Phenology of five tick species in the central Great Plains.

The states of Kansas and Oklahoma, in the central Great Plains, lie at the western periphery of the geographic distributions of several tick species. As the focus of most research on ticks and tick-borne diseases has been on Lyme disease which commonly occurs in areas to the north and east, the ticks of this region have seen little research attention. Here, we report on the phenology and activity patterns shown by tick species observed at 10 sites across the two states and explore factors associated with abundance of all and life specific individuals of the dominant species. Ticks were collected in 2020-2022 using dragging, flagging and carbon-dioxide trapping techniques, designed to detect questing ticks. The dominant species was A. americanum (24098, 97%) followed by Dermacentor variabilis (370, 2%), D. albipictus (271, 1%), Ixodes scapularis (91, <1%) and A. maculatum (38, <1%). Amblyomma americanum, A. maculatum and D. variabilis were active in Spring and Summer, while D. albipictus and I. scapularis were active in Fall and Winter. Factors associated with numbers of individuals of A. americanum included day of year, habitat, and latitude. Similar associations were observed when abundance was examined by life-stage. Overall, the picture is one of broadly distributed tick species that shows seasonal limitations in the timing of their questing activity.

Rethinking ecological niches and geographic distributions in face of pervasive human influence in the Anthropocene.

Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses to B, A, and M via ecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision-making, but commonly in the context of 'natural' settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human-natural landscape is recognized as the new norm. Therefore, B, A, and M (BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human-influenced BAM (Hi-BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions.

Ecological niche conservatism spurs diversification in response to climate change.

Lengthy debate has surrounded the theoretical and empirical science of whether climatic niche evolution is related to increased or decreased rates of biological diversification. Because species can persist for thousands to millions of years, these questions cross broad scales of time and space. Thus, short-term experiments may not provide comprehensive understanding of the system, leading to the emergence of contrasting opinions: niche evolution may increase diversity by allowing species to explore and colonize new geographic areas across which they could speciate; or, niche conservatism might augment biodiversity by supporting isolation of populations that may then undergo allopatric speciation. Here, we use a simulation approach to test how biological diversification responds to different rates and modes of niche evolution. We find that niche conservatism promotes biological diversification, whereas labile niches-whether adapting to the conditions available or changing randomly-generally led to slower diversification rates. These novel results provide a framework for understanding how Earth-life interactions produced such a diverse biota.

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.

An evaluation of the ecological niche of Orf virus (Poxviridae): Challenges of distinguishing broad niches from no niches.

Contagious ecthyma is a skin disease, caused by Orf virus, creating great economic threats to livestock farming worldwide. Zoonotic potential of this disease has gained recent attention owing to the re-emergence of disease in several parts of the world. Increased public health concern emphasizes the need for a predictive understanding of the geographic distributional potential of Orf virus. Here, we mapped the current distribution using occurrence records, and estimated the ecological niche in both geographical and environmental spaces. Twenty modeling experiments, resulting from two- and three-partition models, were performed to choose the candidate models that best represent the geographic distributional potential of Orf virus. For all of our models, it was possible to reject the null hypothesis of predictive performance no better than random expectations. However, statistical significance must be accompanied by sufficiently good predictive performance if a model is to be useful. In our case, omission of known distribution of the virus was noticed in all Maxent models, indicating inferior quality of our models. This conclusion was further confirmed by the independent final evaluation, using occurrence records sourced from the Centre for Agriculture and Bioscience International. Minimum volume ellipsoid (MVE) models indicated the broad range of environmental conditions under which Orf virus infections are found. The excluded climatic conditions from MVEs could not be considered as unsuitable owing to the broad distribution of Orf virus. These results suggest two possibilities: that the niche models fail to identify niche limits that constrain the virus, or that the virus has no detectable niche, as it can be found throughout the geographic distributions of its hosts. This potential limitation of component-based pathogen-only ENMs is discussed in detail.

