Why the significance of variable is changed due to the change in number of variable?

@hinduja1234 wrote:

I am currently solving one regression problem using linear regression in which I have a created a regression model in R.

model1=lm(Price ~ Year+WinterRain+AGST+HarvestRain+Age+FrancePop,data=wine)
summary(model1)

Call:
lm(formula = Price ~ Year + WinterRain + AGST + HarvestRain + Age + FrancePop, data = wine)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.48179 -0.24662 -0.00726  0.22012  0.51987 

Coefficients: (1 not defined because of singularities)
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  7.092e-01  1.467e+02   0.005 0.996194    
Year        -5.847e-04  7.900e-02  -0.007 0.994172    
WinterRain   1.043e-03  5.310e-04   1.963 0.064416 .  
AGST         6.012e-01  1.030e-01   5.836 1.27e-05 ***
HarvestRain -3.958e-03  8.751e-04  -4.523 0.000233 ***
Age                 NA         NA      NA       NA    
FrancePop   -4.953e-05  1.667e-04  -0.297 0.769578    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.3019 on 19 degrees of freedom
Multiple R-squared:  0.8294,    Adjusted R-squared:  0.7845 
F-statistic: 18.47 on 5 and 19 DF,  p-value: 1.044e-06

I have looked into the significances of the model variable by looking into a number of stars which tells about the significances of the variable .So I have removed one variable french population so I get a better model.

creating new model

 model1=lm(Price ~ Year+WinterRain+AGST+HarvestRain+Age,data=wine)
 summary(model1)

Call:
lm(formula = Price ~ Year + WinterRain + AGST + HarvestRain +  Age, data = wine)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.45470 -0.24273  0.00752  0.19773  0.53637 

Coefficients: (1 not defined because of singularities)
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) 44.0248601 16.4434570   2.677 0.014477 *  
Year        -0.0239308  0.0080969  -2.956 0.007819 ** 
WinterRain   0.0010755  0.0005073   2.120 0.046694 *  
AGST         0.6072093  0.0987022   6.152  5.2e-06 ***
HarvestRain -0.0039715  0.0008538  -4.652 0.000154 ***
Age                 NA         NA      NA       NA    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.295 on 20 degrees of freedom
Multiple R-squared:  0.8286,    Adjusted R-squared:  0.7943 
F-statistic: 24.17 on 4 and 20 DF,  p-value: 2.036e-07

After creating a new model, the variable significances has changed from the previous model .I want to know why this happen.

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