Using ground-derived data to assess the environmental niche of the spinose ear tick, Otobius megnini

Entomologia Experimentalis et Applicata

Volumn 137, Issue 2, 2010, Pages 132-142

  Estrada Peña, Agustín ^a   Nava, Santiago ^b   Horak, Ivan G ^c   Guglielmone, Alberto A ^b  

^a UNIVERSIDAD DE ZARAGOZA   (Spain)

^b INSTITUTO NACIONAL DE TECNOLOGÍA AGROPECUARIA INTA   (Argentina)

^c UNIVERSITY OF PRETORIA   (South Africa)

Author keywords

Acari; Argasidae; Endophilous; Ground climate; Habitat suitability; Ixodida; Modelling

Indexed keywords

AIR TEMPERATURE; BIOGEOGRAPHY; ECOLOGICAL MODELING; ENVIRONMENTAL ASSESSMENT; GEOGRAPHICAL DISTRIBUTION; HABITAT SELECTION; HOMOLOGY; NDVI; NEOTROPIC ECOZONE; NICHE; TICK;

ACARI; ARGASIDAE; IXODIDA; OTOBIUS MEGNINI;

EID: 78649402518     PISSN: 00138703     EISSN: 15707458     Source Type: Journal    
DOI: 10.1111/j.1570-7458.2010.01050.x     Document Type: Article

References (36)

