Relationships among cost, citation, and access in journal publishing by an ecology and evolutionary biology department at a U.S. university

Background

Optimizing access to high-quality scientific journals has become an important priority for academic departments, including the ability to read the scientific literature and the ability to afford to publish papers in those journals. In this contribution, we assess the question of whether institutional investment in scientific journals aligns with the journals where researchers send their papers for publication, and where they serve as unpaid reviewers and editors.

Methods

We assembled a unique suite of information about the publishing habits of our Department of Ecology and Evolutionary Biology, including summaries of 3,540 journal publications by 35 faculty members. These data include economic costs of journals to institutions and to authors, benefits to authors in terms of journal prestige and citation rates, and considerations of ease of reading access for individuals both inside and outside the university. This dataset included data on institutional costs, including subscription pricing (rarely visible to scholars), and "investment" by scholars in supporting journals, such as time spent as editors and reviewers.

Results

Our results highlighted the complex set of relationships between these factors, and showed that institutional costs often do not match well with payoffs in terms of benefits to researchers (e.g., citation rate, prestige of journal, ease of access). Overall, we advocate for greater cost-benefit transparency to help compare different journals and different journal business models; such transparency would help both researchers and their institutions in investing wisely the limited resources available to academics.

Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza

The choice of appropriate independent variables to create models characterizing ecological niches of species is of critical importance in distributional ecology. This set of dimensions in which a niche is defined can inform about what factors limit the distributional potential of a species. We used a multistep approach to select relevant variables for modeling the ecological niche of the aquatic Spirodela polyrhiza, taking into account variability arising from using distinct algorithms, calibration areas, and spatial resolutions of variables. We found that, even after an initial selection of meaningful variables, the final set of variables selected based on statistical inference varied considerably depending on the combination of algorithm, calibration area, and spatial resolution used. However, variables representing extreme temperatures and dry periods were more consistently selected than others, despite the treatment used, highlighting their importance in shaping the distribution of this species. Other variables related to seasonality of solar radiation, summer solar radiation, and some soil proxies of nutrients in water, were selected commonly but not as frequently as the ones mentioned above. We suggest that these later variables are also important to understanding the distributional potential of the species, but that their effects may be less pronounced at the scale at which they are represented for the needs of this type of modeling. Our results suggest that an informed definition of an initial set of variables, a series of statistical steps for filtering and exploring these predictors, and model selection exercises that consider multiple sets of predictors, can improve determination of variables that shape the niche and distribution of the species, despite differences derived from factors related to data or modeling algorithms.

On the relationship between environmental suitability and habitat use for three neotropical mammals

Recent studies have used occupancy models (OM) and ecological niche models (ENM) to provide a better understanding of species’ distributions at different scales. One of the main ideas underlying the theoretical foundations of both OM and ENM is that they are positively related to abundance: higher occupancy implies higher density and more suitable areas are likely to have more abundant populations. Here, we analyze the relationship between habitat use measured in terms of occupancy probabilities from OM and environmental suitability derived from ENM in three different Neotropical mammal species: Leopardus wiedii, Cuniculus paca, and Dasypus novemcinctus. For ENM, we used climatic and vegetation cover variables and implemented a model calibration and selection protocol to select the most competitive models. For OM, we used a single-species, single-season model with site covariates for camera-trap data from six different sites throughout the Neotropical realm. Covariates included vegetation percentage, normalized difference vegetation index, normalized difference water index, and elevation. For each site, we fit OM using all possible combinations of variables and selected the most competitive (ΔAICc < 2) to build an average OM. We explored relationships between estimated suitability and occupancy values using Spearman correlation analysis. Relationships between ENM and OM tended to be positive for the three Neotropical mammals, but the strength varied among sites, which could be explained by local factors such as site characteristics and conservation status of areas. We conjecture that ENM are suitable to understand spatial patterns at coarser geographic scales because the concept of the niche is about the species as a whole, whereas OM are more relevant to explain the distribution locally, likely reflecting transient dynamics of populations resulting from many local factors such as community composition and biotic processes.

Differences Between Attached and Detached Cadaveric Prosections on Students' Identification Ability During Practical Examinations

Cadaveric prosections are effective learning tools in anatomy education. They range from a fully dissected, sometimes plastinated, complete cadaver (in situ prosections), to a single, carefully dissected structure detached from a cadaver (ex situ prosections). While most research has focused on the advantages and disadvantages of dissection versus prosection, limited information is available on the instructional efficacy of different prosection types. This contribution explored potential differences between in situ and ex situ prosections regarding the ability of undergraduate students to identify anatomical structures. To determine if students were able to recognize the same anatomical structure on both in situ and ex situ prosections, or on either one individually, six structures were tagged on both prosection types as part of three course summative examinations. The majority of students (61%-68%) fell into one of the two categories: those that recognized or failed to recognize the same structure on both in situ and ex situ prosections. The percentage of students who recognized a selected structure on only one type of prosection was small (1.6%-31.6%), but skewed in favor of ex situ prosections (P ≤ 0.01). These results suggest that overall students' identification ability was due to knowledge differences, not the spatial or contextual challenges posed by each type of prosection. They also suggest that the relative difficulty of either prosection type depends on the nature of the anatomical structure. Thus, one type of prosection might be more appropriate for teaching some structures, and therefore the use of both types is recommended.

