7 research outputs found

    The Arthropod Fauna of Oak (Quercus spp., Fagaceae) Canopies in Norway

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    (1) We document the invertebrate fauna collected from 24 oak canopies in east and west Norway as a contribution to the Norwegian Biodiversity Information Centre’s ‘The Norwegian Taxonomy Initiative’. (2) A snap-shot inventory of the canopies was recorded by means of emitting a mist of natural pyrethrum into the canopies at night using a petrol-driven fogger and collecting the specimens in butterfly nets spread on the ground under the canopy. (3) Almost the entire catch of more than 6800 specimens was identified to 722 species. Out of 92 species new to the Norwegian fauna, 21 were new to science and, additionally, 15 were new to the Nordic fauna. Diptera alone constituted nearly half of the species represented, with 61 new records (18 new species). Additionally, 24 Hymenoptera (one new species), six oribatid mites (two new species) and one Thysanoptera were new to the Norwegian fauna. (4) Our study emphasizes the importance of the oak tree as a habitat both for a specific fauna and occasional visitors, and it demonstrates that the canopy fogging technique is an efficient way to find the ‘hidden fauna’ of Norwegian forests. The low number of red listed species found reflects how poor the Norwegian insect fauna is still studied. Moreover, the implication of the IUCN red list criteria for newly described or newly observed species is discussed.</jats:p

    Comprehensive inventory of true flies (Diptera) at a tropical site

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    Estimations of tropical insect diversity generally suffer from lack of known groups or faunas against which extrapolations can be made, and have seriously underestimated the diversity of some taxa. Here we report the intensive inventory of a four-hectare tropical cloud forest in Costa Rica for one year, which yielded 4332 species of Diptera, providing the first verifiable basis for diversity of a major group of insects at a single site in the tropics. In total 73 families were present, all of which were studied to the species level, providing potentially complete coverage of all families of the order likely to be present at the site. Even so, extrapolations based on our data indicate that with further sampling, the actual total for the site could be closer to 8000 species. Efforts to completely sample a site, although resource-intensive and time-consuming, are needed to better ground estimations of world biodiversity based on limited sampling

    Comparing Global Sentinel-2 Land Cover Maps for Regional Species Distribution Modeling

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    Mapping the spatial and temporal dynamics of species distributions is necessary for biodiversity conservation land-use planning decisions. Recent advances in remote sensing and machine learning have allowed for high-resolution species distribution modeling that can inform landscape-level decision-making. Here we compare the performance of three popular Sentinel-2 (10-m) land cover maps, including dynamic world (DW), European land cover (ELC10), and world cover (WC), in predicting wild bee species richness over southern Norway. The proportion of grassland habitat within 250 m (derived from the land cover maps), along with temperature and distance to sandy soils, were used as predictors in both Bayesian regularized neural network and random forest models. Models using grassland habitat from DW performed best (RMSE = 2.8 ± 0.03; average ± standard deviation across models), followed by ELC10 (RMSE = 2.85 ± 0.03) and WC (RMSE = 2.87 ± 0.02). All satellite-derived maps outperformed a manually mapped Norwegian land cover dataset called AR5 (RMSE = 3.02 ± 0.02). When validating the model predictions of bee species richness against citizen science data on solitary bee occurrences using generalized linear models, we found that ELC10 performed best (AIC = 2278 ± 4), followed by WC (AIC = 2367 ± 3), and DW (AIC = 2376 ± 3). While the differences in RMSE we observed between models were small, they may be significant when such models are used to prioritize grassland patches within a landscape for conservation subsidies or management policies. Partial dependencies in our models showed that increasing the proportion of grassland habitat is positively associated with wild bee species richness, thereby justifying bee conservation schemes that aim to enhance semi-natural grassland habitat. Our results confirm the utility of satellite-derived land cover maps in supporting high-resolution species distribution modeling and suggest there is scope to monitor changes in species distributions over time given the dense time series provided by products such as DW
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