scholarly journals Leaf area index change in ice-storm-damaged sugar maple stands

2001 ◽  
Vol 77 (4) ◽  
pp. 627-635 ◽  
Author(s):  
Ian Olthof ◽  
Douglas J. King ◽  
R. A. Lautenschlager
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Sugar Maple ◽  
Forest Damage ◽  
Time Interval ◽  
Short Time Interval ◽  
Ice Storm ◽  
Height Range ◽  
Area Index ◽  
Understory Vegetation Cover

Changes in Leaf Area Index (LAI) between the summers of 1999 and 2000 were measured using the TRAC optical instrument in sugar maple stands damaged by the 1998 ice storm. Changes were determined to be significant if they were greater than the 95% bounds of the instrument precision. They were evaluated in relation to 1998 canopy damage estimates, 1999 stand treatments (lime, fertilizer, lime + fertilizer, herbicide, none), and 1999 understory vegetation cover. Results show that LAI change is significantly related to overstory damage, and understory abundance in the 0–7-m height range. Plot treatments were not related to these LAI changes, possibly due to the short time interval between application and LAI measurement. Keywords: forest damage, ice storm, leaf area index, optical instruments, TRAC

The effect of ice damage and post-damage fertilization and competition control on understory microclimate of sugar maple (Acer saccharum Marsh.) stands

2003 ◽  
Vol 79 (1) ◽  
pp. 82-90 ◽  
Author(s):  
William C Parker
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Acer Saccharum ◽  
Sugar Maple ◽  
Natural Disturbance ◽  
Ice Storm ◽  
Area Index ◽  
Competition Control

The influence of ice damage, fertilization, and herbicide treatments on understory microclimate was examined in several sugar maple stands during three growing seasons. Stands with greater initial crown damage and lower leaf area index had higher understory light levels, elevated air temperatures and lower humidity. Ice damage had comparatively less effect on the below-ground environment. Stands with higher damage and lower leaf area index exhibited higher soil temperature and lower soil moisture availability in certain years. The strength and significance of the relationships of canopy features with microclimatic variables diminished over time with canopy recovery and growth of understory vegetation. Fertilization treatment effects on stand microclimate were not apparent, but competition control reduced understory leaf area, increased soil temperature, and had minimal influence on soil moisture status. Key words: canopy, fertilization, ice storm, microclimate, natural disturbance, sugar maple, vegetation management

scholarly journals Relations Between Leaf Area Index and Growth Characteristics of Florunner, Southern Runner, and Sunrunner Peanut1

1991 ◽  
Vol 18 (1) ◽  
pp. 30-37 ◽  
Author(s):  
David P. Davis ◽  
Timothy P. Mack
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Fungal Pathogens ◽  
Dry Weight ◽  
Growth Characteristics ◽  
Vegetative Stage ◽  
Height Range ◽  
Area Index ◽  
Number Of Leaves ◽  
Leaf Dry Weight

Abstract Growth characteristics of three commonly planted peanut cultivars were measured during the 1988 and 1989 growing seasons at the Wiregrass Substation in Headland, Ala., to develop equations for predicting leaf area index (LAI) from other growth varibales. These equations were needed to allow rapid estimation of leaf area loss from foliar-feeding insects or foliar-fungal pathogens. Conventionally planted and tilled fields of Florunner, Sunrunner and Southern Runner peanut (Arachis hypogaea L.) were sampled for plant vegetative stage, reproductive stage, height, number of leaves, leaf area, leaf dry weight, number of pods, pod dry weight, stem dry weight, and stand density. Most growth characteristics increased linearly (p<0.05) with time in both years. LAI was significantly correlated (P<0.05) with most growth variables for each cultivar. Linear regression was used to create equations for prediction of LAI from leaf dry weight (range of R2 = 0.93 to 0.97) and number of leaves (range of R2 = 0.74 to 0.95) for each cultivar, and all cultivars combined. Equations were also developed to predict LAI from plant height (range of R2 = 0.85 to 0.96) and plant vegetative stage (range of R2 = 0.81 to 0.83). These equations should be useful to those who wish to estimate LAI from other growth variables.

Overstory and understory leaf area index as indicators of forest response to ice storm damage

2003 ◽  
Vol 3 (1) ◽  
pp. 49-64 ◽  
Author(s):  
Ian Olthof ◽  
Douglas J. King ◽  
R.A. Lautenschlager
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Ice Storm ◽  
Storm Damage ◽  
Area Index ◽  
Ice Storm Damage

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

Hyperspectral characteristics and leaf area index monitoring of rice (Oryza sativa L.) under carbon dioxide concentration enrichment

2021 ◽  
Vol 54 (3) ◽  
pp. 231-243
Author(s):  
Chao Liu ◽  
Zhenghua Hu ◽  
Rui Kong ◽  
Lingfei Yu ◽  
Yuanyuan Wang ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Oryza Sativa ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Oryza Sativa L ◽  
Carbon Dioxide Concentration ◽  
Area Index
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