulnerable endemic fish faunas? Products from this research contribute directly to the USGS Aquatic GAP Program by providing a quantitative framework for informing the selection of conservation priorities and identifying high priority surveillance locations aimed at the early detection of fish invasions and minimizing the future ecological impacts on native fish diversity. More generally, this project will provide a general framework for how non-indigenous species (and other forms of biological and environmental change) can be better incorporated into current and future Aquatic GAP programs.

Research Objectives � Anticipating the future threatens posed by invasive species requires a predictive approach that forecasts potential distributions to further inform the identification and prioritization of critical conservation areas and endemic species at risk. Such an approach would integrate the understanding of invader dynamics and the ecological interactions between the invader and natural ecosystems. These models would serve as the basis for specific strategies to prevent the further invasion and adverse impacts of non-indigenous species.

This project addresses 3 fundamental questions (listed above) that are critical for effectively managing the invasion of the Lower Colorado River Basin by non-indigenous fishes

Practical questions such as these about the control and management of non-indigenous fish species require quantitative models that forecast their potential distribution in the Lower Colorado River Basin. This project will develop predictive models for non-indigenous fishes with the aim of forecasting potential distributions throughout the Lower Colorado River Basin as a function of habitat suitability and proximity to sources of human introduction. Products from this research with lead to preventative measures and pro-active management strategies that can be implemented before non-indigenous species have become established.

Research Approaches � Regional conservation planning for the Lower Colorado River Basin requires knowledge about the potential spread and impact of non-indigenous fish species. These strategies should be based on the analysis of large-scale, long-term datasets, which when combined with small-scale experimental studies, will provide complementary approaches to better understand both historical and current distributional patterns of non-indigenous species. Broad-scale studies provide the foundation for proactive conservation planning by identifying patterns and rates of spread. This project requires knowledge of native and non-native species distributions, and ecogeographical layers describing natural and human-impacted features of the environment, in particular, patterns of landuse and altered flow regimes associated with dams. In collaboration with the Lower Colorado River Basin Aquatic GAP this data will be collected and synthesized.

Habitat-suitability or niche-based modeling techniques relate species point occurrence records to geographic information about the ecological characteristics of the landscape to produce a hypothesis about which ecological features are within a species' niche and which are not. The ecological niche model can then be projected onto landscapes to identify regions that present ecological conditions inside and outside of the species' niche, producing predictions of potentially suitable habitat distributions (Peterson 2003). I will use Ecological Niche Factor Analysis (ENFA, Hirzel et al. 2002) to model habitat suitability and the potential distributions of non-indigenous freshwater fishes in the Lower Colorado River Basin as a function of ecogeographical and human-related variables. ENFA is a method that quantifies the niche occupied by a species by comparing its distribution in ecological space with the environmental characteristics of the entire study area.

 

Current Staff

Federal Staff: 102

Masters Students: 247

Phd Students: 163

Post Docs: 55

University Staff: 266

5 Year Summary

Students graduated: 722

Scientific Publications: 1960

Presentations: 4355

 

Personnel

Funding Agencies

  • Gap Analysis Program (GAP)

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