CN102217499A - Method for predicating biomass of overground part of Aegiceras corniculatum - Google Patents
Method for predicating biomass of overground part of Aegiceras corniculatum Download PDFInfo
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- CN102217499A CN102217499A CN2011101443713A CN201110144371A CN102217499A CN 102217499 A CN102217499 A CN 102217499A CN 2011101443713 A CN2011101443713 A CN 2011101443713A CN 201110144371 A CN201110144371 A CN 201110144371A CN 102217499 A CN102217499 A CN 102217499A
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Abstract
The invention discloses a method for predicating biomass of overground part of Aegiceras corniculatum and belongs to the technical field of coastal mangrove ecological system protection and restoration, which is implemented according to the steps as follows: selecting Aegiceras corniculatum individuals with a certain number of n of different sizes and with statistics significances, respectively measuring the crown diameters and heights of the Aegiceras corniculatum individuals; then measuring the organisms on the overground part actually by a harvest method and implementing regression implemented according to a power exponent equation: Y=a*b, thus obtaining a power exponent equation capable of predicating the biomass of the overground part of the Aegiceras corniculatum based on the crown diameters and heights; then actually measuring the heights H (m) and the crown diameters CD (m) of the Aegiceras corniculatum plants the biomass liveweight of which is to be predicated and respectively substituting the heights and the crown diameters to the power exponent equation, wherein the calculated AGB value is the biomass liveweight (kg, fresh weight) of the overground part of the Aegiceras corniculatum tree to be predicated. As the heights and the crown diameters with obvious characteristics are adopted in the method for predicating biomass of overground part of Aegiceras corniculatum, the precision is high. The predicating method is simple and convenient, and is particularly easy to operate in muddy mangrove marshes.
Description
Technical field
The present invention announces a kind of method of predicting mangrove Aegiceras corniculatum acrial part biomass, the technical field that belongs to coastal mangrove ecosystem protection and repair.
Background technology:
The plant of, the most critical factor the most active as the ecosystem, the size of its biomass directly affects the 26S Proteasome Structure and Function of this ecosystem, also be one of important evaluation index of ecosystem health situation simultaneously, therefore, the acquisition of phytomass is great for the Research Significance of the ecosystem.Generally, the acquisition of phytomass is normal adopts direct sample prescription harvesting method, yet for this just fragile and rare mangrove ecosystem of littoral zone, directly sample prescription harvesting method is not only destructive big, and also is difficult to harvesting because of mire.Therefore, people often utilize some growth indexes that are simple and easy to survey, by similar regression equation analysis, the acrial part biomass of prediction Different Red tree plant (Aboveground Biomass, AGB).Wherein, the diameter of a cross-section of a tree trunk 1.3 meters above the ground of mangrove (Diameter at Breast Height, DBH), the height of tree (Tree Height, H), (Basal Diameter D) is growth indexes the most commonly used for base footpath.The regression equation of using mainly contains logAGB=m+nlog (DBH
2* H), logAGB=m+nlogH, logAGB=m+nlogDBH, logAGB=m+nlog (D
2H *) several logarithmic equation forms such as.Also have the corresponding AGB=a of the being converted to (DBH of above several forms
2* H)
b, AGB=aH
b, AGB=aDBH
b, AGB=a (D
2* H)
bThe idempotent exponential equation forms.A wherein, b, m, regression coefficients such as n are constant.(Canopy Diameter, CD) index adopts the ground biomass of following prediction equation mangrove: AGB=a+bH/ ㏑ H+cCD+dD with the height of tree, basic stem two indexes also once to have indivedual researchs to increase the hat width of cloth
2, a wherein, b, c, regression coefficients such as d are constant.Above regression equation is widely used in the prediction that Avicennia marina, autumn eggplant, Hai Sang, sea lacquer, angle block fruit etc. have the shrub mangrove acrial part biomass of obvious stem at present, and accuracy is higher.Also there is the scholar that above regression equation is applied to there is not obvious stem, mostly is in the prediction of the Aegiceras corniculatum acrial part biomass that is the shape of growing thickly, although the result shows higher accuracy is arranged also, but in the prediction of reality, growth indexes such as the diameter of a cross-section of a tree trunk 1.3 meters above the ground of Aegiceras corniculatum, basic stem all are difficult to accurately even can't determine, thereby the accuracy of prediction will reduce greatly.In order to address this problem, the above prediction mode of research and utilization is abroad arranged, and the Aegiceras corniculatum that will have many stems (growing thickly) stem is one by one predicted the back addition respectively, tries to achieve whole strain acrial part biomass, though the accuracy that this has increased prediction has increased the complexity of predicting widely.