Climatic suitability of the eastern paralysis tick, Ixodes holocyclus, and its likely geographic distribution in the year 2050

The eastern paralysis tick, Ixodes holocyclus is one of two ticks that cause potentially fatal tick paralysis in Australia, and yet information on the full extent of its present or potential future spatial distribution is not known. Occurrence data for this tick species collected over the past two decades, and gridded environmental variables at 1 km² resolution representing climate conditions, were used to derive correlative ecological niche models to predict the current and future potential distribution. Several hundreds of candidate models were constructed with varying combinations of model parameters, and the best-fitting model was chosen based on statistical significance, omission rate, and Akaike Information Criterion (AICc). The best-fitting model matches the currently known distribution but also extends through most of the coastal areas in the south, and up to the Kimbolton peninsula in Western Australia in the north. Highly suitable areas are present around south of Perth, extending towards Albany, Western Australia. Most areas in Tasmania, where the species is not currently present, are also highly suitable. Future spatial distribution of this tick in the year 2050 indicates moderate increase in climatic suitability from the present-day prediction but noticeably also moderate to low loss of climatically suitable areas elsewhere.

Genome-environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes

The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome-wide gene regulatory networks shape genomic adaptation to key environmental conditions.

An ecological niche shift for Neanderthal populations in Western Europe 70,000 years ago

Middle Paleolithic Neanderthal populations occupied Eurasia for at least 250,000 years prior to the arrival of anatomically modern humans. While a considerable body of archaeological research has focused on Neanderthal material culture and subsistence strategies, little attention has been paid to the relationship between regionally specific cultural trajectories and their associated existing fundamental ecological niches, nor to how the latter varied across periods of climatic variability. We examine the Middle Paleolithic archaeological record of a naturally constrained region of Western Europe between 82,000 and 60,000 years ago using ecological niche modeling methods. Evaluations of ecological niche estimations, in both geographic and environmental dimensions, indicate that 70,000 years ago the range of suitable habitats exploited by these Neanderthal populations contracted and shifted. These ecological niche dynamics are the result of groups continuing to occupy habitual territories that were characterized by new environmental conditions during Marine Isotope Stage 4. The development of original cultural adaptations permitted this territorial stability.

Geographic potential of the world's largest hornet, Vespa mandarinia Smith (Hymenoptera: Vespidae), worldwide and particularly in North America

The Asian giant hornet (AGH, Vespa mandarinia) is the world's largest hornet, occurring naturally in the Indomalayan region, where it is a voracious predator of pollinating insects including honey bees. In September 2019, a nest of Asian giant hornets was detected outside of Vancouver, British Columbia; multiple individuals were detected in British Columbia and Washington state in 2020; and another nest was found and eradicated in Washington state in November 2020, indicating that the AGH may have successfully wintered in North America. Because hornets tend to spread rapidly and become pests, reliable estimates of the potential invasive range of V. mandarinia in North America are needed to assess likely human and economic impacts, and to guide future eradication attempts. Here, we assess climatic suitability for AGH in North America, and suggest that, without control, this species could establish populations across the Pacific Northwest and much of eastern North America. Predicted suitable areas for AGH in North America overlap broadly with areas where honey production is highest, as well as with species-rich areas for native bumble bees and stingless bees of the genus Melipona in Mexico, highlighting the economic and environmental necessity of controlling this nascent invasion.

Relationship Between Body Mass and Forewing Length in Neotropical Ichneumonidae (Insecta: Hymenoptera)

Biomass is an important indicator of various ecological factors in insect populations and communities. Although the utility of this variable is proven, it is usually dismissed in ecological studies, generally, because of the difficulty of measuring it. Considering that insect biomass is apparently declining worldwide, here, we aimed to test the accuracy of forewing length as an estimator of body mass in Neotropical Ichneumonidae to help in monitoring insect biomass. Forewing length and dry body mass were measured in 728 individuals from distinct localities in Venezuela and Ecuador. A clear log-linear relationship existed between the two variables, and a log-linear regression had significant and strong predictive power of mass based on wing length. To derive the final values of mass from predictions made using our equation, we used an exponential transformation. We present an R function for predicting mass from wing length. We consider our findings applicable to many Neotropical species of Ichneumonidae, and helpful especially when specimens are measured in dry collections.

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol.

