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7篇 您的检索式:作者名="Janet Franklin"
    题名 作者 年代 出处 被引量
1A comparison of methods for monitoring multitemporal vegetation change using Thematic Mapper imagery显示文摘John Rogan Janet Franklin Dar A Roberts 2002Remote Sensing of Environment2002,,1:1
2Incorporating spatial dependence in predictive vegetation models显示文摘Jennifer Miller Janet Franklin Richard Aspinall 2006Ecological Modelling2006,,3:1
3Mapping land-cover modifications over large areas: A comparison of machine learning algorithms 显示文摘John Rogan Janet Franklin Doug Stow 2008Remote Sensing of Environment2008,,112:1
4Histological and lmmunophenotypic Profile of Nasal NK/T cell lymphomas From Peru : High Prevalence of P53 Overexpression 显示文摘Leticia MD Janet L Franklin MD 1999Human Pathology1999,30,7:1
5A comparison of methods for monitoring multitemporal vegation change using Thematic Mapper imagery显示文摘John Rogan Janet Franklin 2002Remote Sensing of Environment2002,80,:1
6Predicting the distribution of shrub species in southern California from climate and terrain-derived variables 显示文摘FRANKLIN JANET 1998Journal of Vegetation Science1998,9,:1
7Cross-scale modeling of surface temperature and tree seedling establishment in mountain landscapes显示文摘Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heights of only several centimeters.Currently,future climate models predict temperature at 2 m above ground,leaving ground-surface microclimate not well characterized.Methods:Using a network of field temperature sensors and climate models,a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature.Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.Results:The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing,south-facing,valley,and ridgeline topographic settings,and when compared to measured temperatures yielded an R2 of 0.88,0.80,0.88,and 0.80,respectively.Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures,resulting in R2 values of 0.86,0.77,0.72,and 0.79 for north-facing,south-facing,valley,and ridgeline topographic settings.Quasi-Poisson regressions predicting recruitment of Quercus kelloggii(black oak)seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.Conclusion:Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment.Such methods could be applied to improve projections of species’range shifts under climate change.Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.John R Dingman Lynn C Sweet Ian McCullough Frank W Davis Alan Flint Janet Franklin Lorraine E Flint 2013Ecological Processes2013,2,1:1
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