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.

Mapping the global distribution of invasive pest Drosophila suzukii and parasitoid Leptopilina japonica: implications for biological control.

Insect pest invasions cause significant damage to crop yields, and the resultant economic losses are truly alarming. Climate change and trade liberalization have opened new ways of pest invasions. Given the consumer preference towards organic agricultural products and environment-friendly nature of natural pest control strategies, biological control is considered to be one of the potential options for managing invasive insect pests. Drosophila suzukii (Drosophilidae) is an extremely damaging fruit pest, demanding development of effective and sustainable biological control strategies. In this study, we assessed the potential of the parasitoid Leptopilina japonica (Figitidae) as a biocontrol agent for D. suzukii using ecological niche modeling approaches. We developed global-scale models for both pest and parasitoid to identify four components necessary to derive a niche based, target oriented prioritization approach to plan biological control programs for D. suzukii: (i) potential distribution of pest D. suzukii, (ii) potential distribution of parasitoid L. japonica, (iii) the degree of overlap in potential distributions of pest and parasitoid, and (iv) biocontrol potential of this system for each country. Overlapping suitable areas of pest and parasitoid were identified at two different thresholds and at the most desirable threshold (E = 5%), potential for L. japonica mediated biocontrol management existed in 125 countries covering 1.87 × 107 km2, and at the maximum permitted threshold (E = 10%), land coverage was reduced to 1.44 × 107 km2 in 121 countries. Fly pest distributional information as a predictor variable was not found to be improving parasitoid model performance, and globally, only in half of the countries, >50% biocontrol coverage was estimated. We therefore suggest that niche specificities of both pest and parasitoid must be included in site-specific release planning of L. japonica for effective biocontrol management aimed at D. suzukii. This study can be extended to design cost-effective pre-assessment strategies for implementing any biological control management program.

Impact of public sentiments on the transmission of COVID-19 across a geographical gradient.

COVID-19 is a respiratory disease caused by a recently discovered, novel coronavirus, SARS-COV-2. The disease has led to over 81 million confirmed cases of COVID-19, with close to two million deaths. In the current social climate, the risk of COVID-19 infection is driven by individual and public perception of risk and sentiments. A number of factors influences public perception, including an individual's belief system, prior knowledge about a disease and information about a disease. In this article, we develop a model for COVID-19 using a system of ordinary differential equations following the natural history of the infection. The model uniquely incorporates social behavioral aspects such as quarantine and quarantine violation. The model is further driven by people's sentiments (positive and negative) which accounts for the influence of disinformation. People's sentiments were obtained by parsing through and analyzing COVID-19 related tweets from Twitter, a social media platform across six countries. Our results show that our model incorporating public sentiments is able to capture the trend in the trajectory of the epidemic curve of the reported cases. Furthermore, our results show that positive public sentiments reduce disease burden in the community. Our results also show that quarantine violation and early discharge of the infected population amplifies the disease burden on the community. Hence, it is important to account for public sentiment and individual social behavior in epidemic models developed to study diseases like COVID-19.

Mycobacterium leprae in Armadillo Tissues from Museum Collections, United States.

We examined armadillos from museum collections in the United States using molecular assays to detect leprosy-causing bacilli. We found Mycobacterium leprae bacilli in samples from the United States, Bolivia, and Paraguay; prevalence was 14.8% in nine-banded armadillos. US isolates belonged to subtype 3I-2, suggesting long-term circulation of this genotype.

Global ecological niche conservatism and evolution in Olea species.

