Recognizing sources of uncertainty in disease vector ecological niche models: An example with the tick Rhipicephalus sanguineus sensu lato

Effect of an altitudinal gradient on the morphology, molecular identification and distribution of Rhipicephalus linnaei in Veracruz, Mexico

Studies of morphological and genetic variation in vector populations across environmental gradients can help researchers to estimate species' responses to climate change scenarios and the potential risk of disease-causing pathogen expansion, which impacts negatively on human health. In this study, we analysed the effect of altitudinal gradients on the phenotypic response of the hard tick of medical and veterinary importance, Rhipicephalus sanguineus sensu lato (s.l.). Specimens of R. sanguineus s.l. were collected from host animals in one of Mexico's regions with high climatic heterogeneity (Veracruz), and geometric morphometric theory was employed to assess the response of three morphological characters to the altitudinal gradient. Additionally, genetic similarity data were provided, and ecological niche models were used to project the climatic distribution in the region. Our results demonstrate that the shape and size of ticks respond to altitude. Molecular identification indicate that all analysed samples correspond to the tropical lineage recently named Rhipicephalus linnaei. According to ecological niche models, the mean annual temperature contributes significantly to the spatial distribution of this tick species, with areas of higher suitability in the mountainous region. These changes in morphological structure and the presence of ticks at higher altitudinal gradients suggest that R. linnaei has a high potential for adaptation. Due to the variability of ecosystems in the state of Veracruz, our results could be valuable in assessing the response of this tick in a changing environment, aiding in predicting future scenarios in the distribution and abundance of this species.

Predicting the current and future distribution of Monochamus carolinensis (Coleoptera: Cerambycidae) based on the maximum entropy model

BACKGROUND

Monochamus carolinensis is an important vector of pinewood nematodes in North America that is under quarantine in several countries worldwide. The distribution of M. carolinensis was previously thought to be limited to North America; however, we discovered it during trapping in China in 2022. Using this discovery and information regarding the area of origin, we applied a machine-learning algorithm based on the maximum entropy principle to predict the current and future (2050s, 2070s) potential distribution areas of M. carolinensis using bioclimatic variables.

RESULTS

The biological suitability of M. carolinensis was mainly driven by precipitation factors (BIO18, BIO15, BIO19), with 87.18% of the potential distribution areas located in South America, Asia, North America and Africa. Future potential distribution areas of M. carolinensis are predicted to expand to high latitudes, with an average increase of 10 245 874.88 km2 , and only 6.89% of the current suitable areas will become unsuitable. The potential distribution areas in 2070 are largest under the SSP585 scenario, with a 41.40% predicted increase (52 309 803.61 km2 ) above the current distribution, mainly reflecting an increase of the marginally and highly suitable areas.

CONCLUSION

The determination of dominant climatic factors and potential distribution areas will help provide an early warning for an M. carolinensis invasion, as well as provide a scientific basis for the spread and outbreak, facilitating development of effective governmental prevention and control measures. © 2023 Society of Chemical Industry.

A global examination of ecological niche modeling to predict emerging infectious diseases: a systematic review

Introduction

As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche modeling (ENM) is increasingly employed to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species' spatial distribution. Still, ENM applied to EIDs is relatively new with varying algorithms and data types. We conducted a systematic review (PROSPERO: CRD42021251968) with the research question: What is the state of the science and practice of estimating ecological niches via ENM to predict the emergence and spread of vector-borne and/or zoonotic diseases?

Methods

We searched five research databases and eight widely recognized One Health journals between 1995 and 2020. We screened 383 articles at the abstract level (included if study involved vector-borne or zoonotic disease and applied ENM) and 237 articles at the full-text level (included if study described ENM features and modeling processes). Our objectives were to: (1) describe the growth and distribution of studies across the types of infectious diseases, scientific fields, and geographic regions; (2) evaluate the likely effectiveness of the studies to represent ecological niches based on the biotic, abiotic, and mobility framework; (3) explain some potential pitfalls of ENM algorithms and techniques; and (4) provide specific recommendation for future studies on the analysis of ecological niches to predict EIDs.

Results

We show that 99% of studies included mobility factors, 90% modeled abiotic factors with more than half in tropical climate zones, 54% modeled biotic conditions and interactions. Of the 121 studies, 7% include only biotic and mobility factors, 45% include only abiotic and mobility factors, and 45% fully integrated the biotic, abiotic, and mobility data. Only 13% of studies included modifying social factors such as land use. A majority of studies (77%) used well-recognized ENM algorithms (MaxEnt and GARP) and model selection procedures. Most studies (90%) reported model validation procedures, but only 7% reported uncertainty analysis.

Discussion

Our findings bolster ENM to predict EIDs that can help inform the prevention of outbreaks and future epidemics.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier (CRD42021251968).

Predicting climate-driven distribution shifts in Hyalomma marginatum (Ixodidae)

Hyalomma marginatum is an important tick species which is the main vector of Crimean–Congo haemorrhagic fever and spotted fever. The species is predominantly distributed in parts of southern Europe, North Africa and West Asia. However, due to ongoing climate change and increasing reports of H. marginatum in central and northern Europe, the expansion of this range poses a potential future risk. In this study, an ecological niche modelling approach to model the current and future climatic suitability of H. marginatum was followed. Using high-resolution climatic variables from the Chelsa dataset and an updated list of locations for H. marginatum, ecological niche models were constructed under current environmental conditions using MaxEnt for both current conditions and future projections under the ssp370 and ssp585 scenarios. Models show that the climatically suitable region for H. marginatum matches the current distributional area in the Mediterranean basin and West Asia. When applied to future projections, the models suggest a considerable expansion of H. marginatum's range in the north in Europe as a result of rising temperatures. However, a decline in central Anatolia is also predicted, potentially due to the exacerbation of drought conditions in that region.

Tracing the future of epidemics: Coincident niche distribution of host animals and disease incidence revealed climate-correlated risk shifts of main zoonotic diseases in China

Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.

A Scoping Review of Species Distribution Modeling Methods for Tick Vectors

Background

Globally, tick-borne disease is a pervasive and worsening problem that impacts human and domestic animal health, livelihoods, and numerous economies. Species distribution models are useful tools to help address these issues, but many different modeling approaches and environmental data sources exist.

Objective

We conducted a scoping review that examined all available research employing species distribution models to predict occurrence and map tick species to understand the diversity of model strategies, environmental predictors, tick data sources, frequency of climate projects of tick ranges, and types of model validation methods.

Design

Following the PRISMA-ScR checklist, we searched scientific databases for eligible articles, their references, and explored related publications through a graphical tool (www.connectedpapers.com). Two independent reviewers performed article selection and characterization using a priori criteria.

Results

We describe data collected from 107 peer-reviewed articles that met our inclusion criteria. The literature reflects that tick species distributions have been modeled predominantly in North America and Europe and have mostly modeled the habitat suitability for Ixodes ricinus (n = 23; 21.5%). A wide range of bioclimatic databases and other environmental correlates were utilized among models, but the WorldClim database and its bioclimatic variables 1–19 appeared in 60 (56%) papers. The most frequently chosen modeling approach was MaxEnt, which also appeared in 60 (56%) of papers. Despite the importance of ensemble modeling to reduce bias, only 23 papers (21.5%) employed more than one algorithm, and just six (5.6%) used an ensemble approach that incorporated at least five different modeling methods for comparison. Area under the curve/receiver operating characteristic was the most frequently reported model validation method, utilized in nearly all (98.9%) included studies. Only 21% of papers used future climate scenarios to predict tick range expansion or contraction. Regardless of the representative concentration pathway, six of seven genera were expected to both expand and retract depending on location, while Ornithodoros was predicted to only expand beyond its current range.

Conclusion

Species distribution modeling techniques are useful and widely employed tools for predicting tick habitat suitability and range movement. However, the vast array of methods, data sources, and validation strategies within the SDM literature support the need for standardized protocols for species distribution and ecological niche modeling for tick vectors.

Potential geographic distribution of Ixodes cookei, the vector of Powassan virus

Ixodes cookei Packard, the groundhog tick or woodchuck tick, is the main known vector of Powassan virus (POWV) disease in North America and an ectoparasite that infests diverse small- and mid-size mammals for blood meals to complete its life stages. Since I. cookei spends much of its life cycle off the host and needs hosts for a blood meal in order to pass to the next life stage, it is susceptible to changes in environmental conditions. We used a maximum-entropy approach to ecological niche modeling that incorporates detailed model-selection routes to link occurrence data to climatic variables to assess the potential geographic distribution of I. cookei under current and likely future climate conditions. Our models identified suitable areas in the eastern United States, from Tennessee and North Carolina north to southern Canada, including Nova Scotia, New Brunswick, eastern Newfoundland and Labrador, southern Quebec, and Ontario; suitable areas were also in western states, including Washington and Oregon and restricted areas of northern Idaho, northwestern Montana, and adjacent British Columbia, in Canada. This study produces the first maps of the potential geographic distribution of I. cookei. Documented POWV cases overlapped with suitable areas in the northeastern states; however, the presence of this disease in areas classified by our models as not suitable by our models but with POWV cases (Minnesota and North Dakota) requires more study.

Climate change impacts on ticks and tick-borne infections

Evidence climate change is impacting ticks and tick-borne infections is generally lacking. This is primarily because, in most parts of the world, there are no long-term and replicated data on the distribution and abundance of tick populations, and the prevalence and incidence of tick-borne infections. Notable exceptions exist, as in Canada where the northeastern advance of Ixodes scapularis and Lyme borreliosis in the USA prompted the establishment of tick and associated disease surveillance. As a result, the past 30 years recorded the encroachment and spread of I. scapularis and Lyme borreliosis across much of Canada concomitant with a 2-3 °C increase in land surface temperature. A similar northerly advance of I. ricinus [and associated Lyme borreliosis and tick-borne encephalitis (TBE)] has been recorded in northern Europe together with expansion of this species’ range to higher altitudes in Central Europe and the Greater Alpine Region, again concomitant with rising temperatures. Changes in tick species composition are being recorded, with increases in more heat tolerant phenotypes (such as Rhipicephalus microplus in Africa), while exotic species, such as Haemaphysalis longicornis and Hyalomma marginatum, are becoming established in the USA and Southern Europe, respectively. In the next 50 years these trends are likely to continue, whereas, at the southern extremities of temperate species’ ranges, diseases such as Lyme borreliosis and TBE may become less prevalent. Where socioeconomic conditions link livestock with livelihoods, as in Pakistan and much of Africa, a One Health approach is needed to tackling ticks and tick-borne infections under the increasing challenges presented by climate change.

Likely Geographic Distributional Shifts among Medically Important Tick Species and Tick-Associated Diseases under Climate Change in North America: A Review

Ticks rank high among arthropod vectors in terms of numbers of infectious agents that they transmit to humans, including Lyme disease, Rocky Mountain spotted fever, Colorado tick fever, human monocytic ehrlichiosis, tularemia, and human granulocytic anaplasmosis. Increasing temperature is suspected to affect tick biting rates and pathogen developmental rates, thereby potentially increasing risk for disease incidence. Tick distributions respond to climate change, but how their geographic ranges will shift in future decades and how those shifts may translate into changes in disease incidence remain unclear. In this study, we have assembled correlative ecological niche models for eight tick species of medical or veterinary importance in North America (Ixodes scapularis, I. pacificus, I. cookei, Dermacentor variabilis, D. andersoni, Amblyomma americanum, A. maculatum, and Rhipicephalus sanguineus), assessing the distributional potential of each under both present and future climatic conditions. Our goal was to assess whether and how species' distributions will likely shift in coming decades in response to climate change. We interpret these patterns in terms of likely implications for tick-associated diseases in North America.

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.

Multidimensional Analysis of the Spatiotemporal Variations in Ecological, Production and Living Spaces of Inner Mongolia and an Identification of Driving Forces

There is increasing focus on the difficult challenge of realizing coordinated development of production, living and ecological spaces within the regional development process. An ecological–production–living space evaluation index system was established in this study based on the concept of ecological, production and living spaces (EPLSs), the relationship between land use function and land use type and the national standard of land use classification. The aim of this study was to reveal the driving forces and patterns of variation in EPLSs in Inner Mongolia from 1990 to 2015. The results indicated that Inner Mongolia is mainly dominated by ecological space, followed by production space. Production and living spaces are mainly distributed to the south of the Greater Hinggan–Yinshan–Helan mountain ranges. Spatial changes in EPLSs were accelerated with prominent regional differences, with declining ecological area and increasing living and production spaces. Regional urbanization and industrialization were identified as the driving forces for change in EPLS in Inner Mongolia. It is hoped that the findings of this study can provide rational guidance for management of land use and coordinated development of EPLSs within Inner Mongolia.