Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change

<p>Abstract</p> <p>Background</p> <p>Lyme disease is the commonest vector-borne zoonosis in the temperate world, and an emerging infectious disease in Canada due to expansion of the geographic range of the tick vector <it>Ixodes scapularis</it>. Studies suggest that climate change will accelerate Lyme disease emergence by enhancing climatic suitability for <it>I. scapularis</it>. Risk maps will help to meet the public health challenge of Lyme disease by allowing targeting of surveillance and intervention activities.</p> <p>Results</p> <p>A risk map for possible Lyme endemicity was created using a simple risk algorithm for occurrence of <it>I. scapularis </it>populations. The algorithm was calculated for each census sub-division in central and eastern Canada from interpolated output of a temperature-driven simulation model of <it>I. scapularis </it>populations and an index of tick immigration. The latter was calculated from estimates of tick dispersion distances by migratory birds and recent knowledge of the current geographic range of endemic <it>I. scapularis </it>populations. The index of tick immigration closely predicted passive surveillance data on <it>I. scapularis </it>occurrence, and the risk algorithm was a significant predictor of the occurrence of <it>I. scapularis </it>populations in a prospective field study. Risk maps for <it>I. scapularis </it>occurrence in Canada under future projected climate (in the 2020s, 2050s and 2080s) were produced using temperature output from the Canadian Coupled Global Climate Model 2 with greenhouse gas emission scenario enforcing '<it>A2</it>' of the Intergovernmental Panel on Climate Change.</p> <p>Conclusion</p> <p>We have prepared risk maps for the occurrence of <it>I. scapularis </it>in eastern and central Canada under current and future projected climate. Validation of the risk maps provides some confidence that they provide a useful first step in predicting the occurrence of <it>I. scapularis </it>populations, and directing public health objectives in minimizing risk from Lyme disease. Further field studies are needed, however, to continue validation and refinement of the risk maps.</p

Tracking the migration of a nocturnal aerial insectivore in the Americas

Abstract Background Populations of Eastern Whip-poor-will (Antrostomus vociferous) appear to be declining range-wide. While this could be associated with habitat loss, declines in populations of many other species of migratory aerial insectivores suggest that changes in insect availability and/or an increase in the costs of migration could also be important factors. Due to their quiet, nocturnal habits during the non-breeding season, little is known about whip-poor-will migration and wintering locations, or the extent to which different breeding populations share risks related to non-breeding conditions. Results We tracked 20 males and 2 females breeding in four regions of Canada using geolocators. Wintering locations ranged from the gulf coast of central Mexico to Costa Rica. Individuals from the northern-most breeding site and females tended to winter furthest south, although east-west connectivity was low. Four individuals appeared to cross the Gulf of Mexico either in spring or autumn. On southward migration, most individuals interrupted migration for periods of up to 15 days north of the Gulf, regardless of their subsequent route. Fewer individuals showed signs of a stopover in spring. Conclusions Use of the southeastern United States for migratory stopover and a concentration of wintering locations in Guatemala and neighbouring Mexican provinces suggest that both of these regions should be considered potentially important for Canadian whip-poor-wills. This species shows some evidence of both “leapfrog” and sex-differential migration, suggesting that individuals in more northern parts of their breeding range could have higher migratory costs

Additional file 2: Table S1. of Tracking the migration of a nocturnal aerial insectivore in the Americas

Non-breeding location estimates for 22 eastern whip-poor-wills breeding in Ontario, Canada. M and F in the bird ID indicates males and females. (PDF 45 kb

The relationship between the risk algorithm on which the risk maps were based, and the index of certainty that a site contained a reproducing population

<p><b>Copyright information:</b></p><p>Taken from "Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change"</p><p>http://www.ij-healthgeographics.com/content/7/1/24</p><p>International Journal of Health Geographics 2008;7():24-24.</p><p>Published online 22 May 2008</p><p>PMCID:PMC2412857.</p><p></p

Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change-0

Ected populations in Canada using Algorithm 6 (graph a: risk index = number of ticks at model equilibrium × number of tick populations within 425 km) and Algorithm 12 (graph b: risk index = number of ticks at model equilibrium × number of tick populations within 425 km × percentage forest cover).<p><b>Copyright information:</b></p><p>Taken from "Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change"</p><p>http://www.ij-healthgeographics.com/content/7/1/24</p><p>International Journal of Health Geographics 2008;7():24-24.</p><p>Published online 22 May 2008</p><p>PMCID:PMC2412857.</p><p></p

Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change-4

Ected populations in Canada using Algorithm 6 (graph a: risk index = number of ticks at model equilibrium × number of tick populations within 425 km) and Algorithm 12 (graph b: risk index = number of ticks at model equilibrium × number of tick populations within 425 km × percentage forest cover).<p><b>Copyright information:</b></p><p>Taken from "Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change"</p><p>http://www.ij-healthgeographics.com/content/7/1/24</p><p>International Journal of Health Geographics 2008;7():24-24.</p><p>Published online 22 May 2008</p><p>PMCID:PMC2412857.</p><p></p

Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change-2

Field study sites were visited. The 'index of certainty' for the presence of an population was calculated from the abundance of ticks and the numbers of instars discovered during the field visit. The value 0 indicated that no ticks were found. The 'high' risk regions for population establishment are indicated in red, the 'moderate' risk regions are in orange, the 'low' risk regions are in yellow, and regions with no risk of established populations but some risk from bird-borne 'adventitious' ticks are in green<p><b>Copyright information:</b></p><p>Taken from "Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change"</p><p>http://www.ij-healthgeographics.com/content/7/1/24</p><p>International Journal of Health Geographics 2008;7():24-24.</p><p>Published online 22 May 2008</p><p>PMCID:PMC2412857.</p><p></p

Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change-1

The 2080s (using the temperature conditions predicted by the CGCM2 climate model under emissions scenario ). In Figs a to d, the 'slow' scenario, the model assumes that by the end of each time period, only risk CSDs with an algorithm value in the top 10% will contain an population. In Figs e to h, the 'fast' scenario, the model assumes that by the end of each time period, all CSDs within the 'moderate' risk zone for establishment (risk CSDs) contain an population. For both scenarios, the time steps are 2000 to 2019, 2020 to 2049, 2050 to 2079 and 2080 to 2109. The 'high' risk regions for population establishment are indicated in red, the 'moderate' risk regions are in orange, the 'low' risk regions are in yellow, regions with no risk of established populations but some risk from bird-borne 'adventitious' ticks are in green, and regions with no predicted risk of either are colourless.<p><b>Copyright information:</b></p><p>Taken from "Risk maps for range expansion of the Lyme disease vector, , in Canada now and with climate change"</p><p>http://www.ij-healthgeographics.com/content/7/1/24</p><p>International Journal of Health Geographics 2008;7():24-24.</p><p>Published online 22 May 2008</p><p>PMCID:PMC2412857.</p><p></p