The Presence–Absence Situation and Its Impact on the Assemblage Structure and Interspecific Relations of Pronophilina Butterflies in the Venezuelan Andes (Lepidoptera: Nymphalidae)

Assemblage structure and altitudinal patterns of Pronophilina, a species-rich group of Andean butterflies, are compared in El Baho and Monte Zerpa, two closely situated and ecologically similar Andean localities. Their faunas differ only by the absence of Pedaliodes ornata Grose-Smith in El Baho. There are, however, important structural differences between the two Pronophilina assemblages. Whereas there are five co-dominant species in Monte Zerpa, including P. ornata, Pedaliodes minabilis Pyrcz is the only dominant with more than half of all the individuals in the sample in El Baho. The absence of P. ornata in El Baho is investigated from historical, geographic, and ecological perspectives exploring the factors responsible for its possible extinction including climate change, mass dying out of host plants, and competitive exclusion. Although competitive exclusion between P. ornata and P. minabilis is a plausible mechanism, considered that their ecological niches overlap, which suggests a limiting influence on each other’s populations, the object of competition was not identified, and the reason of the absence of P. ornata in El Baho could not be established. The role of spatial interference related to imperfect sexual behavioral isolation is evaluated in maintaining the parapatric altitudinal distributions of three pairs of phenotypically similar and related species of Pedaliodes, Corades, and Lymanopoda

Revalidation of Pedaliodes lithochalcis BUTLER & DRUCE, description of a new species from Peru and Bolivia and of a new subspecies of P. napaea BATES from Honduras (Lepidoptera : Nymphalidae : Satyrinae)

Pedaliodes lithochalcis, occurring in Costa Rica and Panama, has been considered for more than a century a junior synonym of P. dejecta from Guatemala. It is reinstated here as a valid species. It is shown that the two species belong to different groups of species with sympatric representatives throughout Central America and the Andes characterized by common characters of adult morphology, particularly the male genitalia. Pedaliodes lithochalcis is closely related to P. napaea whose new subspecies, P. napaea naksi n. ssp., is described from the Celaque massif in Honduras. It is the first cloud forest Satyrinae butterfly described from this country. Pedaliodes dejecta is related to another Mesoamerican species, P. ereiba, and to P. pomponia from Ecuador and to a new species, P. peregrina n. sp., from Peru and Bolivia

Rigid Transformations for Stabilized Lower Dimensional Space to Support Subsurface Uncertainty Quantification and Interpretation

Subsurface datasets inherently possess big data characteristics such as vast volume, diverse features, and high sampling speeds, further compounded by the curse of dimensionality from various physical, engineering, and geological inputs. Among the existing dimensionality reduction (DR) methods, nonlinear dimensionality reduction (NDR) methods, especially Metric-multidimensional scaling (MDS), are preferred for subsurface datasets due to their inherent complexity. While MDS retains intrinsic data structure and quantifies uncertainty, its limitations include unstabilized unique solutions invariant to Euclidean transformations and an absence of out-of-sample points (OOSP) extension. To enhance subsurface inferential and machine learning workflows, datasets must be transformed into stable, reduced-dimension representations that accommodate OOSP. Our solution employs rigid transformations for a stabilized Euclidean invariant representation for LDS. By computing an MDS input dissimilarity matrix, and applying rigid transformations on multiple realizations, we ensure transformation invariance and integrate OOSP. This process leverages a convex hull algorithm and incorporates loss function and normalized stress for distortion quantification. We validate our approach with synthetic data, varying distance metrics, and real-world wells from the Duvernay Formation. Results confirm our method's efficacy in achieving consistent LDS representations. Furthermore, our proposed "stress ratio" (SR) metric provides insight into uncertainty, beneficial for model adjustments and inferential analysis. Consequently, our workflow promises enhanced repeatability and comparability in NDR for subsurface energy resource engineering and associated big data workflows.Comment: 30 pages, 17 figures, Submitted to Computational Geosciences Journa