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In forensic science, fly larval size and developmental time help to estimate the time elapsed since a person has died until the body is found, generally known as minimum postmortem interval (mPMI). Lucilia sericata (Meigen 1826) is a cosmopolitan and necrophagous fly species (Diptera: Calliphoridae) that usually colonizes decomposing stages. In this study, we determined life tables parameters of L. sericata (e.g. fly survivorship, mortality and life expectancy) and developmental time of different larval stages under controlled temperatures. Cohorts of 12 eggs (12 x 10 repetitions) of L. sericata were exposed to 8°C, 10°C, 18°C, 25°C, 30°C, 35°C, and 37 ± 0.5°C. We found that larval development was not complete at 8°C and 10°C (minimum temperature limit), and at 35°C and 37°C (maximum temperature limit). The number of larvae that reached the adult stage was similar (F2,30 = 0.20, p = 0.814) at all viable temperatures (18°C, 25°C, and 30°C). We found the highest mortality to occur at initial developmental stages. Under viable temperatures, the developmental time of L. sericata from egg to adult decreases with temperature, with an average of 778 h at 18°C, 401 h at 25°C, and 288 h at 30°C. The developmental time of L. sericata at the fastest temperature (778 h) is similar to that found in Vienna (Austria), but it is 2–3 times slower than that in three cities across the United States. These results will improve the estimation of mPMIs in tropical countries across the Andes region [ABSTRACT FROM AUTHOR]

Composition, diversity, and structure of trees in tropical montane forests are responsive to ecological gradients and local succession. Those parameters are a result of ecological interactions between vegetation, environment, and location. This study identified floristic groups on mainly secondary forests and evaluated how the composition, diversity, and structure of trees correlate with climate, soil, and age since abandonment. We included in our models a measurement of spatial correlation, to explore the role of dispersion. For this purpose, we measured diameter and height of all trees with DBH ≥ 10 cm, in twenty-eight 500 m2 plots, in an elevation range between 2900 and 3500 m. We found 14 indicator species in three floristic groups. Group composition was explained by age since abandonment, which showed strong succession effects. Mean monthly precipitation and Manganese, but not spatial correlation, explained plant composition in these montane forests, suggesting a minor role of dispersion. Species richness and structure of the arboreal vegetation were influenced by interactions between age, precipitation, and soil nutrients concentration. We concluded that in fragmented landscapes, within the rugged region of southern Ecuador, it is possible to find different floristic groups that encompass high variation in their composition. [ABSTRACT FROM AUTHOR]

Texture information from passive remote sensing images provides surrogates for habitat structure, which is relevant for modeling biodiversity across space and time and for developing effective ecological indicators. However, the applicability of this information might differ among taxa and diversity measures. We compared the ability of indicators developed from texture analysis of remotely sensed images to predict species richness and species turnover of six taxa (trees, pyraloid moths, geometrid moths, arctiinae moths, ants, and birds) in a megadiverse Andean mountain rainforest ecosystem. Partial least-squares regression models were fitted using 12 predictors that characterize the habitat and included three topographical metrics derived from a high-resolution digital elevation model and nine texture metrics derived from very high-resolution multi-spectral orthophotos. We calculated image textures derived from mean, correlation, and entropy statistics within a relatively broad moving window (102 m × 102 m) of the near infra-red band and two vegetation indices. The model performances of species richness were taxon dependent, with the lowest predictive power for arctiinae moths (4%) and the highest for ants (78%). Topographical metrics sufficiently modeled species richness of pyraloid moths and ants, while models for species richness of trees, geometrid moths, and birds benefited from texture metrics. When more complexity was added to the model such as additional texture statistics calculated from a smaller moving window (18 m × 18 m), the predictive power for trees and birds increased significantly from 12% to 22% and 13% to 27%, respectively. Gradients of species turnover, assessed by non-metric two-dimensional scaling (NMDS) of Bray-Curtis dissimilarities, allowed the construction of models with far higher predictability than species richness across all taxonomic groups, with predictability for the first response variable of species turnover ranging from 64% (birds) to 98% (trees) of the explained change in species composition, and predictability for the second response variable of species turnover ranging from 33% (trees) to 74% (pyraloid moths). The two NMDS axes effectively separated compositional change along the elevational gradient, explained by a combination of elevation and texture metrics, from more subtle, local changes in habitat structure surrogated by varying combinations of texture metrics. The application of indicators arising from texture analysis of remote sensing images differed among taxa and diversity measures. However, these habitat indicators improved predictions of species diversity measures of most taxa, and therefore, we highly recommend their use in biodiversity research. [ABSTRACT FROM AUTHOR]