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动态能量预算 (DEB) 模型在陡峭环境梯度中的适用性。

Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients.

机构信息

Department of Zoology and Entomology, Rhodes University, Grahamstown, South Africa.

Southern Seas Ecology Laboratories, School of Biological Sciences and The Environment Institute, The University of Adelaide, Adelaide, SA, 5005, Australia.

出版信息

Sci Rep. 2018 Nov 6;8(1):16384. doi: 10.1038/s41598-018-34786-w.

DOI:10.1038/s41598-018-34786-w
PMID:30401809
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6219521/
Abstract

Robust ecological forecasting requires accurate predictions of physiological responses to environmental drivers. Energy budget models facilitate this by mechanistically linking biology to abiotic drivers, but are usually ground-truthed under relatively stable physical conditions, omitting temporal/spatial environmental variability. Dynamic Energy Budget (DEB) theory is a powerful framework capable of linking individual fitness to environmental drivers and we tested its ability to accommodate variability by examining model predictions across the rocky shore, a steep ecotone characterized by wide fluctuations in temperature and food availability. We parameterized DEB models for co-existing mid/high-shore (Mytilus galloprovincialis) and mid/low-shore (Perna perna) mussels on the south coast of South Africa. First, we assumed permanently submerged conditions, and then incorporated metabolic depression under low tide conditions, using detailed data of tidal cycles, body temperature and variability in food over 12 months at three sites. Models provided good estimates of shell length for both species across the shore, but predictions of gonadosomatic index were consistently lower than observed. Model disagreement could reflect the effects of details of biology and/or difficulties in capturing environmental variability, emphasising the need to incorporate both. Our approach provides guidelines for incorporating environmental variability and long-term change into mechanistic models to improve ecological predictions.

摘要

稳健的生态预测需要准确预测生理对环境驱动因素的反应。能量预算模型通过将生物学与非生物驱动因素机械地联系起来,从而促进了这一点,但通常是在相对稳定的物理条件下进行地面验证,忽略了时间/空间环境变异性。动态能量预算 (DEB) 理论是一个强大的框架,能够将个体适应性与环境驱动因素联系起来,我们通过检查跨越岩石海岸的模型预测来测试其适应变异性的能力,岩石海岸是一个生态交错带,其特点是温度和食物供应广泛波动。我们在南非南部海岸为共存的中/高岸 (贻贝) 和中/低岸 (贻贝) 贻贝参数化了 DEB 模型。首先,我们假设永久淹没条件,然后在低潮条件下纳入代谢抑制,使用潮汐周期、体温和 12 个月内三个地点食物变化的详细数据。模型在整个海岸对两种物种的壳长提供了很好的估计,但性腺指数的预测值始终低于观察值。模型不一致可能反映了生物学细节和/或捕捉环境变异性的困难的影响,强调需要同时考虑这两个因素。我们的方法为将环境变异性和长期变化纳入机械模型以提高生态预测提供了指导方针。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/edfd931515d2/41598_2018_34786_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/d8b18572778b/41598_2018_34786_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/8429f74f3391/41598_2018_34786_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/59a1787264f2/41598_2018_34786_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/6822d34d94df/41598_2018_34786_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/bf4210e01194/41598_2018_34786_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/4313ef97c0fc/41598_2018_34786_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/edfd931515d2/41598_2018_34786_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/d8b18572778b/41598_2018_34786_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/8429f74f3391/41598_2018_34786_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/59a1787264f2/41598_2018_34786_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/6822d34d94df/41598_2018_34786_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/bf4210e01194/41598_2018_34786_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/4313ef97c0fc/41598_2018_34786_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df3f/6219521/edfd931515d2/41598_2018_34786_Fig7_HTML.jpg

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