General Theory and Good Practices in Ecological Niche Modeling: A Basic Guide

Ecological niche modeling (ENM) and species distribution modeling (SDM) are sets of tools that allow the estimation of distributional areas on the basis of establishing relationships among known occurrences and environmental variables. These tools have a wide range of applications, particularly in biogeography, macroecology, and conservation biology, granting prediction of species potential distributional patterns in the present and dynamics of these areas in different periods or scenarios. Due to their relevance and practical applications, the usage of these methodologies has significantly increased throughout the years. Here, we provide a manual with the basic routines used in this field and a practical example of its implementation to promote good practices and guidance for new users.

Curso modelado de nicho ecológico, version 1.0

El conjunto de ideas, métodos y programas informáticos que se conoce como “Modelado de Nicho Ecológico” (MNE)—y el relacionado “Modelado de Distribución de Especies” (MDS)—han sido objeto de intensa exploración e investigación en las últimas décadas. A pesar de existir al menos cuatro síntesis publicadas, este campo ha crecido tanto en complejidad, que la formación de nuevos investigadores es difícil. Hasta ahora, dicha formación se ha hecho de manera presencial en cursos organizados por universidades o centros de investigación, de los que hemos formado parte como instructores. Sin embargo, el acceso a este tipo de cursos especializados es restringido, por un lado, porque los cursos no se ofrecen en todas las universidades, y por otro, porque normalmente se imparten en inglés. Para facilitar el acceso a una mayor comunidad de científicos de habla hispana, presentamos un curso en español, completamente digital y de acceso gratuito, que se realizó vía Internet durante 23 semanas consecutivas en 2018. Aunque las barreras intrínsecas al uso de Internet pueden dificultar la accesibilidad a los materiales del curso, hemos usado diversos formatos para la divulgación de los contenidos académicos (video, audio, pdf) con el objetivo de eliminar la mayor parte de estos problemas.

kuenm: an R package for detailed development of ecological niche models using Maxent

Background

Ecological niche modeling is a set of analytical tools with applications in diverse disciplines, yet creating these models rigorously is now a challenging task. The calibration phase of these models is critical, but despite recent attempts at providing tools for performing this step, adequate detail is still missing. Here, we present the kuenm R package, a new set of tools for performing detailed development of ecological niche models using the platform Maxent in a reproducible way.

Results

This package takes advantage of the versatility of R and Maxent to enable detailed model calibration and selection, final model creation and evaluation, and extrapolation risk analysis. Best parameters for modeling are selected considering (1) statistical significance, (2) predictive power, and (3) model complexity. For final models, we enable multiple parameter sets and model transfers, making processing simpler. Users can also evaluate extrapolation risk in model transfers via mobility-oriented parity (MOP) metric.

Discussion

Use of this package allows robust processes of model calibration, facilitating creation of final models based on model significance, performance, and simplicity. Model transfers to multiple scenarios, also facilitated in this package, significantly reduce time invested in performing these tasks. Finally, efficient assessments of strict-extrapolation risks in model transfers via the MOP and MESS metrics help to prevent overinterpretation in model outcomes.

Potential Spatial Distribution of the Newly Introduced Long-horned Tick, Haemaphysalis longicornis in North America

The North American distributional potential of the recently invaded tick, Haemaphysalis longicornis, was estimated using occurrence data from its geographic range in other parts of the world and relevant climatic data sets. Several hundred candidate models were built using a correlative maximum entropy approach, and best-fitting models were selected based on statistical significance, predictive ability, and complexity. The median of the best-fitting models indicates a broad potential distribution for this species, but restricted to three sectors—the southeastern United States, the Pacific Northwest, and central and southern Mexico.

Current and Future Distribution of the Lone Star Tick, Amblyomma americanum (L.) (Acari: Ixodidae) in North America

Acarological surveys in areas outside the currently believed leading edge of the distribution of lone star ticks (Amblyomma americanum), coupled with recent reports of their identification in previously uninvaded areas in the public health literature, suggest that this species is more broadly distributed in North America than currently understood. Therefore, we evaluated the potential geographic extent under present and future conditions using ecological niche modeling approach based on museum records available for this species at the Walter Reed Biosystematics Unit (WRBU). The median prediction of a best fitting model indicated that lone star ticks are currently likely to be present in broader regions across the Eastern Seaboard as well as in the Upper Midwest, where this species could be expanding its range. Further northward and westward expansion of these ticks can be expected as a result of ongoing climate change, under both low- and high-emissions scenarios.

Sample data and training modules for cleaning biodiversity information

Large-scale biodiversity databases have become crucial information sources in many analyses in biogeography, macroecology, and conservation biology, often involving development of empirical models of species’ ecological niches and predictions of their geographic distributions. These analyses, however, can be impaired by the presence of errors, particularly as regards taxonomic identifications and accurate geographic coordinates. Here, we present a detailed data-cleaning exercise based on two contrasting datasets; we link these example data with a step-by-step guide to overcoming these problems and improving data quality for analyses based on these data.

Major challenges for correlational ecological niche model projections to future climate conditions

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions.