Comparison of evoked vs. spontaneous tics in a patient with trigeminal neuralgia (tic doloureux)

A 53-year old woman with tic doloureaux, affecting her right maxillary division of the trigeminal nerve (V2), could elicit shooting pains by slightly tapping her teeth when off medication. The pains, which she normally rated as > 6/10 on a visual analog scale (VAS), were electric shock-like in nature. She had no other spontaneous or ongoing background pain affecting the region. Based on her ability to elicit these tics, functional magnetic resonance imaging (fMRI) was performed while she produced brief shocks every 2 minutes on cue (evoked pain) over a 20 min period. In addition, she had 1–2 spontaneous shocks manifested between these evoked pains over the course of functional image acquisition. Increased fMRI activation for both evoked and spontaneous tics was observed throughout cortical and subcortical structures commonly observed in experimental pain studies with healthy subjects; including the primary somatosensory cortex, insula, anterior cingulate, and thalamus. Spontaneous tics produced more decrease in signals in a number of regions including the posterior cingulate cortex and amygdala, suggesting that regions known to be involved in expectation/anticipation may have been activated for the evoked, but not spontaneous, tics. In this patient there were large increases in activation observed in the frontal regions, including the anterior cingulate cortex and the basal ganglia. Spontaneous tics showed increased activation in classic aversion circuitry that may contribute to increased levels of anxiety. We believe that this is the first report of functional imaging of brain changes in tic-doloureaux

An efficient protocol for the global sensitivity analysis of stochastic ecological models

Stochastic simulation models requiring many input parameters are widely used to inform the management of ecological systems. The interpretation of complex models is aided by global sensitivity analysis, using simulations for distinct parameter sets sampled from multidimensional space. Ecologists typically analyze such output using an “emulator”; that is, a statistical model used to approximate the relationship between parameter inputs and simulation outputs and to derive sensitivity measures. However, it is typical for ad hoc decisions to be made regarding: (1) trading off the number of parameter samples against the number of simulation iterations run per sample, (2) determining whether parameter sampling is sufficient, and (3) selecting an appropriate emulator. To evaluate these choices, we coupled different sensitivity-analysis designs and emulators for a stochastic, 20-parameter model that simulated the re-introduction of a threatened species subject to predation and disease, and then validated the emulators against new output generated from the simulation model. Our results lead to the following sensitivity analysis-protocol for stochastic ecological models. (1) Run a single simulation iteration per parameter sample generated, even if the focal response is a probabilistic outcome, while sampling extensively across the parameter space. In contrast to designs that invested in many model iterations (tens to thousands) per parameter sample, this approach allowed emulators to capture the input-output relationship of the simulation model more accurately and also to produce sensitivity measures that were robust to variation inherent in the parameter-sampling stage. (2) Confirm that parameter sampling is sufficient, by emulating subsamples of the sensitivity-analysis output. As the subsample size is increased, the cross-validatory performance of the emulator and sensitivity measures derived from it should exhibit asymptotic behavior. This approach can also be used to compare candidate emulators and select an appropriate interaction depth. (3) If required, conduct further simulations for additional parameter samples, and then report sensitivity measures and illustrate key response curves using the selected emulator. This protocol will generate robust sensitivity measures and facilitate the interpretation of complex ecological models, while minimizing simulation effort.Thomas A. A. Prowse, Corey J. A. Bradshaw, Steven Delean, Phillip Cassey, Robert C. Lacy, Konstans Wells, Matthew E. Aiello-Lammens, H. R. Akçakaya, and Barry W. Broo

changeRangeR: An R package for reproducible biodiversity change metrics from species distribution estimates

Conservation planning and decision-making rely on evaluations of biodiversity status and threats that are based upon species' distribution estimates. However, gaps exist regarding automated tools to delineate species' current ranges from distribution estimates and use those estimates to calculate both species- and community-level biodiversity metrics. Here, we introduce changeRangeR, an R package that facilitates workflows to reproducibly transform estimates of species' distributions into metrics relevant for conservation. For example, by combining predictions from species distribution models (SDMs) with other maps of environmental data (e.g., suitable forest cover), researchers can characterize the proportion of a species' range that is under protection, metrics used under the IUCN Criteria A and B guidelines (Area of Occupancy and Extent of Occurrence), and other more general metrics such as taxonomic and phylogenetic diversity and endemism. Further, changeRangeR facilitates temporal comparisons among biodiversity metrics to inform efforts toward complementarity and consideration of future scenarios in conservation decisions. changeRangeR also provides tools to determine the effects of modeling decisions through sensitivity tests. Transparent and repeatable workflows for calculating biodiversity change metrics from SDMs such as those provided by changeRangeR are essential to inform conservation decision-making efforts and represent key extensions for SDM methodology and associated metadata documentation.journal articl

