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Bat‐borne pathogens are a threat to global health and in recent history have had major impacts on human morbidity and mortality. Examples include diseases such as rabies, Nipah virus encephalitis, and severe acute respiratory syndrome (SARS). Climate change may exacerbate the emergence of bat‐borne pathogens by affecting the ecology of bats in tropical ecosystems. Here, we report the impacts of climate change on the distributional ecology of the common vampire bat Desmodus rotundus across the last century. Our retrospective analysis revealed a positive relationship between changes in climate and the northern expansion of the distribution of D. rotundus in North America. Furthermore, we also found a reduction in the standard deviation of temperatures at D. rotundus capture locations during the last century, expressed as more consistent, less‐seasonal climate in recent years. These results elucidate an association between D. rotundus range expansion and a continental‐level rise in rabies virus spillover transmission from D. rotundus to cattle in the last 50 years of the 120‐year study period. This correlative study, based on field observations, offers empirical evidence supporting previous statistical and mathematical simulation‐based studies reporting a likely increase of bat‐borne diseases in response to climate change. We conclude that the D. rotundus rabies system exemplifies the consequences of climate change augmentation at the wildlife–livestock–human interface, demonstrating how global change acts upon these complex and interconnected systems to drive increased disease emergence. [ABSTRACT FROM AUTHOR]

Copyright of Methods in Ecology & Evolution is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Biodiversity metrics have become a ubiquitous component of conservation assessments across scales. However, whilst indices have become increasingly widely used, their ability to perform in the face of different biases has remained largely untested under realistic conditions. Citizen science data are increasingly available, but present new challenges and biases, thus understanding how to use them effectively is essential. Here, we built a virtual world incorporating BirdLife data and accounting for their biases, then explored how well commonly‐used diversity metrics could estimate known values across a suite of representative scenarios. We used predictive modelling to model bird diversity globally and overcome biases using the approaches found most accurate in prior assessments. Performance was highly variable across the different types of biases, but in many instances Simpson's index performed best, followed by Hill numbers, whereas Pielou's index was almost universally worst. From standardised tests, we then applied these metrics to eBird data using 611 520 112 samples of 10 359 species of bird (around 88% of known species), to reconstruct global diversity patterns at five and ten km resolutions. However, when we mapped out diversity using Maxent based on these indices, Simpson's index generally over‐predicted diversity, whereas Hill numbers were more conservative. Based on an average of the better projected indices, one can map out diversity across resolutions and overcome biases accurately predicting diversity patterns even for data‐poor areas, but if a single metric is used, Hill numbers are most robust to bias. Going forward, this workflow will enable standardized best practices for diversity mapping based on a clear understanding of the performance of different metrics. [ABSTRACT FROM AUTHOR]

Covalent triazine frameworks (CTFs) are promising heterogeneous photocatalyst candidates owing to their excellent stability, conjugacy, and tunability. In this study, a series of CTFs decorated with different substituents (H, MeO, and F) were synthesised and utilised as photocatalysts for C−H activation reactions. The corresponding optoelectronic properties could be precisely regulated by the electronic effects of different substituents in the nanopore channels of the CTFs; these CTFs were effective photocatalysts for C−H activation in organic synthesis due to their unique structures and optoelectronic properties. Methoxy‐substituted CTF (MeO‐CTF) exhibited extraordinary catalytic performance and reusability in C−H functionalization by constructing an electronic donor‐acceptor system, achieving the highest yield in the photocatalytic C3–H hydroxylation of 2‐phenylimidazole[1,2‐α]pyridine. This strategy provides a new scaffold for the rational design of CTFs as efficient photocatalysts for organic synthesis. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Our knowledge of biodiversity hinges on sufficient data, reliable methods, and realistic models. Without an accurate assessment of species distributions, we cannot effectively target and stem biodiversity loss. Species range maps are the foundation of such efforts, but countless studies have failed to account for the most basic assumptions of reliable species mapping practices, undermining the credibility of their results and potentially misleading and hindering conservation and management efforts. Here, we use examples from the recent literature and broader conservation community to highlight the substantial shortfalls in current practices and their consequences for both analyses and conservation management. We detail how different decisions on data filtering impact the outcomes of analysis and provide practical recommendations and steps for more reliable analysis, whilst understanding the limits of what available data will reliably allow and what methods are most appropriate. Whilst perfect analyses are not possible for many taxa given limited data, and biases, ensuring we use data within reasonable limits and understanding inherent assumptions is crucial to ensure appropriate use. By embracing and enacting such best practices, we can ensure both the accuracy and improved comparability of biodiversity analyses going forward, ultimately enhancing our ability to use data to facilitate our protection of the natural world. [ABSTRACT FROM AUTHOR]

