Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States.
Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States.
复制标题
DOI：
10.1371/journal.pone.0208126
复制
发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Ahrens R
中科院分区：
文献类型：
--
作者：
Montes N;Swett R;Ahrens R
了解游艇活动的分布和强度是管理安全以及环境和社会影响的关键。休闲划船是美国东南部多样化海上交通的一个非常重要的组成部分。使用几种技术(泊松、负二项、栅栏和零膨胀模式、广义加法模型和广义混合模型)，并将休闲船民提供的地图信息与环境和地理变量相结合，对佛罗里达东北部和佐治亚州东南部水域近海休闲船只的季节分布进行了建模，以找到最简约的模型。基于模型的性能，使用负二项分布的GAM方法进行最终的模型分析。最佳季节模型对总偏差的解释在86.1%~88.6%之间。对于大多数季节，包括纬度、经度、纬度和经度之间的相互作用、叶绿素a浓度和大量人工珊瑚礁的模型得到了最好的拟合。唯一的例外是夏季的模型，该模型不包括叶绿素a浓度。鉴于研究区域的复杂性，许多海洋活动和若干海洋物种同时存在，这些模型可提供资料，分析游艇旅行与其他海洋活动(如货船、商船)和物种(如露脊鲸、海龟、鲨鱼)的分布和重叠情况。这些分析可以用来减少这些群体和活动之间的有害互动。
Understanding the distribution and intensity of recreational boating activities is key for managing safety as well as environmental and social impacts. Recreational boating is a very important component of the diverse maritime traffic in the southeastern United States. The seasonal distribution of offshore recreational vessels in waters off the coast of Northeast Florida and Southeast Georgia was modeled using several techniques (Poisson, negative binomial, hurdle and zero inflated modes, generalized additive models, and generalized mixed models) and by combining map-based information provided by recreational boaters with environmental and geographical variables to find the most parsimonious model. Based on model performance, the final model analysis was conducted using a GAM approach with a negative binomial distribution. The best seasonal models explained between 86.1%– 88.6% of the total deviance. For most seasons, a model that included latitude, longitude, interaction between latitude and longitude, chlorophyll a concentration, and abundance of artificial reefs resulted in the best fit. The only exception was the model for the summer season, which did not include chlorophyll a concentration. Given the complexity of the study area, with a number of maritime activities and several marine species co-occurring, these models could provide information to analyze the distribution and overlap of recreational boating trips with other maritime activities (e.g., cargo ships, commercial vessels) and species (e.g., right whales, sea turtles, sharks). These analyses could be used to decrease harmful interactions among these groups and activities.
登录
查看更多内容
影响因子：
5.9
作者：
Bauduin, Sarah;Martin, Julien;Fagan, Daniel E.
通讯作者：
Fagan, Daniel E.
影响因子：
3.8
作者：
Dalton, Tracey;Thompson, Robert;Jin, Di
通讯作者：
Jin, Di
影响因子：
3.4
作者：
Choudhury, S. B.;Jena, B.;Sahu, S. K.
通讯作者：
Sahu, S. K.
影响因子：
5.8
作者：
Bates, Douglas;Maechler, Martin;Walker, Steven C.
通讯作者：
Walker, Steven C.
DOI：
10.2307/1400528
发表时间：
2000-06-01
影响因子：
1.4
作者：
Dutilleul, P;Stockwell, JD;Legendre, P
通讯作者：
Legendre, P