My spatial problem

A description of the research question that you are exploring.  Global change is occurring from the continuing variability in the climate, the ecological responses to the climate drivers, and the socioeconomic and political response.  These changes alter the landscape in predictable and unforeseen ways, simultaneously causing modifications in interactions between the landscape and all the biological communities.  Our reliance on natural resources such as fish, highlights the coupled impacts of these changes between the human and natural system.  Exploring the impacts of this coupled system this term, the spatial problem that Ill address is to understand how habitat suitability models differ for the giant gourami (Osphronemus goramy) in the Mekong Basin between models that are based on the physical landscape and those that incorporate human impacts.  I will use the environmental indicators surface temperature, salinity, and turbidity to map the potential habitat for the giant gourami with an additional layer informed by indicators of human impacts such as land use, population, and proximity to industry to evaluate the differences.

The giant gourami is an air-breathing fish, native to this region, and grown commercially as a food fish as well as for the aquarium market throughout SE Asia (Lefevre et al., 2014).  The fish inhabits freshwater, brackish, benthopelagic environments in swamps, lakes, and rivers among vegetation, found in medium to large rivers and stagnant water bodies.  People around the world rely on fish as a primary source of protein and income, and the growing aquaculture industry provides roughly half of the global fish supply (FAO, 2014).  However, to meet the demands of a rapidly growing population (exceeding 7 billion by 2020), a rising middle class, and an increasingly urban population (65% by 2020), protein consumption is expected to increase to 45kg per capita by 2020, a 25% increase from 1997—the fish consumption rate is no outlier.

 

gourami

A description of the dataset.

  1. Boundary data for the IUCN defined habitat range for the giant gourami in the Mekong Basin species (shown below).  This status code for the species and is listed in this dataset as “Probably Extant.”  However, this particular status code is listed as “discontinued for reasons of ambiguity.”  So it is my hope that this analysis will provide insight into the IUCN-defined habitat and assess how it has changed through time by assessing the parameters used to develop the IUCN data and evaluate additional landscape variables.
  2. Point data on fish occurence 1930-1982 that Ill use to develop a baseline habitat suitability index: http://www.fishbase.org/Map/OccurrenceMapList.php?genus=Osphronemus&species=goramy&dsource=darwin_all_v2
  3. Current surface temperature from http://www.worldclim.org/
  4. Rivers of SE Asia from http://www.naturalearthdata.com/
  5. Vegetation classifications from NDVI data- time series- http://glam1.gsfc.nasa.gov/
  6. Additional information to evaluate the human impacts is available through the Mekong River Basin Study from the World Resources Institute: http://www.wri.org/resources/data-sets/mekong-river-basin-study

IUCN_Gourami

Hypotheses: I expect that the potential habitat for the giant gourami has increased over time and with increased human impacts do to the physiological resilience of the species.  This fish inhabits regions characterized by fresh to brackish water and in slow-moving areas like swamps, lakes, and large rivers.  Given its unique ability to breather air, this fish can survive in poorly oxygenated water to anoxic areas.  I expect that with climate change, increased urbanization, and the changing hydrologic profile of the system due to potential dams that this fish may become more suitable than others for its ability to live in ‘poorer’ environmental conditions.

Approaches: I hope to use python or modelbuilder to iterate through the available datasets to assess the changing habitat based on a habitat suitability index for the giant gourami.  There is also a time-series tool in Arc that I would like to explore.

Expected outcome: I hope to develop a habitat suitability index for the giant gourami and compare habitat suitability models for the potential habitat based on the changing physical landscape and increasing human impacts.  If the data are available, I hope to create a simple time-series animation for each model.

Significance: Fish production from aquaculture is poised to absorb an increasing amount of this demand for meat, offering techniques that offset some of the environmental costs of production.  Depending on the species and farming conditions, fish production can achieve some of the lowest feed-conversion ratios of any type of terrestrial animal meat production.  If farmed responsibly, some species of the diverse group of air-breathing fish such as the giant gourami present an advantage in aquaculture for their unique ability to breathe air.  However, it is critical to understand the impact of increased production levels on the natural range of the species order to mitigate the unwanted invasions or overloading of the natural environment.  A study to assess the spatio-temporal patterns of the habitat suitability of potential aquaculture species will allow for managers to make informed decisions about aquaculture siting and resource allocation.

Your level of preparation: In terms of my experience with the tools available for this type of analysis, I am starting to develop my comfort with ArcInfo, ModelBuilder, and Python for GIS.  However, am no expert.  I have also been exposed to some statistical applications of R, but am again not an expert.

 

FAO. (2014). The State of World Fisheries and Aquaculture 2014. Rome, Italy.

Lefevre, S., Wang, T., Jensen, a., Cong, N. V., Huong, D. T. T., Phuong, N. T., & Bayley, M. (2014). Air-breathing fishes in aquaculture. What can we learn from physiology? Journal of Fish Biology, 84, 705–731. doi:10.1111/jfb.12302

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One thought on “Habitat Suitability for Giant Gourami in the Mekong River Basin

  1. Stephanie,
    Nice work. Today we discussed how (in the intro section) you might define the elements of suitable potential habitat (temperature, salinity, turbidity, flow) and additional layers of human impacts that might affect actual habitat (population, industry, land use). I wonder if you might want to rephrase your research question to something like “How do habitat suitability models for the XX (study organism) in XX (study area) differ, between those based on physical features vs. human impacts on the landscape?” Then, for the approach, you may need to define the thresholds of these variables that you believe limit habitat. In the data section, can you provide a little more detail about where you hope to find data on the properties of temperature, flow, etc.? And your expected result is an animation of habitat over time? Or a comparison of how habitat suitability changes when you consider human as well as physical variables? The first few sentences of the significance section might be moved to the intro/justification.

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