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Validating a biophysical parasite model with fish farm pen and plankton trawl data
Aquaculture Environment Interactions ( IF 2.2 ) Pub Date : 2021-10-21 , DOI: 10.3354/aei00416
TP Adams 1 , S Marshall 2 , S Brown 3 , K Black 1
Affiliation  

ABSTRACT: Biophysical models of parasite dispersal are being increasingly used as a method for screening marine aquaculture developments, whether in establishment of new sites or expansion of existing sites, or planning of farmed fish health management strategies on local or regional spatial scales. How well these models reflect reality, however, is often brought into question, due to the difficulties in validating their outputs. Larval parasitic sea lice can spend up to around 14 d in the water column, as a result potentially travelling several 10s of km between farms. Lice distribution in the water column is typically patchy and low density. Furthermore, infection can occur from lice carried by wild fish. Combined with rapid population turnover and larval exchange between farms, this causes difficulties in attributing links between juvenile lice and their sources. We sought to validate a biophysical model of sea lice dispersal using plankton trawl abundance data and farm site juvenile lice counts. Unusually high farm lice abundances over the study period allowed model predictions of larval density to be compared with trawled samples, in addition to mapping the link between parent and offspring lice counts found on farm sites. We compared the prediction of the larval dispersal model with a site neighbourhood-based metric of infection pressure. Our results validate the ability of the model to predict variation in larval density over time and space and suggest an exponential relationship between estimated infection pressure and observed site juvenile count.

中文翻译:

使用养鱼场围栏和浮游生物拖网数据验证生物物理寄生虫模型

摘要:寄生虫传播的生物物理模型越来越多地被用作筛选海水养殖发展的方法,无论是在建立新地点或扩大现有地点,还是在当地或区域空间尺度上规划养殖鱼类健康管理策略。然而,由于难以验证其输出,这些模型反映现实的程度往往受到质疑。幼虫寄生海虱可以在水体中停留长达 14 天左右,因此可能会在农场之间移动数十公里。虱子在水体中的分布通常是零散且低密度的。此外,野生鱼类携带的虱子也可能引起感染。结合快速的种群周转和养殖场之间的幼虫交换,这导致难以确定幼虱与其来源之间的联系。我们试图使用浮游生物拖网丰度数据和养殖场幼虱计数来验证海虱传播的生物物理模型。研究期间异常高的农场虱子丰度允许将幼虫密度的模型预测与拖网捕捞样本进行比较,此外还可以绘制在农场现场发现的亲本和后代虱子计数之间的联系。我们将幼虫扩散模型的预测与基于站点邻域的感染压力指标进行了比较。我们的结果验证了模型预测幼虫密度随时间和空间变化的能力,并表明估计的感染压力与观察到的现场幼虫数量之间存在指数关系。我们试图使用浮游生物拖网丰度数据和养殖场幼虱计数来验证海虱传播的生物物理模型。研究期间异常高的农场虱子丰度允许将幼虫密度的模型预测与拖网捕捞样本进行比较,此外还可以绘制在农场现场发现的亲本和后代虱子计数之间的联系。我们将幼虫扩散模型的预测与基于站点邻域的感染压力指标进行了比较。我们的结果验证了模型预测幼虫密度随时间和空间变化的能力,并表明估计的感染压力与观察到的现场幼虫数量之间存在指数关系。我们试图使用浮游生物拖网丰度数据和养殖场幼虱计数来验证海虱传播的生物物理模型。研究期间异常高的农场虱子丰度允许将幼虫密度的模型预测与拖网捕捞样本进行比较,此外还可以绘制在农场现场发现的亲本和后代虱子计数之间的联系。我们将幼虫扩散模型的预测与基于站点邻域的感染压力指标进行了比较。我们的结果验证了模型预测幼虫密度随时间和空间变化的能力,并表明估计的感染压力与观察到的现场幼虫数量之间存在指数关系。研究期间异常高的农场虱子丰度允许将幼虫密度的模型预测与拖网捕捞样本进行比较,此外还可以绘制在农场现场发现的亲本和后代虱子计数之间的联系。我们将幼虫扩散模型的预测与基于站点邻域的感染压力指标进行了比较。我们的结果验证了模型预测幼虫密度随时间和空间变化的能力,并表明估计的感染压力与观察到的现场幼虫数量之间存在指数关系。研究期间异常高的农场虱子丰度允许将幼虫密度的模型预测与拖网捕捞样本进行比较,此外还可以绘制在农场现场发现的亲本和后代虱子计数之间的联系。我们将幼虫扩散模型的预测与基于站点邻域的感染压力指标进行了比较。我们的结果验证了模型预测幼虫密度随时间和空间变化的能力,并表明估计的感染压力与观察到的现场幼虫数量之间存在指数关系。
更新日期:2021-10-21
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