Congruence between breeding and wintering biodiversity hotspots: A case study in farmlands of Western Poland

Farmland landscapes are recognized as important ecosystems, not only for their rich biodiversity but equally so for the human beings who live and work in these places. However, biodiversity varies among sites (spatial change) and among seasons (temporal change). In this work, we tested the hypothesis that bird diversity hotspots distribution for breeding is congruent with bird diversity hotspots for wintering season, focusing also the representation of protected areas for the conservation of local hotspots. We proposed a framework based on the  use of species richness, functional diversity, and evolutionary distinctiveness to characterize avian communities. Although our findings show that the spatial distribution of local bird hotspots differed slightly between seasons, the protected areas’ representation was similar in both seasons. Protected areas covered 65% of the most important zones for breeding and 71% for the wintering season in the farmland studied. Functional diversity showed similar patterns as did bird species richness, but this measure can be most effective for highlighting differences on bird community composition. Evolutionary distinctiveness was less congruent with species richness and functional diversity, among seasons. Our findings suggest that inter-seasonal spatial congruence of local hotspots can be considered as suitable areas upon which to concentrate greater conservation efforts. However, even considering the relative congruence of avian diversity metrics at a local spatial scale, simultaneous analysis of protected areas while inter-seasonally considering hotspots, can provide a more complete representation of ecosystems for assessing the conservation status and designating priority areas

Modelling the probability of building fires

Systematic spatial risk analysis plays a crucial role in preventing emergencies.In the Czech Republic, risk mapping is currently based on the risk accumulationprinciple, area vulnerability, and preparedness levels of Integrated Rescue Systemcomponents. Expert estimates are used to determine risk levels for individualhazard types, while statistical modelling based on data from actual incidents andtheir possible causes is not used. Our model study, conducted in cooperation withthe Fire Rescue Service of the Czech Republic as a model within the Liberec andHradec Králové regions, presents an analytical procedure leading to the creation ofbuilding fire probability maps based on recent incidents in the studied areas andon building parameters. In order to estimate the probability of building fires, aprediction model based on logistic regression was used. Probability of fire calculatedby means of model parameters and attributes of specific buildings can subsequentlybe visualized in probability maps

Habitats as predictors in species distribution models: Shall we use continuous or binary data?

The representation of a land cover type (i.e. habitat) within an area is often used as an explanatory variable in species distribution models. However, it is possible that a simple binary presence/absence of the suitable habitat might be the most important determinant of the presence/absence of some species and, thus, be a better predictor of species occurrence than the continuous parameter (area). We hypothesize that the binary predictor is more suitable for relatively rare habitats (e.g. wetlands) while for common habitats (e.g. forests) the amount of the focal habitat is a better predictor. We used the Third Atlas of Breeding Birds in the Czech Republic as the source of species distribution data and CORINE Land Cover inventory as the source of the landcover information. To test our hypothesis, we fitted generalized linear models of 32 water and 32 forest bird species. Our results show that for water bird species, models using binary predictors (presence/absence of the habitat) performed better than models with continuous predictors (i.e. the amount of the habitat); for forest species, however, we observed the opposite. Thus, future studies using habitats as predictors of species occurrences should consider the prevalence of the habitat in the landscape, and the biological role of the habitat type in the particular species' life history. In addition, performing a preliminary comparison of the performance of the binary and continuous versions of habitat predictors (e.g. using information criteria) prior to modelling, during variable selection, can be beneficial. These are simple steps that will improve explanatory and predictive performance of models of species distributions in biogeography, community ecology, macroecology and ecological conservation

Negative Regulation of Mast Cell Signaling and Function by the Adaptor LAB/NTAL

Engagement of the Fcɛ receptor I (FcɛRI) on mast cells and basophils initiates signaling pathways leading to degranulation. Early activation events include tyrosine phosphorylation of two transmembrane adaptor proteins, linker for activation of T cells (LAT) and non–T cell activation linker (NTAL; also called LAB; a product of Wbscr5 gene). Previous studies showed that the secretory response was partially inhibited in bone marrow–derived mast cells (BMMCs) from LAT-deficient mice. To clarify the role of NTAL in mast cell degranulation, we compared FcɛRI-mediated signaling events in BMMCs from NTAL-deficient and wild-type mice. Although NTAL is structurally similar to LAT, antigen-mediated degranulation responses were unexpectedly increased in NTAL-deficient mast cells. The earliest event affected was enhanced tyrosine phosphorylation of LAT in antigen-activated cells. This was accompanied by enhanced tyrosine phosphorylation and enzymatic activity of phospholipase C γ1 and phospholipase C γ2, resulting in elevated levels of inositol 1,4,5-trisphosphate and free intracellular Ca2+. NTAL-deficient BMMCs also exhibited an enhanced activity of phosphatidylinositol 3-OH kinase and Src homology 2 domain–containing protein tyrosine phosphatase-2. Although both LAT and NTAL are considered to be localized in membrane rafts, immunogold electron microscopy on isolated membrane sheets demonstrated their independent clustering. The combined data show that NTAL is functionally and topographically different from LAT

