Modeling Black-Tailed Deer Population Dynamics Using Structured and Unstructured Approaches

Abstract: We used cohort analysis to reconstruct the female segment of a Columbian black-tailed deer (Odocoileus hemionus columbianus) population from 1979 to 2000 in the western Cascades of Washington, USA. We used reconstructed population estimates and age class representations to analyze relationships between population change and female density, forage availability, and weather influences. We applied stage structured and unstructured modeling approaches and used information-theoretic methods to select the best models. We used habitat covariates to develop predictive functions for fertility and survival parameters in structured models. The best structured and unstructured models were composed of combinations of factors including population density, forage availability, and winter weather. Structured and unstructured models could assist with management of black-tailed deer by providing the ability to predict deer population change given covariate values.     

Field Evaluation of Some Models Estimating the Seasonal Pattern of Airborne Ascospores of Venturia inaequalis

A 6-year study was carried out to evaluate the accuracy of some models in estimating airborne ascospores of Venturia inaequalis . The proportion of the season's ascospores trapped on each discharge event was compared with the proportion of mature ascospores, estimated by the New Hampshire model or by some related models. The models differed from each other in the degree-day cumulation, accounting or not for the leaf litter wetness caused by rainfall or by deposition of atmospheric humidity. The New Hampshire model did not fit spore trappings well: 59% of the actual values fell outside the range of the estimates, and 83% of them were overestimates. The wide discrepancy between reality and estimates resulted from the effect of dryness: when many consecutive rainless days occurred, the proportion of ascospores trapped was constantly lower than the model estimates, due to a slowed spore maturation. The effect of dryness was evident during the greater part of the ascospore maturity season, irrespective of the proportion of the season's ascospores that had just matured when the dry period began. Models accounting for leaf litter wetness significantly improved estimates. Therefore, in the Po Valley, the accuracy of the New Hampshire model can be improved by accumulating degree-days only when leaf litter is wet.     

The influence of year-to-year variations in winter weather on the dynamics of Daphnia and Eudiaptomus in Esthwaite Water, Cumbria

1. Micro-crustacea of the genus Daphnia and Eudiaptomus have evolved different physiological mechanisms for coping with life in a rapidly changing environment. In this paper, we analyse some of the physical and biological factors influencing the winter abundance of the two species in a small lake (Esthwaite Water in Cumbria).
2. The results demonstrate that much of the year-to-year variation in their relative abundance can be related to long-term changes in the weather. The highest numbers of Daphnia were typically found in cold, calm winters when small flagellates were relatively abundant. In contrast, the highest numbers of Eudiaptomus were found in mild, windy winters when the phytoplankton community was dominated by colonial diatoms.
3. Year-to-year variations in the winter abundance of Eudiaptomus had no effect on their subsequent development but the numbers of overwintering Daphnia had a significant effect on the size of their first spring 'cohort'. The most important factor influencing the overwintering performance of the two species was the water temperature.
4. Winter air temperatures over much of Europe are influenced by the atmospheric pressure variation known as the North Atlantic Oscillation (NAO). Winter water temperatures in Esthwaite Water were strongly correlated with this empirical index and there was a significant positive correlation between the NAO and the number of overwintering Eudiaptomus.     

Agronomic and meteorological factors affecting the severity of leaf blotch caused by Mycosphaerella graminicola in commercial wheat crops in England

Factors affecting the severity of leaf blotch on the two upper leaves of wheat plants in crops at the milky ripe growth stage (GS 73–75) were investigated using survey data from 3513 randomly selected wheat crops sampled during 1985–1996. Year‐to‐year variation in disease severity was greater than spatial variability at county level, although both showed significant differences. The presence of disease above a 5% severity threshold was modelled using random effects logistic regression (Generalised Linear Mixed Model), which enabled risk variables measured at the field level to be combined with meteorological variables estimated at county level. The final model included terms for the fixed effects of disease resistance rating, date of sowing, high risk septoria periods in May and June, number of fungicide sprays and number of days with frost (≤‐2°C) in November. The percentage of crops above the threshold decreased with later sowing, increased number of November frost days and increased number of fungicide sprays. In contrast, high risk septoria periods (rain splash events) in May and June showed a positive correlation with the percentage of crops above the threshold. There were benefits from using resistant cultivars. The model showed that a range of risk variables were of broadly equivalent importance in determining the development of leaf blotch. These risk variables should be integrated in any scheme designed to support fungicide use decisions.