A novel sulfenylation reagent (sulfenamide) was applied to establish a simple and efficient process to convert C−H bond in imidazo[1,2‐a]pyridine to C−S bond. This process only requires sulfenamides as the sulfenylation reagent and I2 as an inexpensive and readily available catalyst, without using metal catalysts, oxidants, additives, or even light radiation. The proposed reaction features excellent reactivity, substrate compatibility, and regioselectivity. [ABSTRACT FROM AUTHOR]

Aim: Determining the mechanisms by which climate change and human activities affect patterns of ecological specialization in different genetic units of the same species is crucial for developing local or regionally‐based conservation solutions. This study uses species distribution models and genetic analysis to (1) identify the evidence of intraspecific differences in the population size and distribution of the three extant lineages (Sichuan/Gansu (SG), Qinling (QL) and Shennongjia (SNJ)) of Sichuan snub‐nosed monkeys and (2) determine why some lineages have lower population numbers, a smaller geographical distribution, and are more threatened with extinction. Location: China. Methods: We used n‐dimensional hypervolume modelling and genotype‐environment association (GEA) models to compare the climatic niches of three snub‐nosed monkey lineages, SDMs to reconstruct the historical, current and future distributions of each lineage and SMC++ to calculate their effective population sizes. Results: We found evidence of: (1) climatic niche differentiation among the SG, QL and SNJ lineages of Sichuan snub‐nosed monkeys; (2) geographical isolation combined with a decrease in population size during the LGM resulted in ecological specialization among these three lineages; and (3) a decline in climatic suitability and anthropogenically driven land conversion, combined with small population size and a narrow distributional range, indicates that the SNJ lineage is at a greater risk of extinction than the SG and QL lineages. Main conclusions: We demonstrate that during the LGM a reduction in habitat suitability driven by climate change, in concert with decreasing population size, resulted in the geographical isolation of the three Sichuan snub‐nosed monkey subpopulations, leading to lineage differences in ecological specialization. GEA models and hypervolume models demonstrated that the three lineages occupy different ecological niches. Based on lineage‐level models, the SNJ and QL lineages should be the immediate focus of conservation efforts due to their small effective population size and expected future reductions in available suitable habitats. The modelling approach used here is robust and can be applied effectively to examine the biogeography, recent evolutionary history and effective population size of other endangered animal taxa. [ABSTRACT FROM AUTHOR]

Because of their large surface areas, long‐range order, π‐π stacking interactions and hierarchically integrated building blocks, covalent organic frameworks (COFs) have attracted increasing attention. Recently, COFs have been regarded as promising heterogeneous photocatalysts, owing to their remarkable light‐harvesting and energy transition capabilities. The research progress of COFs in photocatalytic organic synthesis is summarized, such as preparation of imines through the oxidation of amines, selective oxidation of sulfides, oxidative hydroxylation of arylboronic acids, C−H bond activation, cyclization, asymmetric organic synthesis and so on. Finally, a perspective of the present challenges of photoactive COFs in organic transformations is given. [ABSTRACT FROM AUTHOR]

Designing materials with high triboelectric is an efficient way of improving output performance of triboelectric nanogenerators (TENGs). Herein, we synthesized a series of covalent organic frameworks (COFs) with similar skeletons but various functional groups ranging between electron‐donating and electron‐withdrawing. These COFs form an ideal platform for clarifying the contribution of each group to TENG performance because the pore wall is perturbed in a predesigned manner. Kelvin probe force microscopy and computational data suggest that surface potentials and electron affinities of COFs can be improved by introducing electron‐donating or withdrawing groups, with the highest values observed for fluorinated COF. The TENG with fluorinated COF delivered an output voltage and current of 420 V and 64 μA, respectively, which are comparable to other reported materials. This strategy can be used to efficiently screen suitable frameworks as TENG materials with excellent output performance. [ABSTRACT FROM AUTHOR]

Two new covalent organic frameworks (COFs) were synthesized from 4,4′,4′′,4′′′‐(pyrene‐1,3,6,8‐tetrayl)tetraaniline and 2,5‐dimethoxyterephthalaldehyde (Py‐DMTA‐COF) or 2′,5′‐dimethoxy‐[1,1′:4′,1′′‐terphenyl]‐4,4′′‐dicarbaldehyde (Py‐DMTPDA‐COF) under solvothermal conditions. These two COFs were further facilely developed as efficient photocatalytic platforms for the synthesis of thiophosphinates. Py‐DMTA‐COF exhibited better photocatalytic activity, broad substrate applicability, and excellent recycling capacity for the preparation of thiophosphinates from P(O)H compounds and thiols compared to Py‐DMTPDA‐COF. This methodology was further extended to the seamless gram‐scale production of target phosphorothioate derivatives. The results demonstrate that COFs can provide a robust platform for developing metal‐free, base‐free, highly efficient, and reusable heterogeneous photocatalysts for organic transformations. [ABSTRACT FROM AUTHOR]

