Tanya Chesney
MS Candidate, Marine Resource Management
College of Oceanic and Atmospheric Sciences
Oregon State University
References were compiled for GEO 565, Geographical Information Systems and Science.
Instructor Dr. Dawn Wright (Winter 2011)
WHAT IS EBM?
Arkema, K.K., S.C. Abramson & B.M. Dewsbury. 2006. Marine ecosystem-based management: from characterization to implementation. Front Ecol. Environ. 4: 525-532.
In this review, the authors examine 18 different EBM definitions and the disconnect between scientific and management translations of EBM. Based upon literature review, the authors compile a table of criteria that are comprised of general, ecological, social and management elements that scientists emphasize for ecosystem-based management. The article points out the difference in criteria between definition, objectives and interventions of EBM. One inference of particular interest was the need to include social criteria unrelated to economic significance. In conclusion of their analysis the authors determine the need to have a universal definition of EBM, an increase in stakeholder involvement throughout the entire EBM process and a need for an appropriate EBM tool.
Cogan, C.B., B.J. Todd, P. Lawton & T.T. Noji. 2009. The role of marine habitat mapping in ecosystem-based management. ICES J. Mar. Sci. 66: 2033-2042.
In this article, the authors establish guidelines for effective management use of marine habitat mapping (MHM) that supports multiple organizations with science-based EBM objectives. The authors also provide detailed justification and examples of how MHM can be an integral tool in implementation of Grumbine’s (1994) ten essential EBM components. The ten EBM elements include hierarchical context; ecological boundaries; ecological integrity; data collection; monitoring; adaptive management; inter-agency cooperation; organization; humans embedded in nature and values. An example of MHM application in data collection is the overlay of satellite, aircraft, surface water analysis, species distribution and pelagic and benthic observations. One of the challenges with ecosystem-based approaches is the limitation of usable consolidated data, and MHM improves data acquisition and data analysis to management agencies.
This article incorporates all of the elements of EBM while emphasizing the need to provide maps and analysis tools that go beyond technological motives in order to be effective and timeless resources. MHM and GIScience enable immediate progression towards a holistic approach to management and marine conservation that can be applied at a variety of temporal and spatial scales. MHM provides a flexible and powerful tool to scientists and management to address resource demands beyond a single-species level. Even more importantly, it enhances marine ecosystem communication and awareness to the public and policy makers that is accessible and understandable.
McLeod, K.L., J. Lubchenco, S.R. Palumbi, & A.A. Rosenberg. 2005. Scientific consensus statement on marine ecosystem-based management. Signed by 217 academic scientists and policy experts and published by the Communication Partnership for Science and the Sea at http://compassonline.org/?=EBM.
McLeod et al. provide an explanation of what marine ecosystem-based management entails. The authors stress the importance of focusing efforts on the protection of key ecosystem processes and encompassing the interactions within and between systems. Marine EBM is a dynamic approach that consists of ecological, economic and social motives. Therefore, management efforts should be non-static, have a scientific-basis and involve all stakeholders. This statement was useful because it provided a general background of marine EBM in addition to what actions should be implemented to meet EBM goals.
Troy, A. & M.A. Wilson. 2006. Mapping ecosystem services: practical challenges and opportunities in linking GIS and value transfer. Ecological Economics. 60: 435-449
Available resources frequently limit and direct ecosystem-based management efforts. Management decisions can be constrained by financial availability and the perception of economic value that is placed on the objective. The quantification of ecosystem services can assist in the concentration of EBM action.
Troy & Wilson map spatial value flows using GIS in order to develop the Natural Assets Information System framework which links economic and biophysical data. Steps taken to produce the framework included defining the study area; developing typology; reviewing literature to obtain additional data; mapping; deriving the total service value; obtaining a geographic aggregation unit that summarizes the ecosystem service values and finally analyzing historic land cover change. Of particular interest, was the Maury Island case study in which the authors determined an economic value by land cover. Their results indicated that beach near dwelling and nearshore aquatic habitat were equated to the highest ecosystem service values. Troy & Wilson stress that quantifying ecosystem services can yield skewed results when available economic values are not available for land covers that have known importance. Overall, this article demonstrates that when used in conjunction with additional analyses, ecosystem service values can focus mitigation efforts especially with a reduced budget.
APPLICATIONS
Dahdouh-Guebas, F. 2002. The use of remote sensing and GIS in the sustainable management of tropical ecosystems. Environment, Development and Sustainability. 4: 93-112.
To support mitigation, the author emphasizes the use of remote sensing and GIS to evaluate and predict anthropogenic effects on coastal mangroves, seagrass beds and coral reefs. Aerial photography was found to be the most effective form of remote sensing tool for investigating mangrove forest density, hydrological data and species composition. GIS techniques were suggested to provide a basis from integrating past and present conditions in order to predict future habitat state. The author stressed the significance of socio-economic surveys in conducting habitat research. Conducting interviews with native individuals may promote early detection of habitat degradation and substantiate recovery efforts.
Foody, GM. GIS: biodiversity applications. 2008. Progress in Physical Geography. 32: 223-235.
