Midges as quantitative temperature indicator species: Lessons for palaeoecology

Abstract

Calibration data sets give a unique opportunity to establish patterns of biological existence and their statistical associations with environmental variables. By use of calibration data sets, environmental variables can be inferred quantitatively. The resulting long time-series may assist in distinguishing natural environmental variability from human-induced variability, both in terms of climate change and biotic turnover. However, the validity of the palaeoenvironmental reconstructions depends on their accuracy, precision and sensibility. Before performing palaeoenvironmental inferences, key mechanisms controlling contemporary species’ distribution, abundances and dynamics should be identified and understood. An inference model is developed to produce reconstructions. A major challenge lies in validating and interpreting the reconstructions. Calibration data sets involving midges (Diptera: Chironomidae) suggest that climate has a broad-scale, regional control over midge existence and abundance, often over-riding the influence of local within-lake variables. In recent years, the use of midges as quantitative indicators of past temperatures has greatly expanded. As the number of reconstructions increase, especially in Fennoscandia and North America, it seems the among-site variability is so large that it is unlikely to be due only to local differences in climate. Hence, we question whether the long climate gradients in calibration data sets can accurately be used to calibrate local variables, when most local gradients in time and space are short. Ten Holocene chironomid-inferred temperature curves from Fennoscandia are compared. We illustrate some general principles in palaeoecology by identifying factors that may cause bias. Especially, we consider how calibration data sets simplify the complexity of the real world by maximizing single ecological gradients and by not taking into account co-varying variables. We give some recommendations and criteria that chironomid analysis should meet in order to improve the reliability of the temperature inferences. Finally, we discuss how the complex interactions between species and environment may have implications when we aim at predicting future biodiversity.

Limnological changes in South Carpathian glacier-formed lakes (Retezat Mountains, Romania) during the Late Glacial and the Holocene: A synthesis

“…could have stronger effect on the lake ecosystems than temperature (e.g. Brooks, 2006;Velle et al, 2010). Therefore, mid to late Holocene assemblage changes in mid-latitude mountain lakes may be related to different and multiple local and regional factors.…”

Stable isotopes reveal that chironomids occupy several trophic levels within West Greenland lakes: Implications for food web studies

“…The distribution and abundance of chironomid taxa are controlled by a number of extrinsic and intrinsic environmental variables, such as oxygen content, total phosphorous, pH, temperature, lake depth, salinity, and pollution (Velle and Heiri 2013). However, ecological knowledge on the effect of extrinsic vs. intrinsic environmental variables is lacking (Velle et al 2010;Eggermont and Heiri 2012). When it comes to in-lake processes, food and habitat availability are likely to be important for this diverse group.…”

Chironomidae (Diptera) in the Himalayan Lakes – A study of sub-fossil assemblages in the sediments of two high altitude lakes from Nepal

“…This variation may reflect changes in silt load from glacial melt-water. In general, it is more difficult to infer recent temperature change, because variation in local environmental factors masks our ability to detect small temperature changes of only a couple of degrees (Velle et al 2010, Velle et al 2012, Eggermont & Heiri 2012. Lake morphometry influences variation in sediment cores, due to eco-logical responses of chironomid taxa to depth and development of the littoral zone and stratification (Heiri et al 2003).…”

“…These data, together with higher concentrations of dissolved Sodium and Potassium from weathering, suggest that Lake Gosaikunda supported slightly higher productivity of chironomids, due to warmth and possibly autochthonous production. Lake depth, the degree of stratification and hypolimnetic oxygen deficit may relate to the differences in chironomid assemblages observed (Heiri et al 2003;Velle et al 2010).…”

“…A comparison of withinlake spatial variability in chironomid assemblages and its impact on temperature modeling found significant heterogeneity among cores from the deepest part of five lakes, as well bias due to change in assemblage structure in cores along littoral to profundal transects (Heiri et al 2003). Change in lake trophic status may or may not be related to average temperature change, thus the cause of shifts in chironomid assemblage composition must be interpreted judiciously in temperature reconstruction (Velle et al 2010).…”