Aim: The abundances and distributions of some species are more closely matched to variations in climate than others. Species traits that might influence how well the distribution and abundance of a species are matched to climatic variation include life history (e.g., body size and dispersal ability), ecology (e.g., habitat specialization and territoriality) and demography (e.g., population size). Here, we used a survey of bird abundances across the USA to assess the extent to which species abundances and distributions are predicted by climate (i.e., climate matching) and how species traits relate to interspecific variation in climate matching. Location: USA. Time period: 1983–2018. Major taxa studied: Birds. Methods: Species abundances were obtained from the North American Breeding Bird Survey. Climate matching was estimated as the predictive performance of species–climate models fitted using boosted regression trees and generalized additive models and modelled as a function of species traits. Results: Species traits explained 56% of the variation in climate matching among species. Intermediate‐sized species were more well matched to climate than smaller or larger species, as were species that lived primarily in forested compared with open habitats, species that were locally more abundant and species that were more territorial. Alternatively, species that were more specialized or had high variability in abundance among sites were less well matched to climate. We also found that species classified as "near threatened" were more well matched to climate, suggesting that these species might be more vulnerable to climate change. However, species classified as "vulnerable" were more decoupled from climate than those of "least concern", possibly owing to ecological drift associated with progressive population declines. Main conclusions: Our findings provide an ecological basis for understanding the extent to which species abundances and distributions match broad climatic gradients, which can provide the groundwork to improve our ability to predict distributions under global change. [ABSTRACT FROM AUTHOR]

Aim: Community assembly processes are difficult to observe in nature but can be inferred from species diversity patterns. However, taxonomic patterns may be consistent with multiple explanations, such as habitat filtering or biogeographical processes, which can also act differently across spatial scales. Here, we assessed multiple facets of diversity to determine the relative contributions of local versus regional processes and historical versus contemporary factors in establishing macroecological patterns. Location: From the Mediterranean peninsulas to northern Scandinavia. Time period: Species occurrence data gathered since c. 1980. Major organism group studied: Trichoptera (Insecta). Methods: Based on an extensive functional space and a phylogenetic tree including 197 and 509 species, respectively, and the composition of 180 communities, we assessed the distribution of taxonomic, functional and phylogenetic diversity within 18 ecoregions (local α‐ and β‐diversity) and among those ecoregions (regional γ‐ and β‐diversity). Results: Local estimates of taxonomic, functional and phylogenetic α‐ and β‐diversity were similar across Europe, which reveals that all streams have similar carrying capacity even though the local abiotic factors involved are likely different among ecoregions. In contrast, regional taxonomic and phylogenetic diversities decreased as latitude increased, whereas functional richness and functional dispersion displayed unimodal relationships. The position of species on the functional space was not conserved, while northern species pools were found to be phylogenetically clustered and southern ones overdispersed. The nestedness component mainly contributed to the taxonomic and phylogenetic β‐diversity among northern communities, whereas in southern latitudes the turnover was dominant. Main conclusions: Decoupled latitudinal patterns of taxonomic, phylogenetic and functional diversity reveal the importance of regional environmental filtering over local factors in limiting species range and shaping the regional species pool. The biogeographical signature is still present; the northern recolonizations following the Pleistocene glaciations originated exclusively from central regions, instead of Mediterranean refugia, as was previously accepted. [ABSTRACT FROM AUTHOR]

Covalent–organic frameworks (COFs) are rarely used as heterogeneous catalysts for cycloaddition reactions, especially in [3+2] reactions. In this study, 4,4′,4″,4‴‐(pyrene‐1,3,6,8‐tetrayl) tetra‐aniline, 2,5‐dihydroxyterephthalaldehyde, and 2,5‐dimethylterephthalaldehyde are used to construct COFs with high porosity, crystallinity, and chemical stability. The phenolic and methyl groups on the pore channel of the COFs are precisely tuned to effectively serve as heterogeneous catalysts for the formal [3+2] reaction between 5‐alkoxyoxazoles and azodicarboxylate or nitrosobenzene compounds. The resultant COFs that are assembled from adjustable building unit ratios exhibit excellent catalytic performance for the targeted [3+2] reaction. [ABSTRACT FROM AUTHOR]

