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Macroinvertebrate abundance is lower in temperate reservoirs with higher winter drawdown

  • Gabrielle TrottierEmail author
  • Holly Embke
  • Katrine Turgeon
  • Christopher Solomon
  • Christian Nozais
  • Irene Gregory-Eaves
Primary Research Paper

Abstract

Hydrological regime alteration in reservoirs is a major anthropogenic disturbance in aquatic ecosystems. We examined winter drawdown effects on macroinvertebrate abundance and community composition in reservoirs while accounting for localized physical variables that might explain additional variability. We hypothesized that drawdown would affect the abundance and the community composition of macroinvertebrates because of the exposure of organisms to freezing and desiccation. However, we expected the detection and magnitude of these responses to be conditional on localized physical habitat variables (i.e., fetch, thermal condition and slope), which also influence abundance and community composition of macroinvertebrates. To test these hypotheses, we applied generalized linear mixed effects models and multivariate analyses to data collected from 118 samples in 15 temperate reservoirs. Sampling stations from reservoirs that experienced high winter drawdown and/or were below the thermocline showed significantly lower macroinvertebrate abundances. Changes in community composition across sites were muted as chironomids, oligochaetes and sphaeriids dominated all assemblages. Decreases in macroinvertebrate abundances with drawdown amplitude and lower temperatures (i.e., hypolimnion) could have implications for food web structure, as they substantially contribute to fish diet, and ecosystem functions (e.g., nutrient cycling).

Keywords

Macroinvertebrates Aquatic insects Thermal regime Community composition Water level fluctuations 

Notes

Acknowledgements

This work was supported by the Conseil Régional de l’Environnement Chaudière-Appalaches (CRECA), Parc National de Frontenac, Regroupement pour la Protection du Grand Lac St-François (RPGLSF), Fondation de la Faune du Québec, Centre de la Science de la Biodiversité du Québec (CSBQ), Mathematics of Information Technology and Complex Systems (MITACS) and WSP Global Group, Inc., as well as McGill University and Université du Québec à Rimouski (UQAR). We thank many assistants for their hard work in the field. We are also very appreciative of Cristian Correa’s assistance both in the field and with the preliminary reservoir selection process. Three anonymous reviewers provided helpful comments on earlier versions of the manuscript.

Supplementary material

10750_2019_3922_MOESM1_ESM.xlsx (53 kb)
Supplementary material 1 (XLSX 53 kb) Table A1 Table showing the temperature (°C, degree Celsius) and dissolved oxygen (DO, mg/l) as a function of depth profile at the deepest point of each reservoir. Thermocline is identified by the dashed boxes in the table. In reservoirs labelled with as asterisk, DO was converted from % saturation values to mg/l values with USGS DOTABLES—Single-Value Computation (https://water.usgs.gov/software/DOTABLES/) using local temperature and barometric pressure data. The deepest Ponar grab in each reservoir was collected at 16 m, with the exception of two reservoirs (FLA and UMB) where the deepest site was indeed oxygen-rich (> 6 mg/l oxygen). Cells with “–” mean that this particular depth was not sampled and empty cells mean that the reservoirs did not encompass those depths (i.e., shallower water bodies)
10750_2019_3922_MOESM2_ESM.xlsx (68 kb)
Supplementary material 2 (XLSX 67 kb) Table A2 Raw data tables detailing sample number (SAMPLE_NUM), sample name (SAMPLE_NAME), fetch in kilometers (FETCH_KM), percentage of slope (SLOPE_PERCENT), distance to shore in meters (DIS_TO_SHORE_M), thermal regime (THERMAL_REG), all taxa that were identified in this study are alphabetically sorted and grouped by orders (see Table A3 for metadata on the code names used for each taxa), where taxa column that make up for more than 5% of the total number of organisms identified is bolded, and lastly, the total abundance per grab (TOTAL_AB_PER_GRAB) as well as the total abundance/m2 (TOTAL_AB_PER_M2; n = 118)
10750_2019_3922_MOESM3_ESM.xlsx (46 kb)
Supplementary material 3 (XLSX 46 kb) Table A3 Metadata detailing the taxonomy (phylum, class, order and family) of all taxa as well as their code names. “NA” does not mean that this specific level of taxonomy is not available, it means that taxa were not further identified for this study

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Gabrielle Trottier
    • 1
    • 5
    Email author
  • Holly Embke
    • 1
    • 6
  • Katrine Turgeon
    • 1
  • Christopher Solomon
    • 3
    • 4
  • Christian Nozais
    • 2
    • 3
  • Irene Gregory-Eaves
    • 1
    • 3
  1. 1.Department of BiologyMcGill UniversityMontrealCanada
  2. 2.Département de biologie chimie et géographieUniversité du Québec à RimouskiRimouskiCanada
  3. 3.Quebec Center for Biodiversity Science (QCBS)MontrealCanada
  4. 4.Cary Institute of Ecosystems StudiesNew YorkUSA
  5. 5.Centre international de référence sur le cycle de vie des produits, procédés et services (CIRAIG)Polytechnique MontréalMontrealCanada
  6. 6.Center for LimnologyUniversity of Wisconsin-MadisonMadisonUSA

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