Background and Aims: Climate is an important parameter in delimiting coarse-grained aspects of fundamental ecological niches of species; evolution of these niches has been considered a key component in biological diversification. We assessed phylogenetic niche conservatism and evolution in 24 species of the family Oleaceae in relation to temperature and precipitation variables. We studied niches of 17 Olea species and 7 species from other genera of Oleaceae globally. Methods: We used nuclear ribosomal and plastid DNA to reconstruct an evolutionary tree for the family. We used an approach designed specifically to incorporate uncertainty and incomplete knowledge of species' ecological niche limits. We performed parsimony- and likelihood-based reconstructions of ancestral states on two independent phylogenetic hypotheses for the family. After detailed analysis, species' niches were classified into warm and cold niches, wet and dry niches, and broad and narrow niches. Key Results: Given that full estimates of fundamental niches are difficult, we explore the alternative approach of explicit incorporation of knowledge of gaps in the information available, which allows avoidance of overestimation of amounts of evolutionary change. The result is a first synthetic view of evolutionary dynamics of ecological niches and distributional potential in a widespread plant family. Temperate regions of the Earth were occupied only by lineages that could derive with cold and dry niches; Southeast Asia held species with warm and wet niches; and parts of Africa held only species with dry niches. Conclusions: High temperature in Lutetian (Oligocene) and low temperature in Rupelian (Eocene) with major desertification events play important role for niche retraction and expansion in the history for Oleaceae clades. Associations between environmental niche characteristics and phylogeny reconstruction play an important role in understanding ecological niche conservatism, the overall picture was relatively slow or conservative niche evolution in this group.

Limited movement of an avian hybrid zone in relation to regional variation in magnitude of climate change.

Studies of natural hybrid zones can provide documentation of range shifts in response to climate change and identify loci important to reproductive isolation. Using a temporal (36-38 years) comparison of the black-capped (Poecile atricapillus) and Carolina (P. carolinensis) chickadee hybrid zone, we investigated movement of the western portion of the zone (western Missouri) and assessed whether loci and pathways underpinning reproductive isolation were similar to those in the eastern portion of the hybrid zone. Using 92 birds sampled along the hybrid zone transect in 2016 and 68 birds sampled between 1978 and 1980, we generated 11,669 SNPs via ddRADseq. These SNPs were used to assess movement of the hybrid zone through time and to evaluate variation in introgression among loci. We demonstrate that the interface has moved ~5 km to the northwest over the last 36-38 years, that is, at only one-fifth the rate at which the eastern portion (e.g., Pennsylvania, Ohio) of the hybrid zone has moved. Temperature trends over the last 38 years reveal that eastern areas have warmed 50% more than western areas in terms of annual mean temperature, possibly providing an explanation for the slower movement of the hybrid zone in Missouri. Our results suggest hybrid zone movement in broadly distributed species, such as chickadees, will vary between areas in response to local differences in the impacts of climate change.

Low risk of acquiring melioidosis from the environment in the continental United States.

Melioidosis is an underreported human disease of tropical and sub-tropical regions caused by the saprophyte Burkholderia pseudomallei. Although most global melioidosis cases are reported from tropical regions in Southeast Asia and northern Australia, there are multiple occurrences from sub-tropical regions, including the United States (U.S.). Most melioidosis cases reported from the continental U.S. are the result of acquiring the disease during travel to endemic regions or from contaminated imported materials. Only two human melioidosis cases from the continental U.S. have likely acquired B. pseudomallei directly from local environments and these cases lived only ~7 km from each other in rural Texas. In this study, we assessed the risk of acquiring melioidosis from the environment within the continental U.S. by surveying for B. pseudomallei in the environment in Texas where these two human melioidosis cases likely acquired their infections. We sampled the environment near the homes of the two cases and at additional sampling locations in surrounding counties in Texas that were selected based on ecological niche modeling. B. pseudomallei was not detected at the residences of these two cases or in the surrounding region. These negative data are important to demonstrate that B. pseudomallei is rare in the environment in the U.S. even at locations where locally acquired human cases likely have occurred, documenting the low risk of acquiring B. pseudomallei infection from the environment in the continental U.S.

Using Google Health Trends to investigate COVID-19 incidence in Africa.