Aim: A long‐standing question in ecology and biogeography is how the population of a species is distributed across space. The highest abundance has been hypothesized to be in the geographical centre or the niche centre, although mixed patterns from empirical studies have triggered a recent debate. Here, we propose a conceptual framework based on environmental suitability and dispersal to interpret the mixed evidence. Location: Global. Time period: Present. Major taxa studied: Virtual species. Methods: We conducted a series of simulations to demonstrate how the abundance pattern would be affected by environmental suitability and dispersal ability. We simulated different combinations of environmental suitabilities and dispersal abilities in landscapes with varied heterogeneities. We also investigated how frequently the location of the niche centre overlapped with the geographical centre. Results: We demonstrated that the highest abundance could occur in the geographical centre, in the niche centre or somewhere in between the two centres, depending on the environmental set‐up and dispersal ability. We found that geographical and niche centres rarely overlapped, suggesting that a counteracting effect between the two factors, rather than reinforcement, is the norm in determining abundance patterns. Therefore, we would expect the highest abundance in the real world to occur between the two centres, in the niche centre, or in the geographical centre, in descending frequency. Main conclusions: Our proposed framework can be used to interpret the mixed patterns from empirical studies when testing the abundant‐centre and abundant niche‐centre hypotheses. Understanding the role of dispersal allows us to make predictions of the location with the highest abundance, as well as its location relative to the geographical centre and the niche centre. The varied locations of highest abundance mirror the mixed evidence in the literature, suggesting that the abundant‐centre and abundant niche‐centre hypotheses are not mutually exclusive. This highlights the importance of considering the underlying mechanisms for a better understanding of biogeographical patterns. [ABSTRACT FROM AUTHOR]

Aim: While species distribution models (SDMs) are standard tools to predict species distributions, they can suffer from observation and sampling biases, particularly presence‐only SDMs, which often rely on species observations from non‐standardized sampling efforts. To address this issue, sampling background points with a target‐group strategy is commonly used, although more robust strategies and refinements could be implemented. Here, we exploited a dataset of plant species from the European Alps to propose and demonstrate efficient ways to correct for observer and sampling bias in presence‐only models. Innovation: Recent methods correct for observer bias by including covariates related to accessibility in model calibrations (classic bias covariate correction, Classic‐BCC). However, depending on how species are sampled, accessibility covariates may not sufficiently capture observer bias. Here, we introduced BCCs more directly related to sampling effort, as well as a novel corrective method based on stratified resampling of the observational dataset before model calibration (environmental bias correction, EBC). We compared, individually and jointly, the effect of EBC and different BCC strategies, when modelling the distributions of 1,900 plant species. We evaluated model performance with spatial block split‐sampling and independent test data, and assessed the accuracy of plant diversity predictions across the European Alps. Main conclusions: Implementing EBC with BCC showed best results for every evaluation method. Particularly, adding the observation density of a target group as a bias covariate (Target‐BCC) gave the most realistic modelled species distributions, with a clear positive correlation (r ≃.5) found between predicted and expert‐based species richness. Although EBC must be carefully implemented in a species‐specific manner, such limitations may be addressed via automated diagnostics included in a provided R function. Implementing EBC and bias covariate correction together may allow future studies to address efficiently observer bias in presence‐only models, and overcome the standard need of an independent test dataset for model evaluation. [ABSTRACT FROM AUTHOR]

Aim: Vegetation phenology that characters the periodic life cycles of plants is indicative of the interactions between the biosphere and the atmosphere. Robust modelling of vegetation phenology metrics that correspond to canopy development events is essential to our understanding of how plants and ecosystems respond to a changing climate. Given considerable uncertainties associated with vegetation phenology modelling using numerical models, we explore the deep learning approach to predicting the timing of global vegetation phenology metrics. Location: Global. Time period: 2001–2015. Major taxa studied: Deciduous vegetation (DV), stressed deciduous vegetation (SDV), evergreen vegetation (EV). Methods: We developed a one‐dimensional convolutional neural network regression (1D‐CNNR) model with 10 hierarchical structures to model global vegetation phenology using meteorological variables as inputs. The developed deep learning model was evaluated using satellite‐derived phenology metrics (i.e., green‐up, maturity, senescence, and dormancy) and compared with the terrestrial ecosystem model Biome‐BGC (BioGeochemical Cycles). Results: Our experimental results show that the 1D‐CNNR model well captures both the spatial pattern and inter‐annual variation of satellite‐derived multiyear vegetation phenology metrics on a global scale. The median root‐mean‐square errors (RMSEs) and standard deviations between phenology metrics derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data and predicted by the 1D‐CNNR model on a global scale from 2001 to 2015 are 4.1 ± 5.9, 4.2 ± 12.1, 3.0 ± 6.8, and 3.4 ± 4.3 days for green‐up, maturation, senescence, and dormancy, respectively, for the DV type; 13.3 ± 29.6, 8.4 ± 29.1, 8.1 ± 21.3, and 9.1 ± 21.6 days for green‐up, maturation, senescence, and dormancy, respectively, for the SDV type; and 13.9 ± 17.4, 17.7 ± 34.6, 18.8 ± 42.9, and 12.1 ± 17.7 days for green‐up, maturation, senescence, and dormancy, respectively, for the EV type. Main conclusions: This research demonstrates that the 1D‐CNNR model has the potential for large‐scale modelling of vegetation phenology. Results from the deep learning model suggest that there is room to improve numerical vegetation phenology models for use in land surface models. [ABSTRACT FROM AUTHOR]