Summary of the invention:
The present invention seeks to by selecting and acrial part biomass height correlation and convenient some growth indexes of easily surveying, make up regression equation between acrial part biomass and these indexs, thereby realize Aegiceras corniculatum, reach and easy the calculating to a nicety of multiple mangrove acrial part biomass of its form similar (many stems are grown thickly).
For realizing above target, the present invention mainly by the following technical solutions, a kind of method of predicting Aegiceras corniculatum acrial part biomass, carry out according to following step:
(1) select the Aegiceras corniculatum individuality of the some n vary in size, record its hat width of cloth, height of tree H(m respectively with statistical significance) after, adopt harvesting method actual measurement acrial part biomass AGB(kg, fresh weight), according to Y=aX
bThe power exponent equation of form returns, and obtains regression coefficient a, b, and wherein independent variable X is CD
2* H, dependent variable Y is AGB; Thereby obtain based on the hat width of cloth and the height of tree, the power exponent equation of measurable Aegiceras corniculatum acrial part biomass: AGB=a (CD2*H) b;
(2) plant height H (m) of the Aegiceras corniculatum plant of field survey biomass to be predicted and hat width of cloth CD (m), with behind the above power exponent equation of its value substitution, the AGB value that calculates is Aegiceras corniculatum acrial part biomass (kg, fresh weight) to be predicted respectively.
Some n described in the present invention with statistical significance, its value is n 〉=16;
Obtain regression coefficient a, b among the present invention, its value is a=3.1253, and b=0.9063 will get equation after the coefficient substitution:
AGB=3.1253(CD2*H)0.9063?。
Advantage of the present invention: Aegiceras corniculatum belongs to no obvious stem, the shrub that is the shape of growing thickly and dungarunga on plant type, and its diameter of a cross-section of a tree trunk 1.3 meters above the ground and base footpath are all not obvious, but above two indexes is all adopted in prediction at present, thereby error is bigger.The present invention adopts plant height and the hat width of cloth index with obvious characteristic, thereby the accuracy height.Regression equation provided by the present invention not only can directly be predicted Aegiceras corniculatum acrial part biomass, and its principle and method, can be used for the acrial part biomass that accurately predicting and tung oil tree have the other plant of similar plant type.Forecasting Methodology provided by the invention is easy, and easy operating is especially at the mangrove swamp wetland of mire.
Embodiment:
Embodiment 1: implement the place and be positioned at Luoyang, gulf, Quanzhou, Fujian Province rivers mouth wetland, this wetland has been listed in mangrove forest nature reserve, Fujian Province at present, and mangrove is based on Aegiceras corniculatum, autumn eggplant and Avicennia marina.The last ten-days period in October, in wetland, choose vary in size, the healthy Aegiceras corniculatum individuality of normal 16 strains of plant type structure, measure separately the hat width of cloth (m), the height of tree (m) after, utilize the harvesting method to survey its acrial part biomass (kg, fresh weight), according to power exponent equation AGB=a (CD
2* H)
bReturn, try to achieve a, the b value is respectively 3.1253 and 0.9063.Thereby obtain the regression equation (table 1) of measurable Aegiceras corniculatum acrial part biomass.
Table 1: based on the acrial part biomass prediction regression analysis of the hat width of cloth and the height of tree
No matter from coefficient of determination R
2, still on the relative error rate of measured value and predicted value, this regression equation all has fabulous prediction effect to Aegiceras corniculatum acrial part biomass.
Checking embodiment: in order further to verify the prediction effect of this equation, in November from wetland, choose once more vary in size, the healthy Aegiceras corniculatum individuality of normal 15 strains of plant type structure, with the same before, record separately the hat width of cloth, the height of tree and acrial part biomass respectively.Then with the hat width of cloth and the height of tree substitution power exponent regression equation AGB=3.1253 (CD of each strain
2* H)
0.9063In, obtain the predicted value of this strain Aegiceras corniculatum acrial part biomass, compare with its measured value again, thus checking and estimate the prediction effect (table 2) of this power exponent regression equation.