The COVID-19 pandemic has caused over 500 million cases and over six million deaths globally. From these numbers, over 12 million cases and over 250 thousand deaths have occurred on the African continent as of May 2022. Prevention and surveillance remains the cornerstone of interventions to halt the further spread of COVID-19. Google Health Trends (GHT), a free Internet tool, may be valuable to help anticipate outbreaks, identify disease hotspots, or understand the patterns of disease surveillance. We collected COVID-19 case and death incidence for 54 African countries and obtained averages for four, five-month study periods in 2020-2021. Average case and death incidences were calculated during these four time periods to measure disease severity. We used GHT to characterize COVID-19 incidence across Africa, collecting numbers of searches from GHT related to COVID-19 using four terms: 'coronavirus', 'coronavirus symptoms', 'COVID19', and 'pandemic'. The terms were related to weekly COVID-19 case incidences for the entire study period via multiple linear and weighted linear regression analyses. We also assembled 72 variables assessing Internet accessibility, demographics, economics, health, and others, for each country, to summarize potential mechanisms linking GHT searches and COVID-19 incidence. COVID-19 burden in Africa increased steadily during the study period. Important increases for COVID-19 death incidence were observed for Seychelles and Tunisia. Our study demonstrated a weak correlation between GHT and COVID-19 incidence for most African countries. Several variables seemed useful in explaining the pattern of GHT statistics and their relationship to COVID-19 including: log of average weekly cases, log of cumulative total deaths, and log of fixed total number of broadband subscriptions in a country. Apparently, GHT may best be used for surveillance of diseases that are diagnosed more consistently. Overall, GHT-based surveillance showed little applicability in the studied countries. GHT for an ongoing epidemic might be useful in specific situations, such as when countries have significant levels of infection with low variability. Future studies might assess the algorithm in different epidemic contexts.

Combining Species Delimitation, Species Trees, and Tests for Gene Flow Clarifies Complex Speciation in Scrub-Jays.

Complex speciation, involving rapid divergence and multiple bouts of post-divergence gene flow, can obfuscate phylogenetic relationships and species limits. In North America, cases of complex speciation are common, due at least in part to the cyclical Pleistocene glacial history of the continent. Scrub-Jays in the genus Aphelocoma provide a useful case study in complex speciation because their range throughout North America is structured by phylogeographic barriers with multiple cases of secondary contact between divergent lineages. Here, we show that a comprehensive approach to genomic reconstruction of evolutionary history, i.e., synthesizing results from species delimitation, species tree reconstruction, demographic model testing, and tests for gene flow, is capable of clarifying evolutionary history despite complex speciation. We find concordant evidence across all statistical approaches for the distinctiveness of an endemic southern Mexico lineage (A. w. sumichrasti), culminating in support for the species status of this lineage under any commonly applied species concept. We also find novel genomic evidence for the species status of a Texas endemic lineage A. w. texana, for which equivocal species delimitation results were clarified by demographic modeling and spatially explicit models of gene flow. Finally, we find that complex signatures of both ancient and modern gene flow between the non-sister California Scrub-Jay (Aphelocoma californica) and Woodhouse's Scrub-Jay (Aphelocoma woodhouseii) result in discordant gene trees throughout the species' genomes despite clear support for their overall isolation and species status. In sum, we find that a multi-faceted approach to genomic analysis can increase our understanding of complex speciation histories, even in well-studied groups. Given the emerging recognition that complex speciation is relatively commonplace, the comprehensive framework that we demonstrate for interrogation of species limits and evolutionary history using genomic data can provide a necessary roadmap for disentangling the impacts of gene flow and incomplete lineage sorting (ILS) to better understand the systematics of other groups with similarly complex evolutionary histories. [Gene flow; genomics; introgression; phylogenomics; population genetics; species delimitation; species trees; systematics.].

Climate change influences on the geographic distributional potential of the spotted fever vectors Amblyomma maculatum and Dermacentor andersoni.