wallace 2: a shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions

Released 4 years ago, the Wallace EcoMod application (R package wallace) provided an open-source and interactive platform for modeling species niches and distributions that served as a reproducible toolbox and educational resource. wallace harnesses R package tools documented in the literature and makes them available via a graphical user interface that runs analyses and returns code to document and reproduce them. Since its release, feedback from users and partners helped identify key areas for advancement, leading to the development of wallace 2. Following the vision of growth by community expansion, the core development team engaged with collaborators and undertook a major restructuring of the application to enable: simplified addition of custom modules to expand methodological options, analyses for multiple species in the same session, improved metadata features, new database connections, and saving/loading sessions. wallace 2 features nine new modules and added functionalities that facilitate data acquisition from climate-simulation, botanical and paleontological databases; custom data inputs; model metadata tracking; and citations for R packages used (to promote documentation and give credit to developers). Three of these modules compose a new component for environmental space analyses (e.g., niche overlap). This expansion was paired with outreach to the biogeography and biodiversity communities, including international presentations and workshops that take advantage of the software's extensive guidance text. Additionally, the advances extend accessibility with a cloud-computing implementation and include a suite of comprehensive unit tests. The features in wallace 2 greatly improve its expandability, breadth of analyses, and reproducibility options, including the use of emerging metadata standards. The new architecture serves as an example for other modular software, especially those developed using the rapidly proliferating R package shiny, by showcasing straightforward module ingestion and unit testing. Importantly, wallace 2 sets the stage for future expansions, including those enabling biodiversity estimation and threat assessments for conservation.journal articl

Impacts of 21st‐century climate change on montane habitat in the Madrean Sky Island Archipelago

Aim The Madrean Sky Island Archipelago is a North American biodiversity hotspot composed of similar to 60 isolated mountains that span the Cordilleran Gap between the Rocky Mountains and the Sierra Madre Occidental. Characterized by discrete patches of high-elevation montane habitat, these "sky islands" serve as stepping stones across a "sea" of desert scrub/grassland. Over this coming century, the region is expected to shift towards a warmer and drier climate. We used species distribution modelling to predict how the spatial distribution of montane habitat will be affected by climate change. Location Madrean Sky Island Archipelago, south-west United States and north-west Mexico (latitude, 29-34 degrees N; longitude, 107-112 degrees W). Methods To approximate the current distribution of montane habitat, we built species distribution models for five high-elevation species (Ceanothus fendleri, Pinus strobiformis, Quercus gambelii, Sciurus aberti, and Synuchus dubius). The resulting models were projected under multiple climate change scenarios-four greenhouse gas concentration trajectories (RCP 2.6, 4.5, 6.0, and 8.5) for each of three climate models (CCSM4, MPI-ESM-LR, and NorESM1-M)-to generate predicted distributions for the years 2050 and 2070. We performed chi-squared tests to detect any future changes to total montane habitat area, and Conover-Iman tests to evaluate isolation among the discrete montane habitat patches. Results While the climate models differ with respect to their predictions as to how severe the effects of future climate change will be, they all agree that by as early as year 2050, there will be significant montane habitat loss and increased montane habitat patch isolation across the Madrean Archipelago region under a worst-case climate change scenario (RCP 8.5). Main conclusions Our results suggest that under 21st-century climate change, the Madrean Sky Islands will become increasingly isolated due to montane habitat loss. This may affect their ability to serve as stepping stones and have negative implications for the region's biodiversity.University of Arizona Center for Insect ScienceOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Chapter 4. In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset

Aim: Ideally, datasets for species distribution modelling (SDM) contain evenly sampled records covering the entire distribution of the species, confirmed absences and auxiliary ecophysiological data allowing informed decisions on relevant predictors. Unfortunately, these criteria are rarely met for marine organisms for which distributions are too often only scantly characterized and absences generally not recorded. Here, we investigate predictor relevance as a function of modelling algorithms and settings for a global dataset of marine species.Location: Global marine.Methods: We selected well-studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio-ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross-validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant. Results: We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org.Main conclusions: While temperature is a relevant predictor of global marine species distributions, considerable variation in predictor relevance is linked to the SDM set-up. We promote the usage of a standardized benchmark dataset (MarineSPEED) for methodological SDM studies