Species richness and composition are often factors used to assess biodiversity. Foody proposes methods, in which GIScience can store, analyze and visualize habitat and species data that pertain to biodiversity evaluation. Habitat cover type and condition can be obtained by aerial and satellite imagery. Through remote sensing, changes in habitat can be modeled and monitored over time in order to evaluate and predict species response to altered ecosystems.
Foody presents limitations to using GIS in biodiversity applications. For example, accurate data at the proper spatial scale and resolution is imperative to prevent imprecise assumptions of species response to habitat alterations and climate change. In addition, spatial autocorrelation is a concern in modeling species distribution and response. Lastly, non-stationary relationships that are assumed to be stationary alter model parameters and diminish the robustness of the model results. This article was beneficial because it stressed the importance in considering uncertainties associated with GIS applications as well as the built-in assumptions that are innate of using the tool. Therefore, in order to prevent management decisions that include false predictions of species response to habitat alteration, evaluation of these uncertainties is crucial.
Friedlander, A.M., E.K. Brown & M.E. Monaco. 2007. Coupling ecology and GIS to evaluate efficacy of marine protected areas in Hawaii. Ecological Applications. 17: 715-730.
Marine Protected Areas (MPAs) are areas that have human-use restrictions in order to achieve a goal such as increasing fisheries abundance or biodiversity. MPAs are incorporated into conservation strategies and EBM to preserve marine habitat and interacting communities within the system. GIScience is a tool that can be utilized to assess MPA effectiveness or to determine site implementation. In addition to belt transect surveys and digital video transects, the researchers in this paper incorporated GIS to create benthic habitat maps of 11 Marine Life Conservation Districts (MLCDs) that varied in size, quality and location in Hawaii. Their objective was to assess fish utilization and abundance. After analysis, the authors found that fish assemblage distribution is dependent on habitat type and reduced fishing efforts, and abundance was 2.6 times greater within MLCDs. This research provided a key example of how GIS can be used in both the planning and monitoring stages of EBM. It also illustrated that GIS can enhance large spatial and temporal scale management approaches and analysis amongst multiple governing bodies.
Miyajima, T., Y. Tanaka, I. Koike, H. Yamano & H. Kayanne. 2007. Evaluation of spatial correlation between nutrient exchange rates and benthic biota in a reef-flat ecosystem by GIS-assisted flow-tracking. Journal of Oceanography. 63: 643-659.
In this article, the researchers created raster maps for benthic coral species coverage. Next, they separated the stocks into biomass for total organic carbon, nitrogen and phosphorus content. Then, they converted raster maps into distribution maps to look at nutrient exchange and biomass of corals. Temporal patterns were evaluated for nutrient uptake given the species distribution and oceanic conditions. Their results found that nutrient exchange was dictated by the benthic species more so than water temperature and light condition.
Effective ecosystem-based management incorporates multiple factors that influence ecosystem function. Therefore, analyzing nutrient exchange, which influences species distribution is imperative. As illustrated in the article, GIS is one modeling technique that can be used to analyze and map fluxes.
Stigall, A.L. & B.S. Lieberman. 2006. Quantitative paleobiogeography: GIS, phylogenetic biogeographical analysis, and conservation insights. J. Biogeogr. 33: 2051-2060.
Stigall & Lieberman utilize GIS analysis and mapping to examine temporal and spatial species distribution during the Late Devonian. In particular, the research looked at the relationship between brachiopod and bivalve fossil distribution, extinction and historical sea level in order to assess range expansion and survival susceptibility. Through niche modeling, the authors found that offshore species were more likely to survive over nearshore species. Additionally, generalists, or species that had the ability to expand their distribution range, were more likely to survive over species with limited habitat range.
This research is important for EBM because it assesses the propensity of survival and the effects of invasive species. Currently, some marine species are altering their distribution range as a result of climatic factors. The analysis of paleobiogeography in relation to changes in sea level and biodiversity provides insight into predictive distribution patterns. Utilizing this knowledge, EBM efforts will be more robust and effective.
Valavanis, V.D., A. Kapantagakis, I. Katara & A. Palialexis. 2004. Critical regions: A GIS-based model of marine productivity hotspots. Aquat. Sci. 66: 139-148.
Areas of high chlorophyll concentrations and low sea surface temperature are known to be directly related to marine species feeding and mating aggregation. Valavanis et al. examine a site in the Eastern Mediterranean Sea using an ESRI GIS model to determine a correlation between hotspots and fisheries catch per unit effort (CPUE) data for the European sardine, anchovy, long-finned squid and short-finned squid from 1998-2001. In their results they found a relationship between anchovy and long-finned squid fishery efforts and productivity hotspots. The researchers also found that fishing activity in the Eastern Mediterranean Sea is concentrated around marine hotspots.
This article demonstrates that GIS analysis can determine relationships between physical marine processes and marine species aggregation. If an EBM objective is to locate supplemental fishing regions or target areas of potential conservation sites, a similar GIS modeling approach may be beneficial.