Amblyomma maculatum (Gulf Coast tick), and Dermacentor andersoni (Rocky Mountain wood tick) are two North American ticks that transmit spotted fevers associated Rickettsia. Amblyomma maculatum transmits Rickettsia parkeri and Francisella tularensis, while D. andersoni transmits R. rickettsii, Anaplasma marginale, Coltivirus (Colorado tick fever virus), and F. tularensis. Increases in temperature causes mild winters and more extreme dry periods during summers, which will affect tick populations in unknown ways. Here, we used ecological niche modeling (ENM) to assess the potential geographic distributions of these two medically important vector species in North America under current condition and then transfer those models to the future under different future climate scenarios with special interest in highlighting new potential expansion areas. Current model predictions for A. maculatum showed suitable areas across the southern and Midwest United States, and east coast, western and southern Mexico. For D. andersoni, our models showed broad suitable areas across northwestern United States. New potential for range expansions was anticipated for both tick species northward in response to climate change, extending across the Midwest and New England for A. maculatum, and still farther north into Canada for D. andersoni.

Spatio-temporal dynamics of rabies and habitat suitability of the common marmoset Callithrix jacchus in Brazil.

Rabies transmitted by wildlife is now the main source of human rabies in the Americas. The common marmoset, Callithrix jacchus, is considered a reservoir of rabies causing sporadic and unpredictable human deaths in Brazil, but the extent of the spillover risk to humans remains unknown. In this study, we described the spatiotemporal dynamics of rabies affecting C. jacchus reported to Brazil's Ministry of Health passive surveillance system between 2008 and 2020, and combined ecological niche modelling with C. jacchus occurrence data to predict its suitable habitat. Our results show that 67 outbreaks (91 cases) of rabies affecting C. jacchus were reported by 41 municipalities between January 2008 and October 2020, with a mean of 5 outbreaks/year [range: 1-14]. The maximum number of outbreaks and municipalities reporting cases occurred in 2018, coinciding with higher surveillance of primate deaths due to Yellow Fever. A mean of 3 [1-9] new municipalities reported outbreaks yearly, suggesting potential spatial expansions of the C. jacchus variant in northeastern Brazil and emerging rabies spillover from vampire bat Desmodus rotundus to C. jacchus in the north and south. Outbreaks were concentrated in the states of Ceará (72%) and Pernambuco (16%) up to 2012, but are now reported in Piauí since 2013, in Bahia since 2017 (D. rotundus' antigenic variant, AgV3) and in Rio de Janeiro since 2019 (AgV3). Besides confirming suitable habitat for this primate in the northeast and the east coast of Brazil, our Maximum Entropy model also predicted suitable habitat on the north and the west states of the country but predicted low habitat suitability among inland municipalities of the Caatinga biome reporting rabies. Our findings revealed new areas reporting rabies infecting C. jacchus, highlighting the need to implement strategies limiting spillover to humans and to better understand the drivers of C. jacchus rabies dynamics.

To isolate or not to isolate: the impact of changing behavior on COVID-19 transmission.

BACKGROUND: The COVID-19 pandemic has caused more than 25 million cases and 800 thousand deaths worldwide to date. In early days of the pandemic, neither vaccines nor therapeutic drugs were available for this novel coronavirus. All measures to prevent the spread of COVID-19 are thus based on reducing contact between infected and susceptible individuals. Most of these measures such as quarantine and self-isolation require voluntary compliance by the population. However, humans may act in their (perceived) self-interest only. METHODS: We construct a mathematical model of COVID-19 transmission with quarantine and hospitalization coupled with a dynamic game model of adaptive human behavior. Susceptible and infected individuals adopt various behavioral strategies based on perceived prevalence and burden of the disease and sensitivity to isolation measures, and they evolve their strategies using a social learning algorithm (imitation dynamics). RESULTS: This results in complex interplay between the epidemiological model, which affects success of different strategies, and the game-theoretic behavioral model, which in turn affects the spread of the disease. We found that the second wave of the pandemic, which has been observed in the US, can be attributed to rational behavior of susceptible individuals, and that multiple waves of the pandemic are possible if the rate of social learning of infected individuals is sufficiently high. CONCLUSIONS: To reduce the burden of the disease on the society, it is necessary to incentivize such altruistic behavior by infected individuals as voluntary self-isolation.