The checking of table 2 acrial part biomass prediction regression equation
The verification the verifying results of table 2 shows that in 15 groups of verification msgs, wherein 10 groups predicted value and measured value relative error are lower than 10%, accounts for 66.67% of sum; In addition 4 groups of predicted values and measured value relative error account for 26.67% of sum between 10-20%; Only there are 1 group predicted value and measured value relative error a little higher than 20%, account for 6.67% of sum.Therefore, utilize the power exponent regression equation power exponent regression equation AGB=3.1253 (CD of the hat width of cloth and height of tree two indexes prediction Aegiceras corniculatum acrial part biomass
2* H)
0.9063Has very accurate prediction effect.
Claims (3)
1. method of predicting Aegiceras corniculatum acrial part biomass is characterized in that carrying out according to following step:
(1) select the Aegiceras corniculatum individuality of the some n vary in size, record its hat width of cloth CD(m respectively with statistical significance), height of tree H(m) after, adopt harvesting method actual measurement acrial part biomass AGB(kg, fresh weight), according to Y=aX
bThe power exponent equation of form returns, and obtains regression coefficient a, b, and wherein independent variable X is CD
2* H, dependent variable Y is AGB; Thereby obtain based on the hat width of cloth and the height of tree, the power exponent equation of measurable Aegiceras corniculatum acrial part biomass: AGB=a (CD2*H) b;
(2) plant height H (m) of the Aegiceras corniculatum plant of field survey biomass to be predicted and hat width of cloth CD (m), with behind the above power exponent equation of its value substitution, the AGB value that calculates is Aegiceras corniculatum acrial part biomass (kg, fresh weight) to be predicted respectively.
2. a kind of method of predicting Aegiceras corniculatum acrial part biomass according to claim 1 is characterized in that wherein said some n with statistical significance, and its value is n 〉=16.
3. a kind of method of predicting Aegiceras corniculatum acrial part biomass according to claim 1 is characterized in that wherein obtaining regression coefficient a, b, and its value is a=3.1253, and b=0.9063 will get equation: AGB=3.1253 (CD2*H) 0.9063 after the coefficient substitution.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103808355A (en) * | 2014-03-04 | 2014-05-21 | 北京林业大学 | Forest measurement angulometer and application method thereof |
| CN103999736A (en) * | 2014-05-19 | 2014-08-27 | 江苏大学 | Estuary wetland mangrove forest ecological rehabilitation afforestation method |
| CN110472189A (en) * | 2018-05-11 | 2019-11-19 | 北京林业大学 | A kind of single-point multiple observations forepart prediction of plant growth method |
| CN112651143A (en) * | 2021-01-26 | 2021-04-13 | 兰州交通大学 | Estimation method for biomass on haloxylon ammodendron ground |
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| CN101642021A (en) * | 2009-09-08 | 2010-02-10 | 江苏大学 | Method for forecasting rhizoma atractylodis growth by four-parameter logistic equation |
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| RU2009110572A (en) * | 2009-03-23 | 2010-09-27 | Екатерина Петровна Кондратенко (RU) | METHOD FOR FORECASTING SPRING WHEAT YIELD |
| CN101642021A (en) * | 2009-09-08 | 2010-02-10 | 江苏大学 | Method for forecasting rhizoma atractylodis growth by four-parameter logistic equation |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103808355A (en) * | 2014-03-04 | 2014-05-21 | 北京林业大学 | Forest measurement angulometer and application method thereof |
| CN103999736A (en) * | 2014-05-19 | 2014-08-27 | 江苏大学 | Estuary wetland mangrove forest ecological rehabilitation afforestation method |
| CN103999736B (en) * | 2014-05-19 | 2016-09-07 | 江苏大学 | A kind of estuarine wetland mangrove forest ecological repairs method of forestation |
| CN110472189A (en) * | 2018-05-11 | 2019-11-19 | 北京林业大学 | A kind of single-point multiple observations forepart prediction of plant growth method |
| CN112651143A (en) * | 2021-01-26 | 2021-04-13 | 兰州交通大学 | Estimation method for biomass on haloxylon ammodendron ground |
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