Valavanis, V.D. et al. 2008. Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS. Hydrobiologia. 612: 5-20.
Valavanis et al. review modeling techniques to locate essential marine fish habitat. The authors incorporate fish data from fishery-dependent and independent survey sources. They also incorporate a number of physical features and oceanic processes including but not limited to bathymetry, substrate, sea surface temperature, chlorophyll concentrations, photosynthetically active radiation, euphotic depth, salinity, and current patterns. The authors state that when modeling essential fish habitat either a prediction or range approach is used.
Although the model elements expressed in the article are useful, the model steps and limitations were of most interest to me. According to Valvanis et al. models can only incorporate two properties when considering generality, reality and precision due to complexity. Therefore, having a clear objective and adequate data is necessary to achieve the most non-biased results. Therefore, when incorporating GIS analysis into EBM, an essential component to success is planning an appropriate method design.
Wijnbladh, E., B.F. Jönsson & L. Kumblad. 2006. Marine ecosystem modeling beyond the box: Using GIS to study carbon fluxes in a coastal ecosystem. AMBIO: A Journal of Human Environment. 35: 484-495.
Rather than using a box-model approach, the authors apply a GIS data-grid to examine the spatial distribution of carbon in the Baltic Sea. Their overall goal was to determine transport of radionucleotide release from a nuclear waste storage facility by establishing carbon sources and sinks. The GIS model included a food-web to illustrate carbon transport between primary producers and heterotrophs. The researchers then incorporated a high-resolution digital elevation model and bottom substrate grid. Their results indicated that the inner basins had net primary production whereas the outer basins had net respiration due to benthic species distribution and environmental conditions. According to the authors, if they had used a box-model approach rather than the GIS model, they would have most likely gotten different results. They state that box-models are better designed for pelagic homogenous systems and are insufficient for coastal systems that are influenced by benthic communities.
GIS and EBM in ACTION
Plakos, M. 2007. CASI data provides better picture of coral reef threats. Prepared for the Khaled bin Sultan Living Oceans Foundation. Accessed from www.ESRI.com/Marine. GIS Best Practices: GIS for Ocean Conservation.
Researchers obtained data from Compact Airborne Spectrographic Imager (CASI) in order to examine coral reef complexes around St. John and St. Thomas, U.S. Virgin Islands. Raster maps were created from the CASI geodatabase and converted to polygons with associated attributes. Based upon their efforts, unknown coral reef habitat was discovered. Although maps produced from their research are available, the research group is planning on making the CASI database available to online users in the form of an interactive GIS.
Brenner, J., J. A. Jiménez, R. Sardá. 2008. Environmental indicators GIS of the Catalan coast. J. Coast Conserv. 11: 185-191.
GIS was utilized to create a model for the Integrated Coastal Zone Management in the Catalan coast to be used in EBM. The researchers incorporated biodiversity, biophysical and socioeconomic sections into raster and vector layers at a scale between 1:50,000 and 1:250,000. The researchers evaluated the impact pressures of tourism and development, the distribution of 490 marine fish and river inputs. They then determined a correlation between fish diversity and human-induced impact and discovered that half the fish families are located in the littoral zone below 50 meters in depth.
Carollo, C., D.J. Reed, J.C. Ogden, D. Palandro. 2009. The importance of data discovery and management in advancing ecosystem-based management. Marine Policy. 33: 651-653.
In an effort to create a framework for coastal and ocean ecosystem-based management in the Gulf of Mexico and East coast of Florida, United States, the Geospatial Assessment of Marine Ecosystems (GAME) project utilized GIS. To accomplish this, GAME members obtained data from a consortium of organizations and created a catalog that is compliant to Federal Geographic Data Committee standards. From the catalog, users can link to data sets that can be mapped and analyzed in GIS. The data ranges from geological, biological, chemical, physical and social. According to the authors, there are still limitations to the database. First, metadata has not always been found to be “properly prepared.” Secondly, scientists are resistant to be involved in the project and provide their data and research.
Mol, B.D. et al. 2009. HERMES-GIS: A tool connecting scientists and policy makers. Oceanography. 22:145-153.
HERMES is a web-based GIS Portal that includes a data archive library with metadata, PANGAEA, and services such as a Web Map Service (WMS). HERMES is organized in a manner that allows for ease of data submission. Additionally, authors have the option to restrict their data to users and have their data password protected; otherwise HERMES is an open-source project. Once the data is accessed in HERMES, data can be analyzed and mapped in GIS. HERMES incorporates biological, geological, oceanographic, socio-economic and ecological data.
Data from HERMES, was used to predict cold-water coral distribution. Using acoustic data, slope, terrain complexity and bathymetric position index, cold-water coral reef habitat was determined in the Northeast Atlantic. This allows EBM conservation efforts to be directed to that region.
The HERMES Portal is an excellent example of ecosystem-based management in action. The project integrates ecological, economic and social aspects. Additionally, a variety of collaborating agencies and scientists are working together to provide and analyze marine ecosystem data. Having an open-source project enables stakeholders to have access to the data and be included throughout the management process.