000131618 001__ 131618
000131618 005__ 20241125101139.0
000131618 0247_ $$2doi$$a10.1186/s13071-023-05959-y
000131618 0248_ $$2sideral$$a136989
000131618 037__ $$aART-2023-136989
000131618 041__ $$aeng
000131618 100__ $$aNoll, Madeleine
000131618 245__ $$aPredicting the distribution of Ixodes ricinus and Dermacentor reticulatus in Europe: a comparison of climate niche modelling approaches
000131618 260__ $$c2023
000131618 5060_ $$aAccess copy available to the general public$$fUnrestricted
000131618 5203_ $$aBackground
The ticks Ixodes ricinus and Dermacentor reticulatus are two of the most important vectors in Europe. Climate niche modelling has been used in many studies to attempt to explain their distribution and to predict changes under a range of climate change scenarios. The aim of this study was to assess the ability of different climate niche modelling approaches to explain the known distribution of I. ricinus and D. reticulatus in Europe.
Methods
A series of climate niche models, using different combinations of input data, were constructed and assessed. Species occurrence records obtained from systematic literature searches and Global Biodiversity Information Facility data were thinned to different degrees to remove sampling spatial bias. Four sources of climate data were used: bioclimatic variables, WorldClim, TerraClimate and MODIS satellite-derived data. Eight different model training extents were examined and three modelling frameworks were used: maximum entropy, generalised additive models and random forest models. The results were validated through internal cross-validation, comparison with an external independent dataset and expert opinion.
Results
The performance metrics and predictive ability of the different modelling approaches varied significantly within and between each species. Different combinations were better able to define the distribution of each of the two species. However, no single approach was considered fully able to capture the known distribution of the species. When considering the mean of the performance metrics of internal and external validation, 24 models for I. ricinus and 11 models for D. reticulatus of the 96 constructed were considered adequate according to the following criteria: area under the receiver-operating characteristic curve > 0.7; true skill statistic > 0.4; Miller’s calibration slope 0.25 above or below 1; Boyce index > 0.9; omission rate < 0.15.
Conclusions
This comprehensive analysis suggests that there is no single ‘best practice’ climate modelling approach to account for the distribution of these tick species. This has important implications for attempts to predict climate-mediated impacts on future tick distribution. It is suggested here that climate variables alone are not sufficient; habitat type, host availability and anthropogenic impacts, not included in current modelling approaches, could contribute to determining tick presence or absence at the local or regional scale.
000131618 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000131618 590__ $$a3.0$$b2023
000131618 592__ $$a0.967$$b2023
000131618 591__ $$aTROPICAL MEDICINE$$b6 / 28 = 0.214$$c2023$$dQ1$$eT1
000131618 593__ $$aParasitology$$c2023$$dQ1
000131618 591__ $$aPARASITOLOGY$$b11 / 45 = 0.244$$c2023$$dQ1$$eT1
000131618 593__ $$aInfectious Diseases$$c2023$$dQ1
000131618 594__ $$a6.3$$b2023
000131618 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000131618 700__ $$aWall, Richard
000131618 700__ $$aMakepeace, Benjamin L.
000131618 700__ $$aNewbury, Hannah
000131618 700__ $$aAdaszek, Lukasz
000131618 700__ $$aBødker, René
000131618 700__ $$0(orcid)0000-0001-7483-046X$$aEstrada-Peña, Agustín$$uUniversidad de Zaragoza
000131618 700__ $$aGuillot, Jacques
000131618 700__ $$ada Fonseca, Isabel Pereira
000131618 700__ $$aProbst, Julia
000131618 700__ $$aOvergaauw, Paul
000131618 700__ $$aStrube, Christina
000131618 700__ $$aZakham, Fathiah
000131618 700__ $$aZanet, Stefania
000131618 700__ $$aRose Vineer, Hannah
000131618 7102_ $$11009$$2773$$aUniversidad de Zaragoza$$bDpto. Patología Animal$$cÁrea Sanidad Animal
000131618 773__ $$g16, 384 (2023), 1-16$$pParasit. vectors$$tParasites & vectors$$x1756-3305
000131618 8564_ $$s4802594$$uhttps://zaguan.unizar.es/record/131618/files/texto_completo.pdf$$yVersión publicada
000131618 8564_ $$s2321266$$uhttps://zaguan.unizar.es/record/131618/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000131618 909CO $$ooai:zaguan.unizar.es:131618$$particulos$$pdriver
000131618 951__ $$a2024-11-22-12:01:52
000131618 980__ $$aARTICLE