Unveiling the factors shaping the distribution of widely distributed alpine vertebrates, using multi-scale ecological niche modelling of the bat Plecotus macrobullaris

Several alpine vertebrates share a distribution pattern that extends across the South-western Palearctic but is limited to the main mountain massifs. Although they are usually regarded as cold-adapted species, the range of many alpine vertebrates also includes relatively warm areas, suggesting that factors beyond climatic conditions may be driving their distribution. In this work we first recognize the species belonging to the mentioned biogeographic group and, based on the environmental niche analysis of Plecotus macrobullaris, we identify and characterize the environmental factors constraining their ranges. Distribution overlap analysis of 504 European vertebrates was done using the Sorensen Similarity Index, and we identified four birds and one mammal that share the distribution with P. macrobullaris. We generated 135 environmental niche models including different variable combinations and regularization values for P. macrobullaris at two different scales and resolutions. After selecting the best models, we observed that topographic variables outperformed climatic predictors, and the abruptness of the landscape showed better predictive ability than elevation. The best explanatory climatic variable was mean summer temperature, which showed that P. macrobullaris is able to cope with mean temperature ranges spanning up to 16 degrees C. The models showed that the distribution of P. macrobullaris is mainly shaped by topographic factors that provide rock-abundant and open-space habitats rather than climatic determinants, and that the species is not a cold-adapted, but rather a cold-tolerant eurithermic organism. P. macrobullaris shares its distribution pattern as well as several ecological features with five other alpine vertebrates, suggesting that the conclusions obtained from this study might be extensible to them. We concluded that rock-dwelling and open-space foraging vertebrates with broad temperature tolerance are the best candidates to show wide alpine distribution in the Western Palearctic.

Niche measures and feeding strategies of Barbodes gonionotus Bleeker and Oreochromis spp. from a ricefield in Bangladesh

Intra-and interspecific virtual niche measures and feeding strategies of Barbodes gonionotus and Oreochromis spp. were studied from a rice field in Bangladesh. Appropriateness and ease of interpretation of different indices were evaluated. Small sizes of both species had a relatively wider dietary breadth and used many of the resource categories available to them than the large size groups, though none were generalist feeder. The dietary overlap of large B. gonionotus on the small was greater than the reverse, but biologically insignificant. While the dietary overlap of large Oreochromis spp. on the small was significantly greater. Interspecific dietary width was relatively broader for B. gonionotus than Oreochromis spp. and overlap of B. gonionotus on Oreochromis spp. was significantly greater than the reverse. Evidence of significant intraspecific dietary overlap between the two sizes of tilapia reflects strong competition and cautions for mixed-size stocking in rice-fish system. Besides, there seem fewer opportunities for habitat segregation between B. gonionotus and Oreochromis spp., due to the significant interspecific dietary overlap of the former on the latter in rice-fish system. Tilapia specialized on periphytic detrital aggregate while silver barb tended to consume aquatic macrophytes and molluscs. Small sizes of B. gonionotus should be preferred for rice-fish integration over the Oreochromis spp. due to their broader niche width and pronounced ontogenetic dietary shifts with the aging of the stock.

Beyond niche thinking: Market selection in science-based ventures

Matching a new technology to an appropriate market is a major challenge for new technology-based firms (NTBF). Such firms are often advised to target niche-markets where the firms and their technologies can establish themselves relatively free of incumbent competition. However, technologies are diverse in nature and do not benefit from identical strategies. In contrast to many Information and Communication Technology (ICT) innovations which build on an established knowledge base for fairly specific applications, technologies based on emerging science are often generic and so have a number of markets and applications open to them, each carrying considerable technological and market uncertainty. Each of these potential markets is part of a complex and evolving ecosystem from which the venture may have to access significant complementary assets in order to create and sustain commercial value. Based on dataset and case study research on UK advanced material university spin-outs (USO), we find that, contrary to conventional wisdom, the more commercially successful ventures were targeting mainstream markets by working closely with large, established competitors during early development. While niche markets promise protection from incumbent firms, science-based innovations, such as new materials, often require the presence, and participation, of established companies in order to create value. © 2012 IEEE.

Solving MIN UR problem by triangle evolution algorithm with archiving and niche techniques

In this paper, as an extension of minimum unsatisfied linear relations problem (MIN ULR), the minimum unsatisfied relations (MIN UR) problem is investigated. A triangle evolution algorithm with archiving and niche techniques is proposed for MIN UR problem. Different with algorithms in literature, it solves MIN problem directly, rather than transforming it into many sub-problems. The proposed algorithm is also applicable for the special case of MIN UR, in which it involves some mandatory relations. Numerical results show that the algorithm is effective for MIN UR problem and it outperforms Sadegh's algorithm in sense of the resulted minimum inconsistency number, even though the test problems are linear.

Simple procedures to assess and compare the ecological niche of species

Hutchinson's (1957; Cold Spring Harbour Symp Quant Biol 22:415-427) niche concept is being used increasingly in the context of global change, and is currently applied to many ecological issues including climate change, exotic species invasion and management of endangered species. For both the marine and terrestrial realms, there is a growing need to assess the breadth of the niches of individual species and to make comparisons among them to forecast the species' capabilities to adapt to global change. In this paper, we describe simple non-parametric multivariate procedures derived from a method originally used in climatology to (1) evaluate the breadth of the ecological niche of a species and (2) examine whether the niches are significantly separated. We first applied the statistical procedures to a simple fictive example of 3 species separated by 2 environmental factors in order to describe the technique. We then used it to quantify and compare the ecological niche of 2 key-structural marine zooplankton copepod species, Calanus finmarchicus and C. helgolandicus, in the northern part of the North Atlantic Ocean using 3 environmental factors. The test demonstrates that the niches of both species are significantly separated and that the coldwater species has a niche larger than that of its warmer-water congeneric species.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.