essential features of a problem - here the accumulation of bioaccumulation, uptake rate, loss rate, net amount not only

Transcription

1 A model, phy~ically or mathematically presents, the essential features of a problem - here the accumulation of metals, (Cu,Fe,Zn & Mn) in different biotopes. Modelling the movement of a pollutant in an estuarine or a marine environment, essentially in its individual components both biotic and abiotic - provides information on its movement, its concentration in different trophic levels or bioaccumulation, uptake rate, loss rate, net amount not only in the compartment but in each component of the compartment as well, The model here examines whether the metal concentration, in the organs of M. casta (estuarine clam) and D. cuneatus (marine, intertidal clam) collected from three study stations, is influenced by factors like concentrations of metals in water, sediment, month in the year, whole organism concentration and at three different stations. Tables provide number of cases (frequency) for each factor of 3 stations besides the output of multiple regression analysis. This output is utilised to develop the mbdel (probability value), keeping organs, stat ions,

2 water, eediment and sex as factors. Taking metal as dependent variable, multiple regression is applied step-wise to avoid any multicolliniarity. In the model presented here, developed by the application of multiple regression formula, organs are taken as dependent variable ; whereas water, sediment, whole animal, different months in a year are taken as independent variables. Taking individual organs with individual stations, the significance derived is presented as follows : For example, adductor muscle at station III indicates significance (Pc0.001) with sediment (factor) at station I but not with the same factor of other stations (I1 and 111) ; water or whole animal (Table 20-31). Likewise male gonad at station I. shows significance (pco. 001) with sediment (station I) but not with water or whole animal, similarly mantle in both males and females (station 11) shows high significant value - p e and p c respectively. with the factor (sediment) at station I. ~igestive diverticula of male and female animals belonging to station 111 have high significance, p and P < with the factor at station I.

3 When individual organ8 are taken all the factors namely water, sediment, month8 in a year in all 3 stations exhibit to the value of p c and the factor-whole animal-exhfbite a higher eignificance with a value of p c Tables represent output for Cu with relation to other factors at different stations, wherein the adductor muscle and foot of male (Tables 20 & 21) are influenced by station I sediment (p c 0.001). But overall significance is , and confidence interval 95.5%. In general for the organ (factor) adductor muscle at all three stations, for each of the four metals, the output was insignificant, in relation to other factors like water, sediment and whole animal. Experimentally also adductor muscle showed low accumulation of metals. But Table indicate how the model is presented wherein individual organ at a particular station is taken to be related with other stations, water and sediment besides whole animal (factors) ie. values obtained at each station are related by factors. Speaking of iron, its concentration in gills and adductor muscle of male at station I is influenced by other factors of station I1 and 111, the significance being p c (Table 32 & 33). For Zn metal, gonad of male and

4 female at station 1 and gonad of male at station 111 are highly significant by the factor (male) of station I, (Table 34-42). Here the whole animal stands as the main factor significance - p < Interestingly for metals Zn and Mn, their concentration in the whole animal (male) showed a higher value than that in females (chapter 4 ), with the specified observation there being the high concentration in the environment, hence higher uptake by males body in specific months of the year. The observation specified over here is also on same lines - as a specific factor (metal) in a specific period (month) influencing accumulation in males and not females. For the metal Mn, the gill and mantle tissue of male and female at station 111 and the foot of female show significance with the factor (water) at station I11 (p < 0.001). The gills of male and female and the adductor muscle of female showed significant result (p < 0.001) with water of station 11. In our analysis also at station I1 the metal accumulation in organs (chapter 5) was in the order of gill > digestive diverticula z gonad > mantle > foot z adductor muscle. Mantle tissue of both male and female from station 11 indicates significance ip < 0.001) with sediment (station I). Gill tissue of male and female from station I1

5 exhibits significance (p c ) with the water at station 11; the gill tissue besides mantle of male and female from station 111 a180 depicts significance (p c ). In the experimental analysis already presented in chapter 3, at station I the concentration value for Fe and Zn was higher than Cu and Mn, with sediment (station I - factor) showing maximum accumulation of metal than water. At the eame station the accumulation order for organs was gill > mantle > Digestive diverticula > gonad foot > adductor muscle. In the model developed also gill showed a significance of p c with the factor (sediment, station I). It is obvious that not all the factors exhibit significance, but specific factors, specific station and in relative value. Nevertheless, the factor depicting significance exhibits its influence on that particular metal (Cu, Fe, Zn and Mn) or that the metal value (bioaccumulation) depends on one or more of these factors. When all factors are combined the confidence limit obtained is 95%. Model exhibits statistically significance - p < to that particular factor i.e water / sediment. The same is presented through a flow chart; wherein it shows how each factor has influence on the uptake of the metal or how metal (accumulation)

6 depends on a specific factor at a specific station. In general when a factor is selected, the influence it has on metal (uptake rate) at a particular organ and at specific station gets depicted.

