Spring temperature, migration chronology, and nutrient allocation to eggs in three species of arctic-nesting geese: Implications for resilience to climate warming

2018 ◽  
Vol 24 (11) ◽  
pp. 5056-5071 ◽  
Author(s):  
Jerry W. Hupp ◽  
David H. Ward ◽  
David X. Soto ◽  
Keith A. Hobson
Parasitology ◽  
2015 ◽  
Vol 142 (10) ◽  
pp. 1306-1317 ◽  
Author(s):  
OWEN J. GETHINGS ◽  
HANNAH ROSE ◽  
SIÂN MITCHELL ◽  
JAN VAN DIJK ◽  
ERIC R. MORGAN

SUMMARYMismatch in the phenology of trophically linked species as a result of climate warming has been shown to have far-reaching effects on animal communities, but implications for disease have so far received limited attention. This paper presents evidence suggestive of phenological asynchrony in a host-parasite system arising from climate change, with impacts on transmission. Diagnostic laboratory data on outbreaks of infection with the pathogenic nematode Nematodirus battus in sheep flocks in the UK were used to validate region-specific models of the effect of spring temperature on parasite transmission. The hatching of parasite eggs to produce infective larvae is driven by temperature, while the availability of susceptible hosts depends on lambing date, which is relatively insensitive to inter-annual variation in spring temperature. In southern areas and in warmer years, earlier emergence of infective larvae in spring was predicted, with decline through mortality before peak availability of susceptible lambs. Data confirmed model predictions, with fewer outbreaks recorded in those years and regions. Overlap between larval peaks and lamb availability was not reduced in northern areas, which experienced no decreases in the number of reported outbreaks. Results suggest that phenological asynchrony arising from climate warming may affect parasite transmission, with non-linear but predictable impacts on disease burden. Improved understanding of complex responses of host-parasite systems to climate change can contribute to effective adaptation of parasite control strategies.


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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