Mullins Lindsay L, Drymon J Marcus, Moore Moriah, Skarke Adam, Moore Alan, Rodgers John C
Coastal Research and Extension Center Mississippi State University Biloxi Mississippi USA.
Department of Geosciences Mississippi State University Mississippi State Mississippi USA.
Ecol Evol. 2021 Oct 26;11(22):16055-16069. doi: 10.1002/ece3.8277. eCollection 2021 Nov.
Identifying critical habitat for highly mobile species such as sharks is difficult, but essential for effective management and conservation. In regions where baseline data are lacking, non-traditional data sources have the potential to increase observational capacity for species distribution and habitat studies. In this study, a research and education organization conducted a 5-year (2013-2018) survey of shark populations in the coastal waters of west-central Florida, an area where a diverse shark assemblage has been observed but no formal population analyses have been conducted. The objectives of this study were to use boosted regression tree (BRT) modeling to quantify environmental factors impacting the distribution of the shark assemblage, create species distribution maps from the model outputs, and identify spatially explicit hot spots of high shark abundance. A total of 1036 sharks were captured, encompassing eleven species. Abundance hot spots for four species and for immature sharks (collectively) were most often located in areas designated as "No Internal Combustion Engine" zones and seagrass bottom cover, suggesting these environments may be fostering more diverse and abundant populations. The BRT models were fitted for immature sharks and five species where > 100: the nurse shark (), blacktip shark (), blacknose shark (), Atlantic sharpnose shark (), and bonnethead (). Capture data were paired with environmental variables: depth (m), sea surface temperature (°C), surface, middle, and bottom salinity (psu), dissolved oxygen (mg/L), and bottom type (seagrass, artificial reef, or sand). Depth, temperature, and bottom type were most frequently identified as predictors with the greatest marginal effect on shark distribution, underscoring the importance of nearshore seagrass and barrier island habitats to the shark assemblage in this region. This approach demonstrates the potential contribution of unconventional science to effective management and conservation of coastal sharks.
识别鲨鱼等高度洄游物种的关键栖息地很困难，但对于有效管理和保护至关重要。在缺乏基线数据的地区，非传统数据来源有可能提高物种分布和栖息地研究的观测能力。在本研究中，一个研究与教育组织对佛罗里达州中西部沿海水域的鲨鱼种群进行了为期5年（2013 - 2018年）的调查，该区域观察到有多种鲨鱼聚集，但尚未进行正式的种群分析。本研究的目的是使用增强回归树（BRT）建模来量化影响鲨鱼种群分布的环境因素，根据模型输出创建物种分布图，并确定鲨鱼高丰度的空间明确热点区域。共捕获了1036条鲨鱼，涵盖11个物种。四种鲨鱼以及未成熟鲨鱼（总体）的丰度热点区域最常位于指定为“无内燃机”的区域和海草底质覆盖区域，这表明这些环境可能孕育了更多样化和丰富的种群。BRT模型针对未成熟鲨鱼和五种捕获量大于100条的鲨鱼进行拟合：护士鲨、黑鳍鲨、黑鼻鲨、大西洋尖鼻鲨和圆头鲨。捕获数据与环境变量配对：深度（米）、海面温度（摄氏度）、表层、中层和底层盐度（盐度单位）、溶解氧（毫克/升）以及底质类型（海草、人工鱼礁或沙地）。深度、温度和底质类型最常被确定为对鲨鱼分布具有最大边际效应的预测因子，这突出了近岸海草和障壁岛栖息地对该区域鲨鱼种群的重要性。这种方法展示了非传统科学对沿海鲨鱼有效管理和保护的潜在贡献。
