About OpenKnowledge@NAU | For NAU Authors

An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas

Wang, Ophelia and Zachmann, Luke J. and Sesnie, Steven E. and Olsson, Aaryn D. and Dickson, Brett G. (2014) An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas. PLoS ONE, 9 (7). e101196. ISSN 1932-6203

[img]
Preview
Text
Wang_O_etal_2014_Iterative_targeted_sampling_design(1).pdf - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview
Publisher’s or external URL: http://dx.doi.org/10.1371/journal.pone.0101196

Abstract

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives.

Item Type: Article
ID number or DOI: 10.1371/journal.pone.0101196
Keywords: Alien plants; Biogeography; Biological invasions; Biology and life sciences; brassica-tournefortii; Cartography; climate-change; Community ecology; Computer and information sciences; Conservation science; Distributions; Earth sciences; Ecological metrics; Ecological risk; Ecology; Ecology and environmental sciences; Environmental protection; Fire; geographic information systems; Geography; Geoinformatics; grass/fire cycle; habitat suitability index models; invasive plant; invasive plants; Mojave Desert; plant communities; Plant Ecology; plants -- Habitat; plant species; Research Article; Spatial and landscape ecology; species interactions; Terrestrial ecology; Terrestrial environments; united-states; USA
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QH Natural history > QH301 Biology
NAU Depositing Author Academic Status: Faculty/Staff
Department/Unit: Research Centers > Landscape Conservation Initiative
College of Engineering, Forestry, and Natural Science > School of Earth Sciences and Environmental Sustainability
Date Deposited: 16 Oct 2015 19:53
URI: http://openknowledge.nau.edu/id/eprint/1692

Actions (login required)

IR Staff Record View IR Staff Record View

Downloads

Downloads per month over past year