Major range loss predicted from lack of heat adaptability in an alpine Drosophila species.

Climate warming is threatening biodiversity worldwide. Climate specialists such as alpine species are especially likely to be vulnerable. Adaptation by rapid evolution is the only long-term option for survival of many species, but the adaptive evolutionary potential of heat resistance has not been assessed in an alpine invertebrate. Here, we show that the alpine fly Drosophila nigrosparsa cannot readily adapt to heat stress. Heat-exposed flies from a regime with increased ambient temperature and a regime with increased temperature plus artificial selection for heat tolerance were less heat tolerant than the control group. Increased ambient temperature affected negatively both fitness and competitiveness. Ecological niche models predicted the loss of three quarters of the climatically habitable areas of this fly by the end of this century. Our findings suggest that, alongside with other climate specialists, species from mountainous regions are highly vulnerable to climate warming and unlikely to adapt through evolutionary genetic changes.

Life-history traits and physiological limits of the alpine fly Drosophila nigrosparsa (Diptera: Drosophilidae): A comparative study.

Interspecific variation in life-history traits and physiological limits can be linked to the environmental conditions species experience, including climatic conditions. As alpine environments are particularly vulnerable under climate change, we focus on the montane-alpine fly Drosophila nigrosparsa. Here, we characterized some of its life-history traits and physiological limits and compared these with those of other drosophilids, namely Drosophila hydei, Drosophila melanogaster, and Drosophila obscura. We assayed oviposition rate, longevity, productivity, development time, larval competitiveness, starvation resistance, and heat and cold tolerance. Compared with the other species assayed, D. nigrosparsa is less fecund, relatively long-living, starvation susceptible, cold adapted, and surprisingly well heat adapted. These life-history characteristics provide insights into invertebrate adaptations to alpine conditions which may evolve under ongoing climate change.

Oviposition Substrate of the Mountain Fly Drosophila nigrosparsa (Diptera: Drosophilidae).

The survival of insect larvae often depends on the mother's choice of oviposition substrate, and thus, this choice is an essential part of an insect species' ecology. Especially species with narrow substrate preferences may suffer from changes in substrate availability triggered by, for example, climate change. Recent climate warming is affecting species directly (e.g., physiology) but also indirectly (e.g., biological interactions) leading to mismatching phenologies and distributions. However, the preferred oviposition substrate is still unknown for many drosophilid species, especially for those at higher elevations. In this study, we investigated the oviposition-substrate preference of the montane-alpine fly Drosophila nigrosparsa in rearing and multiple-choice experiments using natural substrates in the laboratory. Insect emergence from field-collected substrates was tested. More than 650 insects were reared from natural substrates, among them 152 drosophilids but no individual of D. nigrosparsa. In the multiple-choice experiments, D. nigrosparsa preferred ovipositing on mushrooms (> 93% of eggs); additionally, a few eggs were laid on berries but none on other substrates such as cow faeces, rotten plant material, and soil. The flies laid 24 times more eggs per day when mushrooms were included in the substrates than when they were excluded. We infer that D. nigrosparsa is a mushroom breeder with some variation in oviposition choice. The flies favoured some mushrooms over others, but they were not specialised on a single fungal taxon. Although it is unclear if and how climate change will affect D. nigrosparsa, our results indicate that this species will not be threatened by oviposition-substrate limitations in the near future because of the broad altitudinal distribution of the mushrooms considered here, even if the flies will have to shift upwards to withstand increasing temperatures.

A near-infrared spectroscopy routine for unambiguous identification of cryptic ant species.

Species identification-of importance for most biological disciplines-is not always straightforward as cryptic species hamper traditional identification. Fibre-optic near-infrared spectroscopy (NIRS) is a rapid and inexpensive method of use in various applications, including the identification of species. Despite its efficiency, NIRS has never been tested on a group of more than two cryptic species, and a working routine is still missing. Hence, we tested if the four morphologically highly similar, but genetically distinct ant species Tetramorium alpestre, T. caespitum, T. impurum, and T. sp. B, all four co-occurring above 1,300 m above sea level in the Alps, can be identified unambiguously using NIRS. Furthermore, we evaluated which of our implementations of the three analysis approaches, partial least squares regression (PLS), artificial neural networks (ANN), and random forests (RF), is most efficient in species identification with our data set. We opted for a 100% classification certainty, i.e., a residual risk of misidentification of zero within the available data, at the cost of excluding specimens from identification. Additionally, we examined which strategy among our implementations, one-vs-all, i.e., one species compared with the pooled set of the remaining species, or binary-decision strategies, worked best with our data to reduce a multi-class system to a two-class system, as is necessary for PLS. Our NIRS identification routine, based on a 100% identification certainty, was successful with up to 66.7% of unambiguously identified specimens of a species. In detail, PLS scored best over all species (36.7% of specimens), while RF was much less effective (10.0%) and ANN failed completely (0.0%) with our data and our implementations of the analyses. Moreover, we showed that the one-vs-all strategy is the only acceptable option to reduce multi-class systems because of a minimum expenditure of time. We emphasise our classification routine using fibre-optic NIRS in combination with PLS and the one-vs-all strategy as a highly efficient pre-screening identification method for cryptic ant species and possibly beyond.