Commonly collected thermal performance data can inform species distributions in a data-limited invader

Predicting potential distributions of species in new areas is challenging. Physiological data can improve interpretation of predicted distributions and can be used in directed distribution models. Nonnative species provide useful case studies. Panther chameleons (Furcifer pardalis) are native to Madagascar and have established populations in Florida, USA, but standard correlative distribution modeling predicts no suitable habitat for F. pardalis there. We evaluated commonly collected thermal traits- thermal performance, tolerance, and preference-of F. pardalis and the acclimatization potential of these traits during exposure to naturally-occurring environmental conditions in North Central Florida. Though we observed temperature-dependent thermal performance, chameleons maintained similar thermal limits, performance, and preferences across seasons, despite long-term exposure to cool temperatures. Using the physiological data collected, we developed distribution models that varied in restriction: time-dependent exposure near and below critical thermal minima, predicted activity windows, and predicted performance thresholds. Our application of commonly collected physiological data improved interpretations on potential distributions of F. pardalis, compared with correlative distribution modeling approaches that predicted no suitable area in Florida. These straightforward approaches can be applied to other species with existing physiological data or after brief experiments on a limited number of individuals, as demonstrated here.

Co-occurrence probabilities between mosquito vectors of West Nile and Eastern equine encephalitis viruses using Markov Random Fields (MRFcov)

Mosquito vectors of eastern equine encephalitis virus (EEEV) and West Nile virus (WNV) in the USA reside within broad multi-species assemblages that vary in spatial and temporal composition, relative abundances and vector competence. These variations impact the risk of pathogen transmission and the operational management of these species by local public health vector control districts. However, most models of mosquito vector dynamics focus on single species and do not account for co-occurrence probabilities between mosquito species pairs across environmental gradients. In this investigation, we use for the first time conditional Markov Random Fields (CRF) to evaluate spatial co-occurrence patterns between host-seeking mosquito vectors of EEEV and WNV around sampling sites in Manatee County, Florida. Specifically, we aimed to: (i) quantify correlations between mosquito vector species and other mosquito species; (ii) quantify correlations between mosquito vectors and landscape and climate variables; and (iii) investigate whether the strength of correlations between species pairs are conditional on landscape or climate variables. We hypothesized that either mosquito species pairs co-occur in patterns driven by the landscape and/or climate variables, or these vector species pairs are unconditionally dependent on each other regardless of the environmental variables. Our results indicated that landscape and bioclimatic covariates did not substantially improve the overall model performance and that the log abundances of the majority of WNV and EEEV vector species were positively dependent on other vector and non-vector mosquito species, unconditionally. Only five individual mosquito vectors were weakly dependent on environmental variables with one exception, Culiseta melanura, the primary vector for EEEV, which showed a strong correlation with woody wetland, precipitation seasonality and average temperature of driest quarter. Our analyses showed that majority of the studied mosquito species' abundance and distribution are insignificantly better predicted by the biotic correlations than by environmental variables. Additionally, these mosquito vector species may be habitat generalists, as indicated by the unconditional correlation matrices between species pairs, which could have confounded our analysis, but also indicated that the approach could be operationalized to leverage species co-occurrences as indicators of vector abundances in unsampled areas, or under scenarios where environmental variables are not informative.

Predicting potential transmission risk of Everglades virus in Florida using mosquito blood meal identifications

The overlap between arbovirus host, arthropod vectors, and pathogen distributions in environmentally suitable habitats represents a nidus where risk for pathogen transmission may occur. Everglades virus (EVEV), subtype II Venezuelan equine encephalitis virus (VEEV), is endemic to southern Florida where it is transmitted by the endemic vector Culex cedecei between muroid rodent hosts. We developed an ecological niche model (ENM) to predict areas in Florida suitable for EVEV transmission based upon georeferenced vector-host interactions from PCR-based blood meal analysis from blood-engorged female Cx. cedecei females. Thirteen environmental variables were used for model calibration, including bioclimatic variables derived from Daymet 1 km daily temperature and precipitation values, and land use and land cover data representing percent land cover derived within a 2.5 km buffer from 2019 National Land Cover Database (NLCD) program. Maximum temperature of the warmest month, minimum temperature of the coldest month, and precipitation of the driest month contributed 31.6%, 28.5% and 19.9% to ENM performance. The land cover types contributing the greatest to the model performance were percent landcover of emergent herbaceous and woody wetlands which contributed 5.2% and 4.3% to model performance, respectively. Results of the model output showed high suitability for Cx. cedecei feeding on rodents throughout the southwestern portion of the state and pockets of high suitability along the northern east coast of Florida, while areas with low suitability included the Miami-Dade metropolitan area and most of northern Florida and the Panhandle. Comparing predicted distributions of Cx. cedecei feeding upon rodent hosts in the present study to historical human cases of EVEV disease, as well as antibodies in wildlife show substantial overlap with areas predicted moderate to highly suitable for these vector/host associations. As such, the findings of this study likely predict the most accurate distribution of the nidus of EVEV to date, indicating that this method allows for better inference of potential transmission areas than models which only consider the vector or vertebrate host species individually. A similar approach using host blood meals of other arboviruses can be used to predict potential areas of virus transmission for other vector-borne diseases.

