David Vieglais

Predicting Species Invasions Using Ecological Niche Modeling: New Approaches from Bioinformatics Attack a Pressing Problem

O 3 February 1999, President Clinton signed an executive order dealing with invasive species in the United States. The order was designed to lay the foundation for a program “to prevent the introduction of invasive species and provide for their control and to minimize the economic, ecological, and human health impacts that invasive species cause” (Clinton 1999). This program includes far-reaching plans to prevent, plan, monitor, and study species’ invasions. Such high-level attention emphasizes the enormity of the problem facing the United States, and in fact the entire world: With ever-growing international commerce, reduced barriers to trade, and increasing human influence, species are moving around, and natural systems are suffering drastic changes. The dimensions of the problem are indeed impressive. Alien plants, animals, and microbes have poured into the United States from all directions. Natural systems have been disrupted, species extinguished, transportation and agriculture compromised, and resources damaged (Carlton 1997–1998, Ogutu-Ohwayo 1997–1998, Richardson 1997–1998, Shiva 1997–1998). In fact, most modern agriculture is based on nonnative organisms; problems arise because questions of when and why some escape and become nuisances remain unanswered. More generally, no proactive approach to combating such species is available—invasive species are dealt with one at a time, as they become problematic. Scientific approaches to a synthetic, and ultimately proactive, understanding of species invasions have developed along several lines, but most have been frustrated by the complex and unpredictable nature of such invasions—which species will invade and which invaders will become serious problems? For example, considerable effort has gone into identifying characteristics of species likely to invade, or of invaders likely to become pests (e.g., Lawton and Brown 1986, Smallwood and Salmon 1992, Carlton 1996). Another line of inquiry and effort has focused on modeling spatial patterns of range expansion after initial invasion (e.g., Mollison 1986, Williamson and Brown 1986, Reeves and Usher 1989, Hastings 1996, Shigesada and Kawasaki 1997, Holway 1998). All in all, though, a general, synthetic, predictive, proactive approach to species invasions is lacking (Mack 1996) but is desperately needed (Hobbs and Mooney 1998).

Darwin Core: an evolving community-developed biodiversity data standard.

Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations.

Migratory birds modeled as critical transport agents for West Nile Virus in North America.

West Nile Virus has spread more rapidly than expected in the Western Hemisphere. We tested Culex mosquitoes and long-distance migratory birds as potential agents of spread for the virus, using a series of techniques, as follows. (1) Mosquito vector distributions were modeled using an ecological niche modeling approach (GARP) to produce a map of suitability of the landscape for mosquito transmission of the virus. (2) Simulations of spread were developed with an algorithm originally developed for modeling the spread of wildfires (EMBYR), seeding an initial presence of the virus in the New York City area. (3) Alternative spread scenarios were developed as (a) just mosquitoes as movement agents (spread simulation seeded once at New York City and allowed to spread across the mosquito suitability surface), versus (b) spread via mosquitoes on local scales in tandem with long-distance colonization with migratory birds as movement agents (spread simulation seeded once at New York City, and again at sites sampled from the winter destinations of birds breeding in southeastern New York State). The first scenario (mosquitoes only) did not coincide with observed patterns of spread, whereas the second (mosquitoes and migratory birds) coincided closely, suggesting that observed patterns of spread are best explained with migratory birds as critical long-distance transport agents; the virus, in regions to which it is transported by migratory birds, then is transmitted enzootically via mosquitoes. Similar simulations of spread were used to predict extensions of the virus in the Western Hemisphere in coming years.

Predicting invasions of North American basses in Japan using native range data and a genetic algorithm

Abstract Largemouth bass Micropterus salmoides and smallmouth bass M. dolomieu have been introduced into freshwater habitats in Japan, with potentially serious consequences for native fish populations. In this paper we apply the technique of ecological niche modeling using the genetic algorithm for rule-set prediction (GARP) to predict the potential distributions of these two species in Japan. This algorithm constructs a niche model based on point occurrence records and ecological coverages. The model can be visualized in geographic space, yielding a prediction of potential geographic range. The model can then be tested by determining how well independent point occurrence data are predicted according to the criteria of sensitivity and specificity provided by receiver–operator curve analysis. We ground-truthed GARPs ability to forecast the geographic occurrence of each species in its native range. The predictions were statistically significant for both species (P < 0.001). We projected the niche models on...

Participatory design of DataONE—Enabling cyberinfrastructure for the biological and environmental sciences

Abstract The scope and nature of biological and environmental research are evolving in response to environmental challenges such as global climate change, invasive species and emergent diseases. In particular, scientific studies are increasingly focusing on long-term, broad-scale, and complex questions that require massive amounts of diverse data collected by remote sensing platforms and embedded environmental sensor networks; collaborative, interdisciplinary science teams; and new approaches for managing, preserving, analyzing, and sharing data. Here, we describe the design of DataONE (Data Observation Network for Earth)—a cyberinfrastructure platform developed to support rapid data discovery and access across diverse data centers distributed worldwide and designed to provide scientists with an integrated set of familiar tools that support all elements of the data life cycle (e.g., from planning and acquisition through data integration, analysis and visualization). Ongoing evolution of the DataONE architecture is based on participatory, user-centered design processes including: (1) identification and prioritization of stakeholder communities; (2) developing an understanding of their perceptions, attitudes and user requirements; (3) usability analysis and assessment; and (4) engaging science teams in grand challenge exemplars such as understanding the broad-scale dynamics of bird migration. In combination, the four approaches engage the broad community in providing guidance on infrastructure design and implementation.

Data integration and workflow solutions for ecology

The Science Environment for Ecological Knowledge (SEEK) is designed to help ecologists overcome data integration and synthesis challenges. The SEEK environment enables ecologists to efficiently capture, organize, and search for data and analytical processes. We describe SEEK and discuss how it can benefit ecological niche modeling in which biodiversity scientists require access and integration of regional and global data as well as significant analytical resources.

DataONE: A Data Federation with Provenance Support

DataONE is a federated data network focusing on earth and environmental science data. We present the provenance and search features of DataONE by means of an example involving three earth scientists who interact through a DataONE Member Node. DataONE provenance systems enable reproducible research and facilitate proper attribution of scientific results transitively across generations of derived data products.

Temporal measurement and analysis of high-resolution spectral signatures of plants and relationships to biophysical characteristics

Measurements of temporal reflectance signatures as a function of growing season for sand live oak (Quercus geminata), myrtle oak (Q. myrtifolia, and saw palmetto (Serenoa repens) were collected during a two year study period. Canopy level spectral reflectance signatures, as a function of 252 channels between 368 and 1115 nm, were collected using near nadir viewing geometry and a consistent sun illumination angle. Leaf level reflectance measurements were made in the laboratory using a halogen light source and an environmental optics chamber with a barium sulfate reflectance coating. Spectral measurements were related to several biophysical measurements utilizing optimal passive ambient correlation spectroscopy (OPACS) technique. Biophysical parameters included percent moisture, water potential (MPa), total chlorophyll, and total Kjeldahl nitrogen. Quantitative data processing techniques were used to determine optimal bands based on the utilization of a second order derivative or inflection estimator. An optical cleanup procedure was then employed that computes the double inflection ratio (DIR) spectra for all possible three band combinations normalized to the previously computed optimal bands. These results demonstrate a unique approach to the analysis of high spectral resolution reflectance signatures for estimation of several biophysical measures of plants at the leaf and canopy level from optimally selected bands or bandwidths.