Structural changes in lake functioning induced from nutrient loading and climate variability

被引:24
作者
Law, Tony [1 ]
Zhang, Weitao [2 ]
Zhao, Jingyang [1 ]
Arhonditsis, George B. [1 ,2 ]
机构
[1] Univ Toronto, Dept Phys & Environm Sci, Toronto, ON M1C 1A4, Canada
[2] Univ Toronto, Dept Geog, Toronto, ON M5S 3G3, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Plankton models; Climate variability; Nutrient loading; Lake phenology; System stability; Bayesian analysis; Model uncertainty; NORTH-ATLANTIC OSCILLATION; FOOD-WEB INTERACTIONS; CAUSES REGIME SHIFTS; CHAIN MONTE-CARLO; PHYTOPLANKTON COMMUNITIES; BAYESIAN CALIBRATION; EUTROPHICATION MODEL; SPRING BLOOM; WASHINGTON; PHOSPHORUS;
D O I
10.1016/j.ecolmodel.2009.01.001
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964-1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)-phytoplankton-zooplankton-detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r= 0.41), herbivorous grazing (r= 0.38), and detritus mineralization (r= 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042-2051.] to emphasize the "bottom-up" control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 mu g L-1) and chlorophyll a (4 mu g L-1) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:979 / 997
页数:19
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