Aim: The plant species sharing ancestors now disjunctly distributed in eastern Asia (EAS) and eastern North America (ENA) have long been a biogeographic puzzle. Species within the EAS–ENA disjunct genera are presumed to exhibit niche conservatism, the tendency of closely related species to be more ecologically similar, reflecting lineages' common evolutionary history. However, the hypothesis has not been well examined at the species level. Location: EAS and ENA. Time period: Current. Major taxa studied: Species within the EAS–ENA disjunct genera. Methods: We compiled data on climate, species occurrence, growth form, and phylogeny to examine niche conservatism. We first built a phylogenetic tree to select intercontinental congeneric pairwise species and obtained their divergence times. We then quantified the observed niche overlaps with Schoener's D, which has a 0–1 range, based on species occurrence and climate of species' native ranges. To obtain projected distributions, each species' niche was projected to the non‐native region using ensemble ecological niche models. Projected‐related niche overlaps were then calculated using projected distributions and the corresponding climatic conditions. Results: Average observed niche overlaps of congeneric pairwise species were relatively small:.124,.211 and.109 for all, herbaceous and woody species, respectively. Both observed and projected‐related niche overlaps had significant negative relationships with divergence times of intercontinental congeneric pairwise species, with niche overlap for herbaceous species being higher than that for woody plants when controlling for divergence times. Main conclusions: We conclude that the significant negative relationships between niche overlap and divergence times of congeneric pairwise species confirm niche conservatism among species of EAS–ENA disjunct plants and that the extent of niche conservatism is slightly different for herbaceous and woody plants. These findings suggest the potential role of allopatric speciation in EAS, and could help to understand the evolutionary history and the Asian‐bias diversity pattern of the EAS–ENA disjunct plants. [ABSTRACT FROM AUTHOR]

Spatial patterns of biodiversity are inextricably linked to their collection methods, yet no synthesis of bias patterns or their consequences exists. As such, views of organismal distribution and the ecosystems they make up may be incorrect, undermining countless ecological and evolutionary studies. Using 742 million records of 374 900 species, we explore the global patterns and impacts of biases related to taxonomy, accessibility, ecotype and data type across terrestrial and marine systems. Pervasive sampling and observation biases exist across animals, with only 6.74% of the globe sampled, and disproportionately poor tropical sampling. High elevations and deep seas are particularly unknown. Over 50% of records in most groups account for under 2% of species and citizen‐science only exacerbates biases. Additional data will be needed to overcome many of these biases, but we must increasingly value data publication to bridge this gap and better represent species' distributions from more distant and inaccessible areas, and provide the necessary basis for conservation and management. [ABSTRACT FROM AUTHOR]

Aim: The aim was to understand the representativeness and accuracy of expert range maps and to explore alternative methods for mapping species distributions accurately. Location: Global. Time period: Contemporary. Major taxa studied: Terrestrial vertebrates and Odonata. Methods: We analysed the biases in 50,768 animal International Union for Conservation of Nature, Global Assessment of Reptile Distributions and BirdLife species maps and assessed the links between these maps and existing political boundaries and various non‐ecological boundaries to assess their accuracy for certain types of analyses. We cross‐referenced each species map with data from the Global Biodiversity Information Facility to assess whether maps captured the whole range of a species and what percentage of occurrence points fell within the assessed range of the species. In addition, we used a number of different methods to map diversity patterns and compared these with high‐resolution models of distribution patterns. Results: On average, 20–30% of the non‐coastal range boundaries of species overlapped with administrative national boundaries. In total, 60% of areas with the highest spatial turnover in species (high densities of species range boundaries marking high levels of shift in the community of species present) occurred at political boundaries, which was especially common in Southeast Asia. Different biases existed for different taxa, with gridded analysis in reptiles, river basins in Odonata (except the Americas) and county boundaries for amphibians in the USA. On average, up to half (25–46%) of the recorded range points of species fell outside their mapped distributions. Filtered minimum convex polygons performed better than expert range maps in reproducing modelled diversity patterns. Main conclusions: Expert range maps showed high bias at administrative borders in all taxa, but this was highest at the transition from tropical to subtropical regions. The methods used were inconsistent across space, time and taxa, and the ranges mapped did not match species distribution data. Alternative approaches can reconstruct patterns of distribution better than expert maps, and data‐driven approaches are needed to provide reliable alternatives to gain a better understanding of species distributions. [ABSTRACT FROM AUTHOR]