Niche dynamics of Memecylon in Sri Lanka: Distribution patterns, climate change effects, and conservation priorities

Recent climate projections have shown that the distribution of organisms in island biotas is highly affected by climate change. Here, we present the result of the analysis of niche dynamics of a plant group, Memecylon, in Sri Lanka, an island, using species occurrences and climate data. We aim to determine which climate variables explain current distribution, model how climate change impacts the availability of suitable habitat for Memecylon, and determine conservation priority areas for Sri Lankan Memecylon. We used georeferenced occurrence data of Sri Lankan Memecylon to develop ecological niche models and assess both current and future potential distributions under six climate change scenarios in 2041-2060 and 2061-2080. We also overlaid land cover and protected area maps and performed a gap analysis to understand the impacts of land-cover changes on Memecylon distributions and propose new areas for conservation. Differences among suitable habitats of Memecylon were found to be related to patterns of endemism. Under varying future climate scenarios, endemic groups were predicted to experience habitat shifts, gains, or losses. The narrow endemic Memecylon restricted to the montane zone were predicted to be the most impacted by climate change. Projections also indicated that changes in species' habitats can be expected as early as 2041-2060. Gap analysis showed that while narrow endemic categories are considerably protected as demonstrated by their overlap with protected areas, more conservation efforts in Sri Lankan forests containing wide endemic and nonendemic Memecylon are needed. This research helped clarify general patterns of responses of Sri Lankan Memecylon to global climate change. Data from this study are useful for designing measures aimed at filling the gaps in forest conservation on this island.

Climate drivers of adult insect activity are conditioned by life history traits

Insect phenological lability is key for determining which species will adapt under environmental change. However, little is known about when adult insect activity terminates and overall activity duration. We used community-science and museum specimen data to investigate the effects of climate and urbanisation on timing of adult insect activity for 101 species varying in life history traits. We found detritivores and species with aquatic larval stages extend activity periods most rapidly in response to increasing regional temperature. Conversely, species with subterranean larval stages have relatively constant durations regardless of regional temperature. Species extended their period of adult activity similarly in warmer conditions regardless of voltinism classification. Longer adult durations may represent a general response to warming, but voltinism data in subtropical environments are likely underreported. This effort provides a framework to address the drivers of adult insect phenology at continental scales and a basis for predicting species response to environmental change.

Spatial phylogenetics of butterflies in relation to environmental drivers and angiosperm diversity across North America

Broad-scale, quantitative assessments of insect biodiversity and the factors shaping it remain particularly poorly explored. Here we undertook a spatial phylogenetic analysis of North American butterflies to test whether climate stability and temperature gradients have shaped their diversity and endemism. We also performed the first quantitative comparisons of spatial phylogenetic patterns between butterflies and flowering plants. We expected concordance between the two groups based on shared historical environmental drivers and presumed strong butterfly-host plant specializations. We instead found that biodiversity patterns in butterflies are strikingly different from flowering plants, especially warm deserts. In particular, butterflies show different patterns of phylogenetic clustering compared with flowering plants, suggesting differences in habitat conservation between the two groups. These results suggest that shared biogeographic histories and trophic associations do not necessarily assure similar diversity outcomes. The work has applied value in conservation planning, documenting warm deserts as a North American butterfly biodiversity hotspot.

