Focus: Modeling for conservation
Contributed by Dennis Jongsomjit, Anna Costanza, and Preston Duncan
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6 minute read
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In geography, space is essential and comes in many forms. Think of the space you are currently inhabiting while reading. Wander outside and consider the space that a tree takes then the cooler temperature within the surrounding forest. Think about the breeze that has moved from the ocean to the coast, bringing moisture inland from one space to another. And consider the characteristics of the spaces an owl might use as it flies from tree to tree or the spaces a whale uses as it migrates across an entire ocean. As geographers, one of our main tasks is to understand space in all its forms and as ecologists we strive to understand how wildlife use and interact with this space and the environmental conditions within - this is what defines a species’ ecological niche. This understanding allows us to develop ways to best conserve those spaces or keep them intact and ecologically functional.
One of the key tools ecologists use to describe species ecological niches, especially over the last 10 to 20 years, are species distribution models (SDM’s).
Because data that informs a model is spatial, the results can be projected onto maps which can serve as powerful conservation tools. Here, modeled Adélie penguin winter distributions in August are mapped around the Ross Sea, Antarctica.
At their core, SDM’s take characteristics about the space that a species uses - how hot it is, the amount of precipitation, the water temperature, soil type, etc - to develop a model of what is most important for that species. Because this information is spatial, we can project the information from the model onto a map. In map form, the model becomes a powerful tool. Maps can be used to convey complex ecological information in a much more intuitive format. For example, important areas for a species can be highlighted across the landscape or layers of park boundaries or roads can be used to assess areas of a species niche that are protected or threatened.
Satellites are a key tool in providing spatial information for SDMs. They have become increasingly sophisticated, giving us more information about the landscape at higher and higher spatial and temporal resolutions. The use of LiDAR has also provided extremely detailed information about the environment and space in 3-dimensions.
The Hines lab is taking advantage of these technologies to peer into the ecological needs of wildlife and better understand their interactions with humans and the space around them. As an M.S. student in Interdisciplinary Marine & Estuarine Sciences, Anna Costanza is using SDMs to model habitat preferences and habitat use of the Southeast Pacific humpback whale and the Pacific leatherback turtle. Her study area, at the northern coast of Peru, is seasonal habitat for both of these marine species. The humpbacks arrive and pass through the study area starting in May through October for their winter breeding season. Leatherbacks are known to come within the study area when foraging for prey primarily during the austral summer months. Both these species have a high risk of interacting with coastal artisanal fisheries by accidentally becoming entangled or hooked by their gear. Anna’s goal is to identify and map areas of habitat preference for high whale season and overall leatherback turtle habitat. This map will become input into a Bycatch Risk Assessment that will visualize areas of high bycatch risks, useful in reducing unwanted bycatch for both fishers and survival of the species.
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To inform her SDMs, Anna is using MODIS AQUA data for a few environmental covariates - Sea surface temperature, Chlorophyll-a, and KD490 - a light attenuation coefficient. She has also generated GIS topographic variables such as slope of bathymetry, distance to shore and shelf break. Her animal presence points were collected from one-on-one interviews with fishermen and via participatory mapping.
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As another example, Preston Duncan, an M.S. student in Geographic Information Science, will be using Northern Spotted Owl presence data within SDM’s to map habitat suitability and territory selection in Marin county, and see how this relates to their breeding success and frequency. Northern Spotted Owls are a threatened subspecies of Spotted Owl and Marin County, the southern terminus of their range, is somewhat of a “last frontier” population. Severe declines are happening throughout their range due to habitat loss and competition from a novel competitor, the Barred Owl. Marin County is in the early stages of this Barred Owl range expansion, so the timing for determining this population’s habitat preferences and the conditions that allow for high reproductive capacity is favorable to prioritize management for their conservation. His goal is to inform land managers and partners in Marin County of the locales and habitat mosaics that provide the most beneficial conditions for Spotted Owl breeding in this population. This analysis will aim to identify areas of high conservation priority to facilitate Spotted Owls’ ability to persist and thrive in this part of their range.
Preston is partnering with Point Blue Conservation Science and will be using Spotted Owl location data collected by Point Blue and Point Reyes National Seashore field crews for the past 20 years. He will also be utilizing LiDAR data collected by the Golden Gate National Parks Conservancy and other partners to gather forest structure and terrain data.