model_1 <- glm.nb(Number ~ WL, data = data_1, link = "identity")

Call:
glm.nb(formula = Number ~ WL, data = data_1,
    link = "identity", init.theta = 0.9211342881)

Deviance Residuals:
    Min       1Q   Median       3Q      Max
-1.9183  -1.0278  -0.4964  -0.1184   2.9564

Coefficients:
             Estimate Std. Error z value Pr(>|z|)
(Intercept)     53217      10358   5.138 2.78e-07 ***
   WL           12196       9314   1.309     0.19
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for Negative Binomial(0.9211) family taken to be 1)

    Null deviance: 36.140  on 29  degrees of freedom
Residual deviance: 34.976  on 28  degrees of freedom
AIC: 717.15

Number of Fisher Scoring iterations: 1


              Theta:  0.921
          Std. Err.:  0.208

 2 x log-likelihood:  -711.153