Geology topics

Nick Young

Publications and source records attributed to Nick Young.

4 recordsLinked to original sources

USGS2013

The Hyper-Envelope Modeling Interface (HEMI): A Novel Approach Illustrated Through Predicting Tamarisk ( Tamarix spp.) Habitat in the Western USA

Habitat suitability maps are commonly created by modeling a species’ environmental niche from occurrences and environmental characteristics. Here, we introduce the hyper-envelope modeling interface (HEMI), providing a new method for creating habitat suitability models using Bezier surfaces to model a species niche in environmental space. HEMI allows modeled surfaces to be visualized and edited in environmental space based on expert knowledge and does not require absence points for model development. The modeled surfaces require relatively few parameters compared to similar modeling approaches and may produce models that better match ecological niche theory. As a case study, we modeled the invasive species tamarisk ( Tamarix spp.) in the western USA. We compare results from HEMI with those from existing similar modeling approaches (including BioClim, BioMapper, and Maxent). We used synthetic surfaces to create visualizations of the various models in environmental space and used modified area under the curve (AUC) statistic and akaike information criterion (AIC) as measures of model performance. We show that HEMI produced slightly better AUC values, except for Maxent and better AIC values overall. HEMI created a model with only ten parameters while Maxent produced a model with over 100 and BioClim used only eight. Additionally, HEMI allowed visualization and editing of the model in environmental space to develop alternative potential habitat scenarios. The use of Bezier surfaces can provide simple models that match our expectations of biological niche models and, at least in some cases, out-perform more complex approaches.

Environmental Management↗

USGS2013

Using habitat suitability models to target invasive plant species surveys

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale ( Centaurea stoebe and Pastinaca sativa ) in Wisconsin (USA), and one genus at the regional scale ( Tamarix ) in the western United States. These initial data were merged with environmental data at 30-m 2 resolution for Wisconsin and 1-km 2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P < 0.01), and targeted sampling did detect more species than nontargeted sampling with less sampling effort (χ 2 ) = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.

Wisconsin↗

USGS2011

How will climate change affect the potential distribution of Eurasian tree sparrows Passer montanus in North America?

Habitat suitability models have been used to predict the present and future potential distribution of a variety of species. Eurasian tree sparrows Passer montanus , native to Eurasia, have established populations in other parts of the world. In North America, their current distribution is limited to a relatively small region around its original introduction to St. Louis, Missouri. We combined data from the Global Biodiversity Information Facility with current and future climate data to create habitat suitability models using Maxent for this species. Under projected climate change scenarios, our models show that the distribution and range of the Eurasian tree sparrow could increase as far as the Pacific Northwest and Newfoundland. This is potentially important information for prioritizing the management and control of this non-native species.

Current Zoology↗

USGS2010

Bringing modeling to the masses: A web based system to predict potential species distributions

Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.

Future Internet↗