1. Araújo MB, Pearson RG, Thuiller W & Erhard M (2005) Validation of species-climate impact models under climate change. Global Change Biology 11: 1504-1513.
2. Batjes NH (2005) ISRIC-WISE global data set of derived soil properties on a 0.5 by 0.5 degree grid (Version 3.0). Report 2005/08, ISRIC - World Soil Information, Wageningen, The Netherlands (with data set).
3. Borcard D, Legendre P & Drapeau P (1992) Partialling out the spatial component of ecological variation. Ecology 73: 1045-1055.
4. Crombie MK, Gillo RR & Arvidson RE (1999) An application of remotely derived climatological fields for risk assessment of vector-borne disease: a spatial study of filariasis prevalence in the Nile delta, Egypt. Photogrametric Engineering and Remote Sensing 65: 1401-1409.
5. Cumming GS (2000) Using between-model comparisons to fine-tune linear models of species ranges. Journal of Biogeography 27: 441-445.
6. Cumming GS & Van Vuuren DP (2006) Will climate change affect ectoparasite species ranges? Global Ecology and Biogeography 15: 486-497.
7. Dreyer K, Fourie LJ & Kok DJ (1998) Tick diversity, abundance and seasonal dynamics in a resource-poor urban environment in the Free State Province. Onderstepoort Journal of Veterinary Research 65: 305-316.
8. Drummond RO (1967) Seasonal activity of ticks (Acarina: Metastigmata) on cattle in southwestern Texas. Annals of the Entomological Society of America 60: 439-447.
9. Eisen RJ, Eisen L & Lane RS (2006) Predicting density of Ixodes pacificus nymphs in dense woodlands in Mendocino County, California, based on geographic information systems and remote sensing versus field-derived data. American Journal of Tropical Medicine and Hygiene 74: 632-640.
10. Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S et al. (2006) Novel methods improve prediction of species' distributions from occurrence data. Ecography 29: 129-151.
11. Estrada-Peña A (1999) Geostatistics and remote sensing as predictive tools to estimate Ixodes ricinus (Acari: Ixodidae) habitat suitability in the Western Palearctic from AVHRR satellite imagery. Experimental and Applied Acarology 23: 337-349.
12. Estrada-Peña A & Venzal JM (2006) High-resolution predictive mapping for Boophilus annulatus and B. microplus (Acari: Ixodidae) in Mexico and Southern Texas. Veterinary Parasitology 142: 350-358.
13. Estrada-Peña A & Venzal JM (2007) Climate niches of tick species in the Mediterranean region: modeling of occurrence data, distributional constraints, and impact of climate change. Journal of Medical Entomology 44: 1130-1138.
14. Fielding AH & Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 38-49.
15. Guglielmone AA & Mangold AJ (1986) La distribución geográfica de Otobius megnini (Dugès, 1884) (Acarina: Ixodoidea: Argasidae) en la Argentina. Veterinaria Argentina 3: 582-587.
16. Guisan A, Graham CH, Elith J & Huettmann F (2007) Sensitivity of predictive species distribution models to change in grain size. Diversity and Distributions 13: 332-340.
17. Hijmans RJ, Cameron SE, Parra JL, Jones PG & Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
18. Hirzel AH, Hausser J, Chessel D & Perrin N (2002) Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology 83: 2027-2036.
19. Huettmann F & Diamond AW (2006) Large-scale effects on the spatial distribution of seabirds in the Northwest Atlantic. Landscape Ecology 21: 1089-1108.
20. Hugh-Jones M (1989) Applications of remote sensing to the identification of habitats of parasites and diseases vectors. Parasitology Today 5: 244-251.
21. Keirans JE & Pound JM (2003) An annotated bibliography of the spinose ear tick, Otobius megnini (Dugès, 1883) (Acari: Ixodida: Argasidae) 1883-2000. Systematic and Applied Acarology, Special Publication 13: 1-68.
22. Kitron U & Kazmierczak J (1997) Spatial analysis of the distribution of Lyme Disease in Wisconsin. American Journal of Epidemiology 145: 558-566.
23. Lobo JM, Jiménez-Valverde A & Real R (2007) AUC: a misleading measure of the performance of predictive models. Global Ecology and Biogeography 21: 853-863.
24. Lynen G, Zeman P, Bakuname C, Di Giulio G, Mtui P et al. (2007) Cattle ticks of the genera Rhipicephalus and Amblyomma of economic importance in Tanzania: distribution assessed with GIS based on an extensive field survey. Experimental and Applied Acarology 43: 303-319.
25. Mayberry C (2003) Spinose Ear Tick (Otobius megnini). Fact sheet of the Department of Agriculture of the Western Australia Government 1, 1, South Perth, Australia.
26. Nava S, Mangold A & Guglielmone AA (2009) Field and laboratory studies in a Neotropical population of the spinose ear tick, Otobius megnini. Medical and Veterinary Entomology 23: 1-5.
27. Ogden NH, Barker IK, Beauchamp G, Brazeau S, Charron DF et al. (2006) Investigation of ground level and remote-sensed data for habitat clasification and prediction of survival of Ixodes scapularis in habitats of Southeastern Canada. Journal of Medical Entomology 43: 403-414.
28. Pearson RG, Raxworthy CJ, Nakamura M & Peterson AT (2007) Predicting species' distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography 34: 102-117.
29. Peterson AT & Holt RD (2003) Niche differentiation in Mexican birds: using point occurrences to detect ecological innovation. Ecology Letters 6: 774-782.
30. Phillips SJ, Anderson RP & Schapire RE (2006) Maximum entropy modelling of species geographic distributions. Ecological Modelling 190: 231-259.
31. Purse BV, Caracappa S, Marino AMF, Tatem AJ, Rogers DJ et al. (2004) Modelling the distribution of outbreaks and Culicoides vectors in Sicily: towards predictive risk maps for Italy. Veterinaria Italiana 40: 303-310.
32. Segurado P, Araújo MB & Kunin WE (2006) Consequences of spatial autocorrelation for niche-based models. Journal of Applied Ecology 43: 433-444.
33. Shililu J, Ghebremeskel T, Mengistu S, Fekadu H, Zerom M et al. (2003) Distribution of anopheline mosquitoes in Eritrea. American Journal of Tropical Medicine and Hygiene 69: 295-302.
34. Storch D, Konvièka M, Beneß J, Martinková J & Gaston KJ (2003) Distribution patterns in butterflies and birds of the Czech Republic: separating effects of habitat and geographic position. Journal of Biogeography 30: 1195-1205.
35. Theiler G & Salisbury LE (1958) Zoological survey of the Union of South Africa Tick survey: Part XI. The distribution of Otobius megnini, the spinose ear tick. Onderstepoort Journal of Veterinary Research 27: 605-610.
36. Thuiller W, Richardson DM, Pysek P, Midgley GF, Hughes GO & Rouget M (2005) Niche-based modelling as a tool for predicting the global risk of alien plant invasions. Global Change Biology 11: 2234-2250.