ENM2020 : A FREE ONLINE COURSE AND SET OF RESOURCES ON MODELING SPECIES NICHES AND DISTRIBUTIONS

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades-including a maturation of relevant theory and key concepts-but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an "Overview" talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.Peer reviewe

Which Factors Determine Spatial Segregation in the South American Opossums (Didelphis aurita and D. albiventris)? An Ecological Niche Modelling and Geometric Morphometrics Approach

Didelphis albiventris and D. aurita are Neotropical marsupials that share a unique evolutionary history and both are largely distributed throughout South America, being primarily allopatric throughout their ranges. In the Araucaria moist forest of Southern Brazil these species are sympatric and they might potentially compete having similar ecology. For this reason, they are ideal biological models to address questions about ecological character displacement and how closely related species might share their geographic space. Little is known about how two morphologically similar species of marsupials may affect each other through competition, if by competitive exclusion and competitive release. We combined ecological niche modeling and geometric morphometrics to explore the possible effects of competition on their distributional ranges and skull morphology. Ecological niche modeling was used to predict their potential distribution and this method enabled us to identify a case of biotic exclusion where the habit generalist D. albiventris is excluded by the presence of the specialist D. aurita. The morphometric analyses show that a degree of shape discrimination occurs between the species, strengthened by allometric differences, which possibly allowed them to occupy marginally different feeding niches supplemented by behavioral shift in contact areas. Overlap in skull morphology is shown between sympatric and allopatric specimens and a significant, but weak, shift in shape occurs only in D. aurita in sympatric areas. This could be a residual evidence of a higher past competition between both species, when contact zones were possibly larger than today. Therefore, the specialist D. aurita acts a biotic barrier to D. albiventris when niche diversity is not available for coexistence. On the other hand, when there is niche diversification (e.g. habitat mosaic), both species are capable to coexist with a minimal competitive effect on the morphology of D. aurita

Climatic and topographic changes since the Miocene influenced the diversification and biogeography of the tent tortoise (Psammobates tentorius) species complex in Southern Africa

Background: Climatic and topographic changes function as key drivers in shaping genetic structure and cladogenic radiation in many organisms. Southern Africa has an exceptionally diverse tortoise fauna, harbouring one-third of the world’s tortoise genera. The distribution of Psammobates tentorius (Kuhl, 1820) covers two of the 25 biodiversity hotspots in the world, the Succulent Karoo and Cape Floristic Region. The highly diverged P. tentorius represents an excellent model species for exploring biogeographic and radiation patterns of reptiles in Southern Africa. Results: We investigated genetic structure and radiation patterns against temporal and spatial dimensions since the Miocene in the Psammobates tentorius species complex, using multiple types of DNA markers and niche modelling analyses. Cladogenesis in P. tentorius started in the late Miocene (11.63–5.33 Ma) when populations dispersed from north to south to form two geographically isolated groups. The northern group diverged into a clade north of the Orange River (OR), followed by the splitting of the group south of the OR into a western and an interior clade. The latter divergence corresponded to the intensifcation of the cold Benguela current, which caused western aridifcation and rainfall seasonality. In the south, tectonic uplift and subsequent exhumation, together with climatic fuctuations seemed responsible for radiations among the four southern clades since the late Miocene. We found that each clade occurred in a habitat shaped by diferent climatic parameters, and that the niches difered substantially among the clades of the northern group but were similar among clades of the southern group. Conclusion: Climatic shifts, and biome and geographic changes were possibly the three major driving forces shaping cladogenesis and genetic structure in Southern African tortoise species. Our results revealed that the cladogenesis of the P. tentorius species complex was probably shaped by environmental cooling, biome shifts and topographic uplift in Southern Africa since the late Miocene. The Last Glacial Maximum (LGM) may have impacted the distribution of P. tentorius substantially. We found the taxonomic diversify of the P. tentorius species complex to be highest in the Greater Cape Floristic Region. All seven clades discovered warrant conservation attention, particularly Ptt-B–Ptr, Ptt-A and Pv-

ENM2020: A Free Online Course and Set of Resources on Modeling Species' Niches and Distributions

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades-including a maturation of relevant theory and key concepts-but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an "Overview" talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology