Simulium (Inaequalium) marins, a new species of black fly (Diptera: Simuliidae) from inselbergs in Brazil

A new species of black fly, Simulium (Inaequalium) marins (Diptera: Simuliidae), is described based on the male, female, pupa and larva. This new species was collected from two localities: a small stream on the Pico dos Marins, a high mountain with granite outcrops in Piquete County, state of São Paulo, and in a small stream in the Serra dos Órgãos National Park, state of Rio de Janeiro, Brazil

An FPTAS for optimizing a class of low-rank functions over a polytope

We present a fully polynomial time approximation scheme (FPTAS) for optimizing a very general class of non-linear functions of low rank over a polytope. Our approximation scheme relies on constructing an approximate Pareto-optimal front of the linear functions which constitute the given low-rank function. In contrast to existing results in the literature, our approximation scheme does not require the assumption of quasi-concavity on the objective function. For the special case of quasi-concave function minimization, we give an alternative FPTAS, which always returns a solution which is an extreme point of the polytope. Our technique can also be used to obtain an FPTAS for combinatorial optimization problems with non-linear objective functions, for example when the objective is a product of a fixed number of linear functions. We also show that it is not possible to approximate the minimum of a general concave function over the unit hypercube to within any factor, unless P = NP. We prove this by showing a similar hardness of approximation result for supermodular function minimization, a result that may be of independent interest

The flora and vegetation of rocky outcrops in three municipalities in the northern region of Ceará, Brazil: phytosociological characterization

Veja material suplementar em <https://doi.org/10.6084/m9.figshare.5915233.v2O presente estudo teve como objetivo identificar a flora e a vegetação dos afloramentos rochosos isolados e de baixa altitude (lajedos), na vegetação de Caatinga Arbustiva Aberta, que se encontram nos municípios de Sobral, Groaíras e Santa Quitéria, no estado do Ceará, Brasil e propor uma classificação fitossociológica para estas comunidades xerófilas. Foram definidas cinco áreas de coleta de dados com elevada proporção de rochas expostas (> 80%) onde as excursões de campo decorreram em março de 2014 e 2015 (3º56’S e 40º23’W, 4º01’S e 40º05’W, 4º07’S e 40º08’W, 4º09’S e 40º09’W e 4º03’S e 40º00’W). No estudo da vegetação aplicou-se os métodos TWINSPAN (two-way indicator species analysis) e o clássico sigmatista de Braun-Blanquet. As áreas mínimas dos inventários fitossociológicos variaram de 8 a 16 m2. Foram coletadas as espécies vegetais que crescem em fissuras, fendas e ilhas de vegetação que se encontram em afloramentos rochosos. Foram registradas 88 espécies, distribuídas em 59 gêneros e 30 famílias botânicas. Fabaceae foi a família que se destacou em riqueza específica (20 spp.), seguida por Poaceae (dez spp.), Euphorbiaceae (sete spp.) e Convolvulaceae (seis spp.). Quanto ao endemismo foram registradas, em vegetação rupestre, 19 espécies endêmicas para o Brasil. Na análise fitossociológica da vegetação propôs-se estudar a comunidade de Pilosocereus gounellei (FA.C.Weber) Byles & Rowley e Encholirium spectabile Mart. ex Schult. & Schult.f. e a de Crateva tapia L. e Combretum leprosum Martinfo:eu-repo/semantics/publishedVersio

High-resolution distribution modeling of a threatened short-range endemic plant informed by edaphic factors

Short-range endemic plants often have edaphic specializations that, with their restricted distributions, expose them to increased risk of anthropogenic extinction. Here, we present a modeling approach to understand habitat suitability for Ricinocarpos brevis R.J.F.Hend. & Mollemans (Euphorbiaceae), a threatened shrub confined to three isolated populations in the semi-arid south-west of Western Australia. The model is a maximum entropy species distribution projection constructed on the basis of physical soil characteristics and geomorphology data at approximately 25 m2 (1 arc-second) resolution. The model predicts the species to occur on shallow, low bulk density soils that are located high in the landscape. The model shows high affinity (72.1% average likelihood of occurrence) for the known populations of R. brevis, as well as identifying likely locations that are not currently known to support the species. There was a strong relationship between the likelihood of R. brevis occurrence and soil moisture content that the model estimated at a depth of 20 cm. We advocate that our approach should be standardized using publicly available data to generate testable hypotheses for the distribution and conservation management of short-range endemic plant species for all of continental Australia

Rapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot

Identification of refugia is an increasingly important adaptation strategy in conservation planning under rapid anthropogenic climate change. Granite outcrops (GOs) provide extraordinary diversity, including a wide range of taxa, vegetation types and habitats in the Southwest Australian Floristic Region (SWAFR). However, poor characterization of GOs limits the capacity of conservation planning for refugia under climate change. A novel means for the rapid identification of potential refugia is presented, based on the assessment of local-scale environment and vegetation structure in a wider region. This approach was tested on GOs across the SWAFR. Airborne discrete return Light Detection And Ranging (LiDAR) data and Red Green and Blue (RGB) imagery were acquired. Vertical vegetation profiles were used to derive 54 structural classes. Structural vegetation types were described in three areas for supervised classification of a further 13 GOs across the region.Habitat descriptions based on 494 vegetation plots on and around these GOs were used to quantify relationships between environmental variables, ground cover and canopy height. The vegetation surrounding GOs is strongly related to structural vegetation types (Kappa = 0.8) and to its spatial context. Water gaining sites around GOs are characterized by taller and denser vegetation in all areas. The strong relationship between rainfall, soil-depth, and vegetation structure (R2 of 0.8–0.9) allowed comparisons of vegetation structure between current and future climate. Significant shifts in vegetation structural types were predicted and mapped for future climates. Water gaining areas below granite outcrops were identified as important putative refugia. A reduction in rainfall may be offset by the occurrence of deeper soil elsewhere on the outcrop. However, climate change interactions with fire and water table declines may render our conclusions conservative. The LiDAR-based mapping approach presented enables the integration of site-based biotic assessment with structural vegetation types for the rapid delineation and prioritization of key refugia