Climate, urbanization, and species traits interactively drive flowering duration

A wave of green leaves and multi-colored flowers advances from low to high latitudes each spring. However, little is known about how flowering offset (i.e., ending of flowering) and duration of populations of the same species vary along environmental gradients. Understanding these patterns is critical for predicting the effects of future climate and land-use change on plants, pollinators, and herbivores. Here, we investigated potential climatic and landscape drivers of flowering onset, offset, and duration of 52 plant species with varying key traits. We generated phenology estimates using >270,000 community-science photographs and a novel presence-only phenometric estimation method. We found longer flowering durations in warmer areas, which is more obvious for summer-blooming species compared to spring-bloomers driven by their strongly differing offset dynamics. We also found that higher human population density and higher annual precipitation are associated with delayed flowering offset and extended flowering duration. Finally, offset of woody perennials was more sensitive than herbaceous species to both climate and urbanization drivers. Empirical forecast models suggested that flowering durations will be longer in 2030 and 2050 under representative concentration pathway (RCP) 8.5, especially for summer-blooming species. Our study provides critical insight into drivers of key flowering phenophases and confirms that Hopkins' Bioclimatic Law also applies to flowering durations for summer-blooming species and herbaceous spring-blooming species.

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.

Spatio-temporal effects of climate change on the geographical distribution and flowering phenology of hummingbird-pollinated plants

BACKGROUNDS AND AIMS

Tropical plant species are already suffering the effects of climate change and projections warn of even greater changes in the following decades. Of particular concern are alterations in flowering phenology, given that it is considered a fitness trait, part of plant species ecological niche, with potential cascade effects in plant-pollinator interactions. The aim of the study was to assess the potential impacts of climate change on the geographical distribution and flowering phenology of hummingbird-pollinated plants.

METHODS

We implemented ecological niche modelling (ENM) to investigate the potential impacts of different climate change scenarios on the geographical distribution and flowering phenology of 62 hummingbird-pollinated plant species in the Brazilian Atlantic Forest.

KEY RESULTS

Distribution models indicate future changes in the climatic suitability of their current habitats, suggesting a tendency towards discontinuity, reduction and spatial displacement. Flowering models indicate that climate can influence species phenology in different ways: some species may experience increased flowering suitability whereas others may suffer decreased suitability.

CONCLUSIONS

Our results suggest that hummingbird-pollinated species are prone to changes in their geographical distribution and flowering under different climate scenarios. Such variation may impact the community structure of ecological networks and reproductive success of tropical plants in the near future.

Research applications of primary biodiversity databases in the digital age

Our world is in the midst of unprecedented change-climate shifts and sustained, widespread habitat degradation have led to dramatic declines in biodiversity rivaling historical extinction events. At the same time, new approaches to publishing and integrating previously disconnected data resources promise to help provide the evidence needed for more efficient and effective conservation and management. Stakeholders have invested considerable resources to contribute to online databases of species occurrences. However, estimates suggest that only 10% of biocollections are available in digital form. The biocollections community must therefore continue to promote digitization efforts, which in part requires demonstrating compelling applications of the data. Our overarching goal is therefore to determine trends in use of mobilized species occurrence data since 2010, as online systems have grown and now provide over one billion records. To do this, we characterized 501 papers that use openly accessible biodiversity databases. Our standardized tagging protocol was based on key topics of interest, including: database(s) used, taxa addressed, general uses of data, other data types linked to species occurrence data, and data quality issues addressed. We found that the most common uses of online biodiversity databases have been to estimate species distribution and richness, to outline data compilation and publication, and to assist in developing species checklists or describing new species. Only 69% of papers in our dataset addressed one or more aspects of data quality, which is low considering common errors and biases known to exist in opportunistic datasets. Globally, we find that biodiversity databases are still in the initial stages of data compilation. Novel and integrative applications are restricted to certain taxonomic groups and regions with higher numbers of quality records. Continued data digitization, publication, enhancement, and quality control efforts are necessary to make biodiversity science more efficient and relevant in our fast-changing environment.

Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data.

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.

Reconstructing Ecological Niche Evolution When Niches Are Incompletely Characterized

Evolutionary dynamics of abiotic ecological niches across phylogenetic history can shed light on large-scale biogeographic patterns, macroevolutionary rate shifts, and the relative ability of lineages to respond to global change. An unresolved question is how best to represent and reconstruct evolution of these complex traits at coarse spatial scales through time. Studies have approached this question by integrating phylogenetic comparative methods with niche estimates inferred from correlative and other models. However, methods for estimating niches often produce incomplete characterizations, as they are inferred from present-day distributions that may be limited in full expression of the fundamental ecological niche by biotic interactions, dispersal limitations, and the existing set of environmental conditions. Here, we test whether incomplete niche characterizations inherent in most estimates of species' niches bias phylogenetic reconstructions of niche evolution, using simulations of virtual species with known niches. Results establish that incompletely characterized niches inflate estimates of evolutionary change and lead to error in ancestral state reconstructions. Our analyses also provide a potential mechanism to explain the frequent observation that maximum thermal tolerances are more conserved than minimum thermal tolerances: populations and species experience more spatial variation in minimum temperature than in maximum temperature across their distributions and, consequently, may experience stronger diversifying selection for cold tolerance.

