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Full-Text Articles in Environmental Sciences
Shifting Hotspots: Climate Change Projected To Drive Contractions And Expansions Of Invasive Plant Abundance Habitats, Bethany A. Bradley, Et. Al.
Shifting Hotspots: Climate Change Projected To Drive Contractions And Expansions Of Invasive Plant Abundance Habitats, Bethany A. Bradley, Et. Al.
Environmental Conservation Faculty Publication Series
No abstract provided.
Breaking Down Barriers To Consistent, Climate-Smart Regulation Of Invasive Plants - A Case Study Of Northeast States, Bethany A. Bradley, Evelyn M. Beaury, Emily Fusco, Lara Munro, Carrie Brown-Lima, William Coville, Benjamin Kesler, Nancy Olmstead, Jocelyn Parker
Breaking Down Barriers To Consistent, Climate-Smart Regulation Of Invasive Plants - A Case Study Of Northeast States, Bethany A. Bradley, Evelyn M. Beaury, Emily Fusco, Lara Munro, Carrie Brown-Lima, William Coville, Benjamin Kesler, Nancy Olmstead, Jocelyn Parker
Environmental Conservation Faculty Publication Series
Efforts to prevent the introduction and spread of new invasive plants are most effective when regulated species are consistent across jurisdictional boundaries and proactively prohibit species before they arrive or in the earliest stages of invasion. Consistent and proactive regulation is particularly important in the northeast U.S. which is susceptible to many new invasive plants due to climate change. Unfortunately, recent analyses of state regulated plant lists show that regulated species are neither consistent nor proactive. To understand why, we focus on two steps leading to invasive plant regulation across six northeast states (Connecticut, Maine, Massachusetts, New Hampshire, New York, …
Invasive Species Risk Assessments Need More Consistent Spatial Abundance Data, Bethany A. Bradley, Jenica M. Allen, Mitchell W. O'Neill, Rebekah D. Wallace, Charles T. Bargeron, Julie A. Richburg, Kristina Stinson
Invasive Species Risk Assessments Need More Consistent Spatial Abundance Data, Bethany A. Bradley, Jenica M. Allen, Mitchell W. O'Neill, Rebekah D. Wallace, Charles T. Bargeron, Julie A. Richburg, Kristina Stinson
Environmental Conservation Faculty Publication Series
Spatial abundance information is a critical component of invasive plant risk assessment. While spatial occurrence data provide important information about potential establishment, abundance data are necessary to understand invasive species’ populations, which ultimately drive environmental and economic impacts. In recent years, the collective efforts of numerous management agencies and public participants have created unprecedented spatial archives of invasive plant occurrence, but consistent information about abundance remains rare. Here, we develop guidelines for the collection and reporting of abundance information that can add value to existing data collection efforts and inform spatial ecology research. In order to identify the most common …
Cheatgrass (Bromus Tectorum) Distribution In The Intermountain Western United States And Its Relationship To Fire Frequency, Seasonality, And Ignitions, Bethany A. Bradley, Caroline A. Curtis, Emily J. Fusco, John T. Abatzoglou, Jennifer K. Balch, Sepideh Dadashi, Mao-Ning Tuanmu
Cheatgrass (Bromus Tectorum) Distribution In The Intermountain Western United States And Its Relationship To Fire Frequency, Seasonality, And Ignitions, Bethany A. Bradley, Caroline A. Curtis, Emily J. Fusco, John T. Abatzoglou, Jennifer K. Balch, Sepideh Dadashi, Mao-Ning Tuanmu
Environmental Conservation Faculty Publication Series
Cheatgrass (Bromus tectorum) is an invasive grass pervasive across the Intermountain Western US and linked to major increases in fire frequency. Despite widespread ecological impacts associated with cheatgrass, we lack a spatially extensive model of cheatgrass invasion in the Intermountain West. Here, we leverage satellite phenology predictors and thousands of field surveys of cheatgrass abundance to create regional models of cheatgrass distribution and percent cover. We compare cheatgrass presence to fire probability, fire seasonality and ignition source. Regional models of percent cover had low predictive power (34% of variance explained), but distribution models based on a threshold of …