Molecular diversity of Pseudoscorpiones in southern High Appalachian leaf litter

The Pseudoscorpiones fauna of North America is diverse, but in regions like the southern Appalachian Mountains, they are still poorly documented with respect to their species diversity, distributions and ecology. Several families have been reported from these mountains and neighbouring areas. Here we analyse barcoding data of 136 specimens collected in leaf litter, most of them from high-elevation coniferous forest. We used ASAP as a species delimitation method to obtain an estimation of the number of species present in the region. For this and based on interspecific genetic distance values previously reported in Pseudoscorpions, we considered three different genetic Kimura two-parameter distance thresholds (3%/5%/8%), to produce more or less conservative estimates. These distance thresholds resulted in 64/47/27 distinct potential species representing the families Chthoniidae (33/22/12 species) and Neobisiidae (31/25/15) and at least six different genera within them. The diversity pattern seems to be affected by the Asheville Depression, a major biogeographic barrier in this area, with a higher diversity to the west of this geographic feature, particularly within the family Neobisiidae. The absence of representatives from other families amongst our studied samples may be explained by differences in their ecological requirements and occupation of different microhabitats.

Hotspot in ferruginous rock may have serious implications in Brazilian conservation policy

A hotspot of subterranean Collembola in ferruginous rock caves and Mesovoid Shallow Substratum is revealed by the analysis of pseudocryptic diversity. The diversity is accessed by detailed description of chaetotaxy and slight variation in morphology of 11 new species of Trogolaphysa Mills, 1938 (Collembola, Paronellidae, Paronellinae) and the 50 previously recorded species of springtails from caves, using optical and electronic microscopy. When combined with recent subterranean surveys, our results show an important reservoir of cave diversity in the Mesovoid Shallow Substratum. Contrastingly the conservation policy for subterranean fauna in metallogenic areas in Brazil prioritizes the caves instead the cave species, which may be extremely detrimental to the fauna in the shallow subterranean habitats not accessible to humans.

A comparison of collecting methods in relation to the diversity of Collembola in scree habitats

We compared the species composition, relative abundances and life form structure of subterranean Collembola (Hexapoda) captured by two different methods along a depth gradient of five forested scree sites in the Western Carpathians, Slovakia: (1) high-gradient extraction of soil samples, and (2) collection using subterranean traps. Our results showed that the soil samples were more efficient in covering species richness at the majority of the sites. The body size of the captured animals depended remarkably on the sampling method. Extraction was more effective in collecting smaller, less active hemi- and euedaphic forms of Collembola, while collection by subterranean traps favoured both motile ground-dwelling as well as relatively large, active euedaphobionts. Additionally, different trends in the vertical stratification of Collembola life forms and their relative abundances were detected by the two methods. Atmobionts and epigeonts, forming the greater part of the communities in traps compared to soil samples, were distributed along the entire scree profiles, but their relative abundance and species numbers had a strongly decreasing trend with depth. Moreover, motile, large hemi- and euedaphic forms had high relative abundances in traps in the middle and deeper scree levels at three sites. In contrast, in soil samples the hemi- and euedaphobionts with small body size were abundant on the surface of the MSS sites. Thus, soil sampling applied before installation of subterranean traps may serve as an appropriate complementary technique to obtain a more complete pattern of Collembola diversity in forested scree habitats.

Advancing Cave Detection Using Terrain Analysis and Thermal Imagery

Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter “unenhanced thermal”) as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn— slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday— slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference— TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.