Application of Deep Learning to Community-Science-Based Mosquito Monitoring and Detection of Novel Species.

Mosquito-borne diseases account for human morbidity and mortality worldwide, caused by the parasites (e.g., malaria) or viruses (e.g., dengue, Zika) transmitted through bites of infected female mosquitoes. Globally, billions of people are at risk of infection, imposing significant economic and public health burdens. As such, efficient methods to monitor mosquito populations and prevent the spread of these diseases are at a premium. One proposed technique is to apply acoustic monitoring to the challenge of identifying wingbeats of individual mosquitoes. Although researchers have successfully used wingbeats to survey mosquito populations, implementation of these techniques in areas most affected by mosquito-borne diseases remains challenging. Here, methods utilizing easily accessible equipment and encouraging community-scientist participation are more likely to provide sufficient monitoring. We present a practical, community-science-based method of monitoring mosquito populations using smartphones. We applied deep-learning algorithms (TensorFlow Inception v3) to spectrogram images generated from smartphone recordings associated with six mosquito species to develop a multiclass mosquito identification system, and flag potential invasive vectors not present in our sound reference library. Though TensorFlow did not flag potential invasive species with high accuracy, it was able to identify species present in the reference library at an 85% correct identification rate, an identification rate markedly higher than similar studies employing expensive recording devices. Given that we used smartphone recordings with limited sample sizes, these results are promising. With further optimization, we propose this novel technique as a way to accurately and efficiently monitor mosquito populations in areas where doing so is most critical.

speciesLink: rich data and novel tools for digital assessments of biodiversity / speciesLink: dados valiosos e ferramentas inovadoras para avaliações digitais da biodiversidade

Abstract speciesLink is a large-scale biodiversity information portal that exists thanks to a broad collaborative network of people and institutions. CRIA's involvement with the scientific community of Brazil and other countries is responsible for the significant results achieved, currently reaching more than 15 million primary biodiversity data records, 95% of which are associated with preserved specimens and about 25% with high-quality digital images. The network provides data on over 200,000 species, of which over 110,000 occur in Brazil. This article describes thematic networks within speciesLink, as well as some of the most useful tools developed. The importance and contributions of speciesLink are outlined, as are concerns about securing stable budgetary support for such biodiversity data e-infrastructures. Here we review the value of speciesLink as a major source of biodiversity information for research, education, informed decision-making, policy development, and bioeconomy.

Resumo speciesLink é um portal de informações em larga escala sobre biodiversidade, que existe graças a uma ampla rede colaborativa de pessoas e instituições. O envolvimento do CRIA com a comunidade científica do Brasil e de outros países é responsável pelos resultados expressivos alcançados, atingindo atualmente mais de 15 milhões de registros de dados primários de biodiversidade, sendo 95% associados a espécimes preservados e cerca de 25% a imagens digitais de alta qualidade. A rede fornece dados sobre mais de 200.000 espécies, das quais mais de 110.000 ocorrem no Brasil. Este artigo descreve as redes temáticas do speciesLink, bem como algumas das ferramentas mais úteis desenvolvidas. A importância e as contribuições do speciesLink são destacadas, assim como as preocupações em garantir um apoio financeiro estável para e-infraestruturas de dados sobre biodiversidade. Aqui revisamos o valor do speciesLink como uma das principais fontes de informação sobre biodiversidade para pesquisa, educação, tomada de decisão, desenvolvimento de políticas e bioeconomia.