Research Interests
Overview
My research interests span the fields of ecology, behavior, and evolution, and revolve around identifying the most efficient and accurate methods to conserve biodiversity in terrestrial systems. I am particularly interested in urban systems and the promotion of biodiversity within human dominated landscapes. Specifically, I seek to explore the potential of arthropod taxa as biological indicators to serve as the basis for decisions about the design, construction and maintenance of biodiversity-promoting habitats. In addition to using arthropods as tools in conservation planning, I am interested in understanding the specific needs of the arthropod fauna and how these needs may differ from the needs of vertebrate species from a conservation perspective. This will require a more complete understanding of terrestrial arthropod ecology at the assemblage or community level, including the functional significance of arthropod groups in ecosystems.
Currently active projects
Conservation in designed and altered landscapes.
Native bees and rights-of-way. I was involved in a project with researchers at the USGS Patuxent Wildlife Research Center (PWRC) in Maryland (USA) to develop effective monitoring tools for native bees. As part of this project, we sampled bees in managed powerline rights-of-way onsite and found those that were maintained as early-successional scrub to be tremendously rich in species. I have become interested in the idea of powerline rights-of-way (and other intensively managed habitats) as mini-nature reserves. This land, if properly managed, has the potential to provide millions of acres of suitable habitat for early successional species, thereby maintaining critical source populations. Power companies already intensively manage the land under their lines and will continue to do so into the foreseeable future. Based on conversations I've had with land managers from NSTAR Electric and Gas Corporation, many power companies are amenable to tailoring their management practices to maximize biodiversity under their lines, as long as the vegetation does not interfere with their ability to deliver power. I plan to expand this area of research to a larger, landscape scale, for example, by asking how the implications of alternative management strategies differ in suburban vs. agricultural vs. predominantly natural environments.
Linear habitats in agricultural systems. As part of an NCEAS sponsored Distributed Graduate Seminar, I worked with a group of graduate students on a project to review the data on the importance of linear features in agricultural landscapes in terms of the provision of on- and off-farm ecosystem services. A growing body of research highlights the importance of proximity to natural habitats in the provision of key ecosystem services, such as habitat for pollinators and natural enemies. In regions where natural areas are rare, linear features can be a proxy for the provision of these services, but relatively few studies have quantitatively explored the relationship between linear habitat type and on- and off-farm services provided. This is especially true across the wide variety of linear habitat types in North and Central America. We are currently synthesizing the literature that does exploring the link between linear habitats and ecosystem services across these regions, and how management and landscape context impact the provision of services. Additionally, we are using a benchmark approach to compare community similarity of linear habitats to a range of reference habitats, including those that would hypothetically maximize the potential for both on- and off-farm ecosystem services. Where data allow, management or design strategies will be evaluated based on the similarity of the resulting linear feature to a natural target community. Taxonomic groups are also considered individually to assess the influence of mobility and local climate on the similarity between linear and target habitats. We further assess the changes in species composition between linear and natural habitats in light of their potential to influence on-farm service dynamics by grouping species into relevant functional groups. Our findings will enable land managers to make better-informed decisions regarding implementation of linear habitats within the agricultural landscape.
Ecosystem Design and Engineering Network (EDEN). In collaboration with researchers from Rutgers, NJIT, Columbia and local park services, I have been involved in a proposal to set up an academia/industry/government research collaboration network and data clearinghouse to promote two goals: 1) The cooperation of industry and academia in the application of the latest theory on ecological community assembly to the design and management of novel ecosystems on private and public lands, and 2) follow up monitoring and study of these systems to test and advance the theory, leading to the development of new models and management tools.
Automated species identification. At present, the factor most severely limiting our understanding of community structure, diversity, and how diversity relates to ecosystem functions and services, is the lack of experts capable of identifying biological specimens to species. For most groups of organisms, the number of trained systematists is low, and the success rate of non-specialists trying to achieve accurate identifications on their own, with currently available tools, is even lower. The situation is worst for relatively small and inconspicuous organisms (i.e., precisely those groups that comprise the bulk of our planet’s biodiversity). One way to ameliorate this problem is to encapsulate the taxonomic expertise of a specialist into a computerized identification system. A system that can identify any species in a particular family, or from a particular area, without requiring the user to have more than the most basic knowledge of the organism to be identified, has the potential to drastically improve the efficiency and scope of biological inventories, and subsequent monitoring efforts. We have developed an Internet-accessible automated identification system that uses artificial neural networks to make identifications based on digital images. We call this system SPIDA-web (SPecies IDentification, Automated and web accessible). See the website (https://research.amnh.org/invertzoo/spida/) for more detailed information. Funding for this project comes from the NSF Biocomplexity program (IDEA) as well as the NSF PBI program. Ultimately, I would like to see the creation of a center for automated species identification. This center would consist of computer programmers, web designers, imaging technicians and biologists. Researchers interested in developing an automated identification system for their particular taxonomic group, or region, would contract out the work to the center, which would produce a custom-designed solution. (Different species groups will require different techniques to be most effective.) Once the ID system is complete, it could either be housed and maintained on the center’s servers, or transferred to the contracting institution. Identification systems are most useful when they are built to evolve, such that as people use the system, new data are incorporated and the system becomes more accurate. Having the expertise in a central place would make maintenance and expansion more efficient.