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B. R. Wells Rice
Temperature is a dominant factor in rice development. Various thermal time methods are a possible way to model the development, and are able to predict phenological stages such as flowering. In our studies three different bilinear models were studied concerning the predicting of duration from emergence to flowering of rice based on phenological data collected from rice experiments carried out in the Irrigation Research Institute between 1991 and 1999 with the rice variety Ringola. The advance from linear model, which is preferred in agriculture involves an upper threshold temperature as a second parameter, and describes the development rate with a constant (Method 1) and two different steepness functions of linear decrease (Method 2 and 3) above this threshold. The duration of the phenological phase showed only slight variations (coefficient of variation, CV=6.43), thus the average number of days offered an acceptable prediction. The linear method did not show a significant improvement (CV=3.96) on the level P=5%. However the three tested bilinear methods resulted in significant development (CV=2.75; 2.71 and 2.73) if adequate parameters were applied. The distribution of variation coefficients according to different parameter combinations gave information on sensitivity of methods, while the adequate parameters of lower and upper thresholds provided some hints about climatic demands of rice.
Landscape complexity in the boreal forest is a function of physiographic complexity (spatial processes) and post-fire successional (temporal) processes operating across scales. In this study we examine the role of succession and topographic complexity in determining the landscape complexity of Riding Mountain National Park, Manitoba, Canada. Landscape complexity is assessed by using multifractal analysis to quantify landscape patterns from Landsat TM imagery. To determine whether complexity changes with age, . young. sites (post-fire stand ages = 11 and 30 years) were matched with adjacent . old. sites (post-fire stand ages ≯ 95 years). The influence of physiography on landscape complexity is examined by comparing sites having . simple. and . complex. physiographies (as determined by fractal surface analysis). The scaling properties of landscape complexity are determined by calculating the multifractal spectrum (Dq) for each site. Landscape complexity increases during early succession; multifractal profiles of 11 year old sites are lower than those of adjacent older stands. However, the multifractal profiles of 30 year old and adjacent older stands are indistinguishable, suggesting that change in landscape complexity occurs within 30 years following fire. Physiographically . complex. sites have consistently greater landscape complexity than adjacent . simple. sites. We conclude that landscape complexity increases over time as succession proceeds, and in space along a gradient from . simple. to . complex. physiographies. It follows that landscape complexity is lowest in early-successional, physiographically . simple. sites and highest in late-successional, physiographically . complex. sites.