Characterization of patterns and variability in the dynamics of outdoor aquatic mesocosms: exploring the capabilities and challenges in data supporting aquatic system models

被引:4
|
作者
Loerracher, Ann-Kathrin [1 ]
Schmidt, Juergen [1 ]
Ebke, Peter [1 ]
Schmolke, Amelie [2 ]
Abi-Akar, Farah [2 ]
Galic, Nika [3 ]
Ashauer, Roman [3 ,4 ]
机构
[1] Mesocosm GmbH, Homberg Ohm, Hesse, Germany
[2] Waterborne Environm, Leesburg, VA USA
[3] Syngenta Crop Protect AG, Basel, Switzerland
[4] Univ York, Dept Environm & Geog, York, England
关键词
Aquatic mesocosm; Mechanistic effect models; Ecosystem; Risk assessment; Model parametrization; Historical control data; FRESH-WATER; ZOOPLANKTON ABUNDANCE; NUTRIENT AVAILABILITY; PHOSPHORUS LIMITATION; POPULATION-DYNAMICS; RELATIVE IMPORTANCE; COMMUNITY DYNAMICS; HABITAT COMPLEXITY; PRIMARY PRODUCERS; PERIPHYTIC ALGAE;
D O I
10.1007/s10646-023-02685-0
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Aquatic mesocosms are complex test systems used within regulatory risk assessment of plant protection products. These model ecosystems allow researchers to capture interactions of multiple species under realistic environmental conditions. They enable assessment of direct and indirect effects of stressors at all trophic levels (i.e., from primary producers to secondary consumers) and impacts on ecosystem functions. Due to the limited ability to test the multitude of potential exposure scenarios, cross-linking aquatic mesocosm studies with virtual mesocosms, i.e., aquatic system models (ASMs), can serve to meet the demand for more environmental realism and ecological relevance in risk assessment. In this study, full control data sets from seven aquatic mesocosm studies conducted at a single test facility under GLP were analysed graphically and using descriptive statistics. Thereby, not only a comprehensive data base but also an insight into the species present, their dynamics over time, and variability in unchallenged mesocosms was observed. While consistency in dynamics could be discerned for physical and chemical parameters, variability was evident for several biological endpoints. This variability points to amplification of small differences over time as well as to stochastic processes. The outline of existing gaps and uncertainties in data leads to the estimation of what can be expected to be captured and predicted by ASMs.
引用
收藏
页码:782 / 801
页数:20
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