Experimental evidence for niche segregation in a sister species pair of non-biting midges

Abstract

The principle of limiting similarity states that closely related species need to partition resources of the habitat in order to coexist in the same general area. We tested this hypothesis experimentally with a sister species pair of non-biting midges (Chironomus riparius and C. piger) by assessing their relative larval fitness under several concentrations of nitrite and temperature regimes, as suggested by the observed habitat segregation in a previous field study. Both chironomid species often occur in eutrophic habitats like agricultural areas or industrial point source effluents. Based on field observations, we hypothesised C. piger to tolerate higher nitrite concentrations, higher temperatures and larger temperature ranges than C. riparius. As predicted, C. piger coped better with higher nitrite concentrations. Against the expectations, C. riparius had a tendentially higher fitness at both higher constant temperatures and larger daily temperature ranges. However, the interaction of both stressors favoured C. piger in warm high-nitrite habitats thus concurring to the field observations. The complex interaction of candidate environmental factors with antagonistic effects found here emphasises thus the necessity to experimentally assess field observations of niche segregation.

Genomic basis of ecological niche divergence among cryptic sister species of non-biting midges

“…Contrary to expectations from field studies, C. riparius ’ fitness tended to be higher at both higher constant temperatures and larger daily temperature ranges. However, the interaction of both stressors favoured C. piger in warm, high nitrite habitats, thus concurring to the field observations [36]. Based on this previous knowledge on ecological niche differences, proteins with functions in cell respiration as well as those concerning response to temperature and solved ions, especially nitrite detoxification, are promising candidates for interspecific differences driven by positive selection.…”

“…One of the main environmental agents causing the formation of detrimental methaemoglobin are nitrate/nitrite [67], thus matching the observed and experimentally confirmed differential adaptation of the chironomid sister species to environmental nitrite concentrations [29,36]. An increased efficiency due to positive selection in converting methaemoglobine would certainly explain the higher nitrite tolerance of C. piger and thus identify a genomic basis for the observed niche difference.…”

“…The latter species often inhabits sediments with high organic content, indicating higher tolerance to anaerobic conditions [33], which was confirmed in different experimental studies [34,35]. In a recent experimental study C. piger coped better with higher nitrite concentrations [36]. Contrary to expectations from field studies, C. riparius ’ fitness tended to be higher at both higher constant temperatures and larger daily temperature ranges.…”

“…The Chironomus riparius and C. piger specimen used in this study were taken from laboratory cultures originally collected in 2009 from the field in south-western Germany as described in Nemec et al [36]. The species were kept in relatively large (> 400 individuals) populations for about 3–4 generations prior to the present study.…”

Support for the evolutionary speed hypothesis from intraspecific population genetic data in the non-biting midgeChironomus riparius

“…Population differentiation was measured as population pairwise F ST values, to reflect the correlation of haplotypic diversity [44], in ARLEQUIN v. 3.5.1.2 [45]. To account for the effect of geography on population differentiation (isolation-bydistance) expected for this species [34], we regressed the population To estimate mutation accumulation and as an additional measure of intrapopulation drift, we calculated the average population distance from the ancestral haplotype for all populations and all markers. The most likely ancestral haplotype was inferred using the statistical parsimony principles detailed by Pfenninger & Posada [46] using the software TCS [47].…”