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Regression Relationships (regression + relationships)
Selected AbstractsScales of association: hierarchical linear models and the measurement of ecological systemsECOLOGY LETTERS, Issue 6 2007Sean M. McMahon Abstract A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance,covariance parameters in hierarchically structured data. Although hierarchical models have occasionally been used in the analysis of ecological data, their full potential to describe scales of association, diagnose variance explained, and to partition uncertainty has not been employed. In this paper we argue that the use of the HLM framework can enable significantly improved inference about ecological processes across levels of organization. After briefly describing the principals behind HLM, we give two examples that demonstrate a protocol for building hierarchical models and answering questions about the relationships between variables at multiple scales. The first example employs maximum likelihood methods to construct a two-level linear model predicting herbivore damage to a perennial plant at the individual- and patch-scale; the second example uses Bayesian estimation techniques to develop a three-level logistic model of plant flowering probability across individual plants, microsites and populations. HLM model development and diagnostics illustrate the importance of incorporating scale when modelling associations in ecological systems and offer a sophisticated yet accessible method for studies of populations, communities and ecosystems. We suggest that a greater coupling of hierarchical study designs and hierarchical analysis will yield significant insights on how ecological processes operate across scales. [source] Environmental control of fine root dynamics in a northern hardwood forestGLOBAL CHANGE BIOLOGY, Issue 5 2003GERALDINE L. TIERNEY Abstract Understanding how exogenous and endogenous factors control the distribution, production and mortality of fine roots is fundamental to assessing the implications of global change, yet our knowledge of control over fine root dynamics remains rudimentary. To improve understanding of these processes, the present study developed regression relationships between environmental variables and fine root dynamics within a northern hardwood forest in New Hampshire, USA, which was experimentally manipulated with a snow removal treatment. Fine roots (< 1 mm diameter) were observed using minirhizotrons for 2 years in sugar maple and yellow birch stands and analyzed in relation to temperature, water and nutrient availability. Fine root dynamics at this site fluctuated seasonally, with growth and mortality peaking during warmer months. Monthly fine root production was strongly associated with mean monthly air temperature and neither soil moisture nor nutrient availability added additional predictive power to this relationship. This relationship exhibited a seasonal temperature hysteresis, which was altered by snow removal treatment. These results suggest that both exogenous and endogenous cues may be important in controlling fine root growth in this system. Proportional fine root mortality was directly associated with mean monthly soil temperature, and proportional fine root mortality during the over-winter interval was strongly related to whether the soil froze. The strong relationship between fine root production and air temperature reported herein contrasts with findings from some hardwood forest sites and indicates that controls on fine root dynamics vary geographically. Future research must more clearly distinguish between endogenous and exogenous control over fine root dynamics in various ecosystems. [source] The development of a new set of long-term climate averages for the UKINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2005Matthew Perry Abstract Monthly and annual long-term average datasets of 13 climate variables are generated for the periods 1961,90 and 1971,2000 using a consistent analysis method. Values are produced for each station in the Met Office's observing network and for a rectangular grid of points covering the UK at a horizontal spacing of 1 km. The variables covered are mean, maximum, minimum, grass minimum and soil temperature, days of air and ground frost, precipitation, days with rain exceeding 0.2 and 1 mm, sunshine, and days with thunder and snow cover. Gaps in the monthly station data are filled with estimates obtained via regression relationships with a number of well-correlated neighbours, and long-term averages are then calculated for each site. Gridded datasets are created by inverse-distance-weighted interpolation of regression residuals obtained from the station averages. This method does not work well for days of frost, thunder and snow, so an alternative approach is used. This involves first producing a grid of values for each month from the available station data. The gridded long-term average datasets are then obtained by averaging the monthly grids. The errors associated with each stage in the process are assessed, including verification of the gridding stage by leaving out a set of stations. The estimation of missing values allows a dense network of stations to be used, and this, along with the range of independent variables used in the regression, allows detailed and accurate climate datasets and maps to be produced. The datasets have a range of applications, and the maps are freely available through the Met Office Website. © Crown Copyright 2005. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] Size-specific growth of bluegill, largemouth bass and channel catfish in relation to prey availability and limnological variablesJOURNAL OF FISH BIOLOGY, Issue 1 2007D. E. Shoup Growth of sympatric populations of three important sport fish species: bluegill Lepomis macrochirus, largemouth bass Micropterus salmoides and channel catfish Ictalurus punctatus, in 14 Illinois reservoirs was assessed in an attempt to relate size-specific growth to environmental conditions. Multiple regression relationships for most species and size classes explained a large percentage of the variation in growth. Growth of small bluegill (50 mm total length, LT) showed a strong negative relationship with bluegill catch per unit effort (cpue), per cent littoral area and pH. Large bluegill (150 mm LT) growth was negatively related to Daphnia spp. and benthic macroinvertebrate abundance and lake volume, and positively related to bluegill cpue. Growth of small (100 mm LT) and large (250 mm LT) largemouth bass was not well explained by any of the measured variables. Growth of both small (300 mm LT) and large (450 mm LT) channel catfish was strongly positively related to forage fishes and ichthyoplankton abundance, and per cent littoral area while negatively related to benthic macroinvertebrates. By identifying environmental conditions associated with increased growth rates, these models provide direction for managing fish populations and suggest testable hypotheses for future study of the complex interactions between environmental conditions and growth. [source] Effect of water temperature on the growth performance and digestive enzyme activities of Chinese longsnout catfish (Leiocassis longirostris Günther)AQUACULTURE RESEARCH, Issue 16 2009Hongyue Zhao Abstract The present study was carried out to investigate the influence of water temperature on the growth performance and digestive enzyme (pepsin, trypsin and lipase) activities of Chinese longsnout catfish. Triplicate groups of Chinese longsnout catfish (35.6±0.48 g, mean±SE) were reared at different water temperatures (20, 24, 28 and 32 °C). The feeding rate (FR), specific growth rate (SGR) and feed efficiency ratio (FER) were significantly affected by water temperatures and regression relationships between water temperature and FI, SGR as well as FER were expressed as FR=,0.016T2+0.91T,10.88 (n=12, R2=0.8752), SGR=,0.026T2+1.39T,17.29 (n=12, R2=0.7599) and FER=,0.013T2+0.70T,8.43 (n=12, R2=0.7272). Based on these, the optimum temperatures for FR, SGR and FER were 27.66, 26.69 and 26.44 °C respectively. The specific activities of digestive enzymes at 24 or 28 °C were significantly higher than that at 20 or 32 °C. In addition, there was a significant linear regression between FR or SGR and specific activities of pepsin and lipase, which indicated that pepsin and lipase played important roles in regulating growth through nutrient digestion in Chinese longsnout catfish. [source] | |||||||||||||