4. Fortin, MC; Medeiros, AS; Gajewski, K; Barley, EM; Larocque-Tobler, I; Porinchu, DF; Wilson, SE. (2015) Chironomid-environment relations in northern North America.Journal of Paleolimnology 54: 223-237 Chironomid-environment relations in northern North America
Chironomidae; Paleolimnology; Paleoecology; Paleoclimate reconstructions; Inference models; Gradient analysis; Chironomids; Temperature
Chironomid assemblages from the uppermost sediments of 435 lakes spanning northern North America were compared to environmental parameters using direct gradient analysis. This large calibration set was merged from several previously developed regional datasets, and increases the number of modern analogues that are available for use for paleoenvironmental interpretations in this region. Air temperature explained the largest amount of variation in the chironomid assemblages with several other environmental factors accounting for statistical significant amounts of the remaining variance. A robust inference model for deriving past mean July air temperatures from subfossil chironomid assemblages was developed and applied to previously published paleoclimate reconstructions from the High-Arctic, Middle-Arctic, Boreal treeline, and Alpine regions of northern North America. The patterns of the temperature reconstructions from the combined dataset were generally similar to the original reconstructions, but with colder inferred temperatures reflecting the incorporation of a larger number of modern sites from colder climates in the combined dataset. This analysis demonstrated that the larger temperature gradient available in the new training set, when compared to the temperature gradients in the original training sets, provides a better estimation of chironomid-environment relationships. In particular, the optima and tolerances estimated using the larger, combined dataset should be more accurate, and therefore, improve midge-based paleoclimate reconstructions for northern North America. Despite the much larger spatial scale and greater associated environmental heterogeneity now incorporated in the combined dataset, this study suggests that in most cases the overarching constraint governing chironomid distributions in northern North America is temperature. DOI
3. Cranston P, Erin Barley, Geneva E. Langley (née Chase), Ann Dieffenbacher-Krall, Allyson Longmuir & Jack Zloty. (2011) Propsilocerus Kieffer (Diptera: Chironomidae) from the Nearctic.Aquatic Insects: International Journal of Freshwater Entomology 33: 343-350 Propsilocerus Kieffer (Diptera: Chironomidae) from the Nearctic
Larvae of the chironomid genus Propsilocerus Kieffer (Diptera: Chironomidae), known from the Palaearctic region and from subfossil larval head capsules in North America, have been found living in remote British Columbia, Canada. We review the morphology and ecology of the taxon in North America, and report and interpret the subfossil occurrences. Although the species appears to be undescribed, we refrain from a formal taxonomic description based on the larva alone pending discovery of the full life history.
DOI
2.Barley, EM; Walker, IR; Kurek, J; Cwynar, LC; Mathewes, RW; Gajewski, K; Finney, BP. (2006) A northwest North American training set: distribution of freshwater midges in relation to air temperature and lake depth.Journal of Paleolimnology 36: 295-314 A northwest North American training set: distribution of freshwater midges in relation to air temperature and lake depth
chironomidae; transfer function; Beringia; air temperature; lake depth; canonical correspondence analysis; paleoclimate
Freshwater midges, consisting of Chironomidae, Chaoboridae and Ceratopogonidae, were assessed as a biological proxy for palaeoclimate in eastern Beringia. The northwest North American training set consists of midge assemblages and data for 17 environmental variables collected from 145 lakes in Alaska, British Columbia, Yukon, Northwest Territories, and the Canadian Arctic Islands. Canonical correspondence analyses (CCA) revealed that mean July air temperature, lake depth, arctic tundra vegetation, alpine tundra vegetation, pH, dissolved organic carbon, lichen woodland vegetation and surface area contributed significantly to explaining midge distribution. Weighted averaging partial least squares (WA-PLS) was used to develop midge inference models for mean July air temperature (r boot 2 = 0.818, RMSEP = 1.46°C), and transformed depth (ln (x+1); r boot 2 = 0.38, and RMSEP = 0.58).Website DOI