7 Table - 20 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF x9 _C-.ICI-III X2 1,522 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID 4 MEAN SQUARE 5.780E-01 Table - 21 UNYJEIGHTED LEAST SQUARES LINEAR REGRESSION OF " X19 x20 X , E E E E-03 (I , , I * 43-1 r D E G OF ~ FREEDOM ~ ~ ~ 5 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED o.g?a2 RE^^^. MEAN BQUARE 6.165E-01

8 Table - 22 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X I2..LLICIIII --I ,5483E ,7950 5, , OVERALL F P VALUE ADJUSTED R SQUARED 0,9873 R SQUARED RESID. MEAN SQUARE Table - 23 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X , E-01: 5.8Q24E , E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED 0.9'760 RESID. MEAN SQUARE

9 Table - 24 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF Xi7 pred I CTOR C-.e-.ILIII ----I E E-01 la529oe , OVERALL F P VALUE 0.000, ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table - 25 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X18 PIlJ?r)I CTOR em E E E I , ' E-02 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1.327E-01

10 Table - 26 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF XI ---e.ii---- X25 X26 X27 X28 X29 X30 -ow--.* , ,7651E E I ,1389E E-01 8, E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED 0,9833 RESID. MEAN SQUARE 3,997 Table - 27 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X3 c---c E-02 2, , ll.---l , OVERALL F P VALUE ADJUSTED R SQUARED SQUARED 0,9788 RESID, MEAN SQUARE 3.853

11 Table - 28 ONWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X i0 CLLI-I-aI ---I-L-III E E E-01-6 * 2364Em.02 1, E , E m , , OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 5.720E-01 Table - 29 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF XI1 X19 x E E E ,2925E ,1513E E DECREES OF FREEDOM 5 OVERALL F P VALUE 0.00Od ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 4.374E-01

12 Table - 30 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF xi I E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1.701E-01 Table - 31 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X13 --I X19 XZO OVERALL F P VALUE 0, 0001 ADJUSTED R SQUARED SQUARED RESID, MEAN SQUARE 1.084E-01

13

14 Table -34 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X a X , E e7445E-02 50,085 1, OVERALL F 14,49 P VALUE 0, 0048 ADJUSTED R SQUARED R SQUARED 0.,9456 RESID. MEAN SQUARE Table -35 X ,4340E E-02 17, E c OVERALL F 47,24 P VALUE ADJUSTED R SQUARED R SQUARED 0,9827 RESID, MEAN SQUARE 26e65

15 Table - 36 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X15 - I E ,6724E E-01 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table - 37 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF XI8 PR.'3DICTOR I I X Ob67 X E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID, MEAN SQUARE 38.30

16 Table - 38 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X X E u--(l E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table -39 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X I. x I * 75 3,0274E E E , OVERALL F P VALUE ADJUSTED R SQUARED 0,9421 R SQUARED I~RSID. MEAN SQUARE 73.10

17 Table - 40 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X9 ---I I E ,6846E , ow OVERALL F P VALUE ADJUSTED,R SQUARED R SQUARED RESID. MEAN SQUARE Table -41 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X11 PR 2D I CTOR VAHl ABLE$.-I ,983-7e1498E ,5263E I , E ,0681E E-01 OVERALL F P VALUE A~.TWY~ED R SQUARED Ei SQUARED RESID. MEAN SQUARE 33e54

18 Table - 42 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X X ow E E ,2113E E-01 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 43.14

19 Table - 43 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X8 Ice E E E E E STUDENT 'S T OVERALL F P VALUE 0,0000 ADJUSTED R SQUARED 0,9812 R SQUARED RCSID. MEAN SQUARE 7, Table - 44 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X8 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 8.423E-02

20 Table -45 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF xi5 lcic---ii X25 X26 X27 X28 X29 X E ,58?6E (llE ~0bl E E E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1.68lE-01 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X I---I X25 X26 X27 X28 X29 x E-01-3, , E E ~~~GREEs OF FREEDOM 5 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 5.465E-02

21 Table - 47 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X4 325 X26 X27 X28 X29 X E I OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table - 48 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X? OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 9.281E-01

22 Table - 49 unweighted LEAST SQUARES LINEAR REGRESSION OF X I X25 X26 X27 X28 X29 X30-1-LIIII-l 4,7156 2,1849s E OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table - 50 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X E I E-02 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1.193

23 Table - 51 unweighted LEAST SQUARES LINEAR REGRESSION OF X12 I c E , , OVERALL F P VALUE 0,0007 ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1,219 Table - 52 IJNWEIGIITED LEAST SQUARES LINEAR l1n!:(;11essiun OF X13 ---,--,-I X19 x22 -, E , OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED Om 9907 J~ESID. MEAN SQUARE 5*070E-01

24 Table - 53 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF XI3 VARf ABLES ---..l--oo- X25 X26 X27 X28 X29 X , ,1332E-01-9,1170E E Do ,9099E-01 2, OVERALL F P VALUE 0,0013 ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE Table - 59 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X14 VARl ABLES X19 --o E I , woo , E-02 4, OVERALL F P VALUE OwQOO1 AUJUSTED R SQUARED 0.9'751 R SQUARED RESID. MEAN SQUARE 7.227E-01

25 Table - 55 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X17 CC..---o E , Dm le4058e-02 OVERALL F P VALUE 0,0000 ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 1.750E-01 Table - 56 UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF X x20 x22 x I--* E-01-1,156lE E-02 OVERALL F P VALUE ADJUSTED R SQUARED R SQUARED RESID. MEAN SQUARE 4,

26 A Model for the flow of Metal Concentrations Fig. 17 J 55-