scholarly journals Climate Warming and Disease Risks for Terrestrial and Marine Biota

Science ◽  
2002 ◽  
Vol 296 (5576) ◽  
pp. 2158-2162 ◽  
Author(s):  
C. D. Harvell
2006 ◽  
Vol 80 (2) ◽  
pp. 93-98 ◽  
Author(s):  
T. Hakalahti ◽  
A. Karvonen ◽  
E.T. Valtonen

AbstractThe link between climate changes and disease risks from various pathogens has been increasingly recognized. The effect of climatic factors on host–parasite population dynamics is particularly evident in northern latitudes where the occurrence and transmission of parasites are strongly regulated by seasonality-driven changes in environmental temperatures. Shortened winter periods would increase growth potential of many parasite populations. The ways in which climate warming could affect life history dynamics of the directly transmitted crustacean ectoparasite Argulus coregoni and complex life cycle trematode Diplostomum spathaceum, which frequently cause problems in northern fish farming, are discussed. Increased problems for fish farming are predicted in terms of increased infection pressure from these parasites in future. This would increase problems associated with infections and increase the use of expensive management protocols with high environmental impact.


2010 ◽  
Author(s):  
Tomás Francisco Yago Vincente ◽  
Brian Mullen ◽  
Thomas N. Mather ◽  
Jean-Yves Herve

2012 ◽  
Vol 23 (3) ◽  
pp. 510-520
Author(s):  
박세정 ◽  
Byounggoo Ko ◽  
김양례 ◽  
정은지 ◽  
JungTaek Shin ◽  
...  

2000 ◽  
pp. 26-31
Author(s):  
E. I. Parfenova ◽  
N. M. Chebakova

Global climate warming is expected to be a new factor influencing vegetation redistribution and productivity in the XXI century. In this paper possible vegetation change in Mountain Altai under global warming is evaluated. The attention is focused on forest vegetation being one of the most important natural resources for the regional economy. A bioclimatic model of correlation between vegetation and climate is used to predict vegetation change (Parfenova, Tchebakova 1998). In the model, a vegetation class — an altitudinal vegetation belt (mountain tundra, dark- coniferous subalpine open woodland, light-coniferous subgolets open woodland, dark-coniferous mountain taiga, light-coniferous mountain taiga, chern taiga, subtaiga and forest-steppe, mountain steppe) is predicted from a combination of July Temperature (JT) and Complex Moisture Index (CMI). Borders between vegetation classes are determined by certain values of these two climatic indices. Some bioclimatic regularities of vegetation distribution in Mountain Altai have been found: 1. Tundra is separated from taiga by the JT value of 8.5°C; 2. Dark- coniferous taiga is separated from light-coniferous taiga by the CMI value of 2.25; 3. Mountain steppe is separated from the forests by the CMI value of 4.0. 4. Within both dark-coniferous and light-coniferous taiga, vegetation classes are separated by the temperature factor. For the spatially model of vegetation distribution in Mountain Altai within the window 84 E — 90 E and 48 N — 52 N, the DEM (Digital Elevation Model) was used with a pixel of 1 km resolution. In a GIS Package IDRISI for Windows 2.0, climatic layers were developed based on DEM and multiple regressions relating climatic indices to physiography (elevation and latitude). Coupling the map of climatic indices with the authors' bioclimatic model resulted into a vegetation map for the region of interest. Visual comparison of the modelled vegetation map with the observed geobotanical map (Kuminova, 1960; Ogureeva, 1980) showed a good similarity between them. The new climatic indices map was developed under the climate change scenario with summer temperature increase 2°C and annual precipitation increase 20% (Menzhulin, 1998). For most mountains under such climate change scenario vegetation belts would rise 300—400 m on average. Under current climate, the dark-coniferous and light-coniferous mountain taiga forests dominate throughout Mountain Altai. The chern forests are the most productive and floristically rich and are also widely distributed. Under climate warming, light-coniferous mountain taiga may be expected to transform into subtaiga and forest-steppe and dark-coniferous taiga may be expected to transform partly into chern taiga. Other consequences of warming may happen such as the increase of forest productivity within the territories with sufficient rainfall and the increase of forest fire occurrence over territories with insufficient rainfall.


Tellus B ◽  
2011 ◽  
Vol 63 (2) ◽  
Author(s):  
Kevin Chaefer ◽  
Tingjun Zhang ◽  
Lori Bruhwiler ◽  
Andrew P. Barrett

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