Double down on remote sensing for biodiversity estimation: a biological mindset

In the light of unprecedented planetary changes in biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential for informing policy and sustainable development. Biodiversity monitoring is a challenge, especially for large areas such as entire continents. Nowadays, spaceborne and airborne sensors provide information that incorporate wavelengths that cannot be seen nor imagined with the human eye. This is also now accomplished at unprecedented spatial resolutions, defined by the pixel size of images, achieving less than a meter for some satellite images and just millimeters for airborne imagery. Thanks to different modeling techniques, it is now possible to study functional diversity changes over different spatial and temporal scales. At the heart of this unifying framework are the “spectral species”—sets of pixels with a similar spectral signal—and their variability over space. The aim of this paper is to summarize the power of remote sensing for directly estimating plant species diversity, particularly focusing on the spectral species concept

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette

2.4-Å structure of the double-ring Gemmatimonas phototrophica photosystem.

Phototrophic Gemmatimonadetes evolved the ability to use solar energy following horizontal transfer of photosynthesis-related genes from an ancient phototrophic proteobacterium. The electron cryo-microscopy structure of the Gemmatimonas phototrophica photosystem at 2.4 Å reveals a unique, double-ring complex. Two unique membrane-extrinsic polypeptides, RC-S and RC-U, hold the central type 2 reaction center (RC) within an inner 16-subunit light-harvesting 1 (LH1) ring, which is encircled by an outer 24-subunit antenna ring (LHh) that adds light-gathering capacity. Femtosecond kinetics reveal the flow of energy within the RC-dLH complex, from the outer LHh ring to LH1 and then to the RC. This structural and functional study shows that G. phototrophica has independently evolved its own compact, robust, and highly effective architecture for harvesting and trapping solar energy

2.4-Å structure of the double-ring Gemmatimonas phototrophica photosystem.

Phototrophic Gemmatimonadetes evolved the ability to use solar energy following horizontal transfer of photosynthesis-related genes from an ancient phototrophic proteobacterium. The electron cryo-microscopy structure of the Gemmatimonas phototrophica photosystem at 2.4 Å reveals a unique, double-ring complex. Two unique membrane-extrinsic polypeptides, RC-S and RC-U, hold the central type 2 reaction center (RC) within an inner 16-subunit light-harvesting 1 (LH1) ring, which is encircled by an outer 24-subunit antenna ring (LHh) that adds light-gathering capacity. Femtosecond kinetics reveal the flow of energy within the RC-dLH complex, from the outer LHh ring to LH1 and then to the RC. This structural and functional study shows that G. phototrophica has independently evolved its own compact, robust, and highly effective architecture for harvesting and trapping solar energy

Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection

There is a lack of guidance on the choice of the spatial grain of predictor and response variables in species distribution models (SDM). This review summarizes the current state of the art with regard to the following points: (i) the effects of changing the resolution of predictor and response variables on model performance; (ii) the effect of conducting multi-grain versus single-grain analysis on model performance; and (iii) the role of land cover type and spatial autocorrelation in selecting the appropriate grain size. In the reviewed literature, we found that coarsening the resolution of the response variable typically leads to declining model performance. Therefore, we recommend aiming for finer resolutions unless there is a reason to do otherwise (e.g. expert knowledge of the ecological scale). We also found that so far, the improvements in model performance reported for multi-grain models have been relatively low and that useful predictions can be generated even from single-scale models. In addition, the use of high-resolution predictors improves model performance; however, there is only limited evidence on whether this applies to models with coarser-resolution response variables (e.g. 100 km2 and coarser). Low-resolution predictors are usually sufficient for species associated with fairly common environmental conditions but not for species associated with less common ones (e.g. common vs rare land cover category). This is because coarsening the resolution reduces variability within heterogeneous predictors and leads to underrepresentation of rare environments, which can lead to a decrease in model performance. Thus, assessing the spatial autocorrelation of the predictors at multiple grains can provide insights into the impacts of coarsening their resolution on model performance. Overall, we observed a lack of studies examining the simultaneous manipulation of the resolution of predictor and response variables. We stress the need to explicitly report the resolution of all predictor and response variables.Peer reviewe

From zero to infinity: Minimum to maximum diversity of the planet by spatio-parametric Rao's quadratic entropy

Aim: The majority of work done to gather information on the Earth's biodiversity has been carried out using in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s information theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, that is they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time.
 Innovation: The parametric Rao’s quadratic entropy, coded in R, (a) allows the representation of the whole continuum of potential diversity indices in one formula, and (b) starting from the Rao’s quadratic entropy, allows the explicit use of distances among pixel reflectance values, together with relative abundances.
 Main conclusions: The proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale. Being part of the rasterdiv R package, the proposed method is expected to ensure high robustness and reproducibility