Data Sources Matter - A Case Study of the Dwarf Seahorse

Cooperative Research Unit Corner

Data Sources Matter - A Case Study of the Dwarf Seahorse

Seahorses are facing global population declines due to a combination of overfishing, habitat loss, and habitat degradation regularly occurring along densely inhabited coastal areas. However, conservation of these unique and charismatic species is often hindered by a poor understanding of their distribution and habitat requirements. Collaborators at the USGS Hawai’i Cooperative Fishery Research Unit, Texas Tech University, and Texas Parks and Wildlife are assessing the status of Dwarf Seahorse (Hippocampus zosterae) on the Texas coast. The goal of the research is to identify the locations of suitable habitat to target conservation efforts, and researchers have found that when conducting such work, data sources matter.

Photo of Dwarf Seahorse (Hippocampus zosterae) in the palm of a hand, taken at Redfish Bay, Aransas Pass, Texas in November 2015

Corralling Data

Dwarf Seahorse is among the smallest seahorse species, reaching a maximum length of about 2 cm. They have been considered a candidate for federal protection due to population declines in Florida, however little is known of their distribution, population status, or habitat requirements in Texas.

To be able to conserve imperiled species, managers first must understand where they occur. This task can be challenging in estuarine systems since distributions are expected to change due to increased coastal development and climate change impacts. Species distribution models (SDMs) provide one method to map ranges of estuarine species by relating observations of occurrences with underlying environmental factors. By characterizing the habitats where individuals of a species are known to occur, SDMs enable prediction of where else in the world suitable habitats may exist. Importantly, SDMs utilize data from past collections and do not require any harm or further collections, especially of imperiled species.

As they began working on developing models for Dwarf Seahorse, researchers discovered that different data sources varied in quality and resulting model outputs. Where the data is obtained can play an important role in how the models perform, thereby affecting the management actions taken.

Little Seahorses, Big Discrepancies

In the case of Dwarf Seahorse, researchers wanted to use environmental data on nitrates, temperature, salinity, light, current, and location of boat ramps to predict suitable habitat, but while gathering occurrence data, they discovered different source data types existed.

Occurrence data were obtained from both the Texas Parks and Wildlife Department (TPWD) and Fishes of Texas Database (FoTx). Given that FoTx relies on self-reporting, usually from various research projects, it is termed an “opportunistic” dataset. However, records provided by TPWD derive from long-term standardized, randomly-distributed surveys, termed “systematic.”

From Maps to Management

Although the FoTx data had stronger predictive performance, these data were more haphazardly collected than TPWD, so the resulting model may not depict the full seahorse distribution. Consequently, the choice of where to obtain occurrence data can change the predicted suitable habitat and eventually how Dwarf Seahorse is managed.

Understanding the implications of which data type is chosen will give insight on more accurate seahorse population trends and aid in developing conservation strategies, especially for the Texas population. Anthropogenic influences on Gulf Coast habitats have fragmented the traditional ranges of many other coastal species, including numerous species of economic, ecological, or other management importance. Investigating distributions, particularly in the face of a changing climate, can display changing trends in populations and identify causes for declines, which aid in developing conservation strategies for coastal wetland species.

Bigger than Dwarf Seahorses

In her ongoing research, Elizabeth Roesler, a doctoral student at the Texas Tech University, will continue to analyze how distribution results change while using other estuarine species to promote conservation and management in the Gulf Coast as well as other coastal ecosystems. The same research techniques will be applied to a diverse group of species with a variety of characteristics, such as large-bodied vs. small-bodied, long- vs. short-lived, and vagile vs. dispersal-limited, to determine how these characteristics influence the model performances and affect the habitat use and range of estuarine species. Her research will produce results useful to fisheries managers, conservationists, and other users of SDMs by comparing alternative types of occurrence data across different species.

The ONB features articles from Cooperative Fish and Wildlife Research Units across the country. Working with key cooperators, including WMI, Units are leading exciting, new, fish and wildlife research projects that we believe our readers will appreciate reading about. This article was written by: Tim Grabowski, Unit Leader, Hawaiʻi Cooperative Fishery Research Unit, Elizabeth Roesler, Department of Natural Resources Management at Texas Tech University, Fernando Martinez-Andrade, Texas Parks and Wildlife Department, Coastal Fisheries Division, and Matthew Barnes, Department of Natural Resources Management, Texas Tech University.

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July 13, 2018