Copyright of Methods in Ecology & Evolution is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Estimating fossil species' geographic range is a major goal for paleobiologists. In the deep time, this is most commonly performed by using polygon‐based methods such as the minimum convex polygon (MCP) or the Alpha‐Hull. Unfortunately, such methods provide a poor representation of the fossil species' actual range, because they are unable to take control of the severe stochastic and taphonomic biases.Here, we introduce MInOSSE (massively interpolated occurrences for species spatial estimation), a model‐based method that combines a machine learning algorithm and geostatistical approaches to reconstruct a target fossil species' geographic ranges by relying on the distribution of other coeval species and without using environmental predictors.We tested MInOSSE by using many simulated fossil species' distributions, comparing its performance with MCP and Alpha‐Hull outcomes and applying it to real case studies.In all simulations, MInOSSE outperformed the competing methods. Interestingly, the superior performance of MInOSSE becomes more apparent when the fossil record of the target species is scarce, that is, when appropriate range reconstruction is most problematic with polygon‐based methods.MInOSSE is a powerful tool for researchers interested in studying geographic range evolution, effects of range size on extinction risk, as well as biodiversity dynamics and macroecological patterns in the deep time. [ABSTRACT FROM AUTHOR]

Aim: Tropical species are thought to experience and be adapted to narrow ranges of abiotic conditions. This idea has been invoked to explain a broad array of biological phenomena, including the latitudinal diversity gradient and differential rates of speciation and extinction. However, debate continues regarding the broad‐scale applicability of this pattern and potential processes responsible. Here, we use a simulation approach to test two propositions: (a) strong geographical patterns in realized niche breadth variation can arise in the absence of variance in fundamental niche breadth size, and (b) realized niche breadths can show latitudinal patterns as a consequence of spatio‐temporal climate change, even when fundamental niche breadths are unrelated to latitude and dispersal abilities are held constant. Location: Global. Time period: Simulations were conducted using climate models from over the last 120 ka, with trait dynamics captured at 95 ka and in the Modern. Major taxa studied: We used virtual species with traits based loosely on plants. Methods: We simulated latitudinal trends of niche breadth and range size for virtual species using a cellular automaton algorithm that linked a gridded geographical domain with a three‐dimensional environmental landscape. Results: In all simulations, strong spatial patterns in realized niches were obtained in the absence of niche evolution, and realized niches showed geographical patterns deriving only from realistic, spatio‐temporal variation in climate. We noted contrasting patterns of niche breadth in different environmental dimensions, with temperature breadth increasing with latitude, but precipitation breadth decreasing with latitude. Overall, simulation outcomes mimicked the real‐world pattern of latitudinal range extent co‐varying with amount of land area. Main conclusions: Tropical species can have narrower niche breadths for maximum and minimum temperature ranges compared with temperate species solely as the result of the spatial arrangement of environments. We therefore suggest that the complex spatio‐temporal distribution of global abiotic environments has strong potential for structuring observed latitudinal gradients of niche breadths. [ABSTRACT FROM AUTHOR]

Ecological niche modeling (ENM) is used widely to study species' geographic distributions. ENM applications frequently involve transferring models calibrated with environmental data from one region to other regions or times that may include novel environmental conditions. When novel conditions are present, transferability implies extrapolation, whereas, in absence of such conditions, transferability is an interpolation step only. We evaluated transferability of models produced using 11 ENM algorithms from the perspective of interpolation and extrapolation in a virtual species framework. We defined fundamental niches and potential distributions of 16 virtual species distributed across Eurasia. To simulate real situations of incomplete understanding of species' distribution or existing fundamental niche (environmental conditions suitable for the species contained in the study area; N*F), we divided Eurasia into six regions and used 1–5 regions for model calibration and the rest for model evaluation. The models produced with the 11 ENM algorithms were evaluated in environmental space, to complement the traditional geographic evaluation of models. None of the algorithms accurately estimated the existing fundamental niche (N*F) given one region in calibration, and model evaluation scores decreased as the novelty of the environments in the evaluation regions increased. Thus, we recommend quantifying environmental similarity between calibration and transfer regions prior to model transfer, providing an avenue for assessing uncertainty of model transferability. Different algorithms had different sensitivity to completeness of knowledge of N*F, with implications for algorithm selection. If the goal is to reconstruct fundamental niches, users should choose algorithms with limited extrapolation when N*F is well known, or choose algorithms with increased extrapolation when N*F is poorly known. Our assessment can inform applications of ecological niche modeling transference to anticipate species invasions into novel areas, disease emergence in new regions, and forecasts of species distributions under future climate conditions. [ABSTRACT FROM AUTHOR]