Climatic niche and flowering and fruiting phenology of an epiphytic plant

Species have geographic distributions constrained by combinations of abiotic factors, biotic factors and dispersal-related factors. Abiotic requirements vary across the life stages for a species; for plant species, a particularly important life stage is when the plant flowers and develops seeds. A previous year-long experiment showed that ambient temperature of 5-35 °C, relative humidity of >50 % and ≤15 consecutive rainless days are crucial abiotic conditions for Spanish moss (Tillandsia usneoides L.). Here, we explore whether these optimal physiological intervals relate to the timing of the flowering and fruiting periods of Spanish moss across its range. As Spanish moss has a broad geographic range, we examined herbarium specimens to detect and characterize flowering/fruiting periods for the species across the Americas; we used high-temporal-resolution climatic data to assess the availability of optimal conditions for Spanish moss populations during each population's flowering period. We explored how long populations experience suboptimal conditions and found that most populations experience suboptimal conditions in at least one environmental dimension. Flowering and fruiting periods of Spanish moss populations are either being optimized for one or a few parameters or may be adjusted such that all parameters are suboptimal. Spanish moss populations appear to be constrained most closely by minimum temperature during this period.

Do ecological niche model predictions reflect the adaptive landscape of species?: a test using Myristica malabarica Lam., an endemic tree in the Western Ghats, India

Ecological niche models (ENM) have become a popular tool to define and predict the "ecological niche" of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects the adaptive landscape of the species. Thus in sites predicted to be highly suitable, species would have maximum fitness compared to in sites predicted to be poorly suitable. As yet there are very few attempts to address this assumption. Here we evaluate this assumption. We used Bioclim (DIVA GIS version 7.3) and Maxent (version 3.3.2) to predict the habitat suitability of Myristica malabarica Lam., an economically important tree occurring in the Western Ghats, India. We located populations of the trees naturally occurring in different habitat suitability regimes (from highly suitable to poorly suitable) and evaluated them for their regeneration ability and genetic diversity. We also evaluated them for two plant functional traits, fluctuating asymmetry--an index of genetic homeostasis, and specific leaf weight--an index of primary productivity, often assumed to be good surrogates of fitness. We show a significant positive correlation between the predicted habitat quality and plant functional traits, regeneration index and genetic diversity of populations. Populations at sites predicted to be highly suitable had a higher regeneration and gene diversity compared to populations in sites predicted to be poor or unsuitable. Further, individuals in the highly suitable sites exhibited significantly less fluctuating asymmetry and significantly higher specific leaf weight compared to individuals in the poorly suitable habitats. These results for the first time provide an explicit test of the ENM with respect to the plant functional traits, regeneration ability and genetic diversity of populations along a habitat suitability gradient. We discuss the implication of these results for designing viable species conservation and restoration programs.

PANNOTATOR: an automated tool for annotation of pan-genomes

Due to next-generation sequence technologies, sequencing of bacterial genomes is no longer one of the main bottlenecks in bacterial research and the number of new genomes deposited in public databases continues to increase at an accelerating rate. Among these new genomes, several belong to the same species and were generated for pan-genomic studies. A pan-genomic study allows investigation of strain phenotypic differences based on genotypic differences. Along with a need for good assembly quality, it is also fundamental to guarantee good functional genome annotation of the different strains. In order to ensure quality and standards for functional genome annotation among different strains, we developed and made available PANNOTATOR (http://bnet.egr.vcu.edu/iioab/agenote.php), a web-based automated pipeline for the annotation of closely related and well-suited genomes for pan-genome studies, aiming at reducing the manual work to generate reports and corrections of various genome strains. PANNOTATOR achieved 98 and 76% of correctness for gene name and function, respectively, as result of an annotation transfer, with a similarity cut-off of 70%, compared with a gold standard annotation for the same species. These results surpassed the RAST and BASys softwares by 41 and 21% and 66 and 17% for gene name and function annotation, respectively, when there were reliable genome annotations of closely related species. PANNOTATOR provides fast and reliable pan-genome annotation; thereby allowing us to maintain the research focus on the main genotype differences between strains.