Abstract: Many previous studies have attempted to assess ecological niche modeling performance using receiver operating characteristic (ROC) approaches, even though diverse problems with this metric have been pointed out in the literature. We explored different evaluation metrics based on independent testing data using the Darwin's Fox (Lycalopex fulvipes) as a detailed case in point. Six ecological niche models (ENMs; generalized linear models, boosted regression trees, Maxent, GARP, multivariable kernel density estimation, and NicheA) were explored and tested using six evaluation metrics (partial ROC, Akaike information criterion, omission rate, cumulative binomial probability), including two novel metrics to quantify model extrapolation versus interpolation (E‐space index I) and extent of extrapolation versus Jaccard similarity (E‐space index II). Different ENMs showed diverse and mixed performance, depending on the evaluation metric used. Because ENMs performed differently according to the evaluation metric employed, model selection should be based on the data available, assumptions necessary, and the particular research question. The typical ROC AUC evaluation approach should be discontinued when only presence data are available, and evaluations in environmental dimensions should be adopted as part of the toolkit of ENM researchers. Our results suggest that selecting Maxent ENM based solely on previous reports of its performance is a questionable practice. Instead, model comparisons, including diverse algorithms and parameterizations, should be the sine qua non for every study using ecological niche modeling. ENM evaluations should be developed using metrics that assess desired model characteristics instead of single measurement of fit between model and data. The metrics proposed herein that assess model performance in environmental space (i.e., E‐space indices I and II) may complement current methods for ENM evaluation. [ABSTRACT FROM AUTHOR]

Ecological niche modelling (ENM) is used widely to aid in conservation planning and management, often focusing on rare species characterized by the biased observations associated with restricted geographic ranges, habitat specialization, small population size and limited natural history information. Generating reliable ENMs for such species is a challenge, however, owing to issues that arise from spatial sampling bias, such as model inaccuracy and overfitting. Here, using virtual scenarios, we assess the utility of integrating occurrence data for closely related species with varying degrees of niche overlap into ENMs of focal species., We consider two approaches to merge related and focal species models: integrating occurrences of focal and related species directly as inputs with which to generate ENMs, vs. creating ENMs based on occurrences of focal and related species separately and merging results based on Bayesian inference approaches., Both single, integrated models and Bayesian inference approaches performed better than models based on focal species only when niche overlap between the focal and related species was large, across ENM algorithms examined. While assessing sensitivity and specificity separately, the performances of the two integration approaches over different ENM algorithms were complicated., The results of the study offer a novel way forward in managing the challenge of creating useful, predictive models even for the rarest species, taking advantage of the reasonably general property of niche conservatism over small-to-moderate amounts of evolutionary time. [ABSTRACT FROM AUTHOR]

Blonder et al. (, Global Ecology and Biogeography, 23, 595-609) introduced a new multivariate kernel density estimation (KDE) method to infer Hutchinsonian hypervolumes in the modelling of ecological niches. The authors argued that their KDE method matches or outperforms several methods for estimating hypervolume geometries and for conducting species distribution modelling. Further clarification, however, is appropriate with respect to the assumptions and limitations of KDE as a method for species distribution modelling. Using virtual species and controlled environmental scenarios, we show that KDE both under- and overestimates niche volumes depending on the dimensionality of the dataset and the number of occurrence records considered. We suggest that KDE may be a viable approach when dealing with large sample sizes, limited sampling bias and only a few environmental dimensions. [ABSTRACT FROM AUTHOR]

A simple and efficient protocol for the iron(III)-catalyzed C5 halogenation of 8-aminoquinoline with potassium halides via a photoredox process was developed, affording desired products in good to excellent yields. This reaction features its mild and green conditions (proceeding in water under air at room temperature). Electronic effect is not obvious in this reaction, and the desired products can be afforded in good to excellent yields regardless of the benzamides possessing electron-donating groups or electron-withdrawing groups; comparatively, substrates containing electron-donating groups result in slightly higher yields of the coupling products than those of electron-withdrawing groups. Moreover, a gram-scale bromination reaction was also successfully fulfilled, demonstrating its potential applicable value in organic synthesis. [ABSTRACT FROM AUTHOR]

Robust methods by which to generate virtual species are needed urgently in the emerging field of distributional ecology to evaluate performance of techniques for modeling ecological niches and species distributions and to generate new questions in biogeography. Virtual species provide the opportunity to test hypotheses and methods based on known and unbiased distributions. We present Niche Analyst (NicheA), a toolkit developed to generate virtual species following the Hutchinsonian approach of an n-multidimensional space occupied by the species. Ecological niche models are generated, analyzed, and visualized in an environmental space, and then projected to the geographic space in the form of continuous or binary species distribution models. NicheA is implemented in a stable and user-friendly Java platform. The software, online manual, and user support are freely available at < >. [ABSTRACT FROM AUTHOR]

Aim Determining which species are more prone to extinction is vital for conserving Earth's biodiversity and for providing insight into macroevolutionary processes. This paper utilizes the Pliocene to Recent fossil record of mollusks to identify determinants of species' extinction over the past three million years of Earth history. Location Western Atlantic. Methods We focus on 92 bivalve and gastropod species that lived during the mid-Pliocene Warm Period ( mPWP; ∼3.264-3.025 Ma) and have either since gone extinct or are still extant. We used ecological niche modeling ( ENM) to assess the vulnerability of these species to extinction as a function of both fundamental ( FN) and realized ( RN) niche breadth proxies, geographic range size, and amount of suitable area available to them during the Last Glacial Maximum ( LGM; ∼21 Ka). Results Geographic range size emerged as a key predictor of extinction for the studied mollusk species, with RN breadth and amount of suitable area available during the LGM as secondary predictors. By contrast, FN breadth was not a significant predictor of extinction risk. Main conclusions The failure to recover FN breadth as a predictor of extinction may suggest that extinction resistance is achieved when species are more successful in filling the geographic extent of their fundamental tolerances. That is, when it comes to species' survival, being a generalist or specialist sensu stricto may be secondary to the unique historical, dispersal, and biotic constraints that dictate a species' occupation of suitable environments, and consequently of geographic space, at a particular time. Identifying the factors that promote extinction is important because of the time-intensive nature of estimating extinction risk for individual species and populations, and because of the rising concerns about the future of marine ecosystems and biodiversity. [ABSTRACT FROM AUTHOR]

The field of ecological niche modelling or species distribution modelling has seen enormous activity and attention in recent years, in the light of exciting biological inferences that can be drawn from correlational models of species' environmental requirements (i.e. ecological niches) and inferences of potential geographic distributions. Among the many methods used in the field, one or two are in practice assumed to be 'best' and are used commonly, often without explicit testing., We explore herein implications of the 'no free lunch' theorem, which suggests that no single optimization approach will prove to be best under all circumstances: we developed diverse virtual species with known niche and dispersal properties to test a suite of niche modelling algorithms designed to estimate potential areas of distribution., The result was that (i) indeed, no single 'best' algorithm was found and (ii) different algorithms performing very different manners depending on the particularities of the virtual species., The conclusion is that niche or distribution modelling studies should begin by testing a suite of algorithms for predictive ability under the particular circumstances of the study and choose an algorithm for a particular challenge based on the results of those tests. Studies that do not take this step may use algorithms that are not optimal for that particular challenge. [ABSTRACT FROM AUTHOR]

The palladacycle-catalyzed of a variety of aldehydes with alcohols was developed. This reaction allows formation of esters in moderate to excellent yields not only for various aldehydes but also alcohols. In addition, the could proceed well under mild conditions with a low catalyst loading of 0.0625 mol%. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Many science disciplines are witnessing marked increases in the volume and variety of data collected, analyzed, and stored (Khoury and Ioannidis [8]). However, it is still unclear how this trend will affect the job market for early-career ecologists (who we define as scholars seeking PhD assistantships or postdoc positions in ecology). Offering an ecology curriculum that emphasizes the foundations of data science will therefore better guarantee that ecological science can adequately address future societal and academic needs. [Extracted from the article]

A convenient protocol is developed for the ortho C-H arylation of substrates having a quinolin-8-ylamino directing group with aryl bromides. [ABSTRACT FROM AUTHOR]

The article presents chemical equations related to the article "Copper(I)-Catalyzed Sulfonylation of 8-Aminoquinoline Amides with Sulfonyl Chlorides in Air" by Y. Wu and others, published in the "Organic Letters" in 2015.