Demography and viability analyses of a diamondback terrapin population

2003 ◽  
Vol 81 (4) ◽  
pp. 716-726 ◽  
Author(s):  
Matthew G Mitro

The diamondback terrapin, Malaclemys terrapin, is a long-lived species with special management requirements but quantitative analyses to support management are lacking. I analyzed mark–recapture data and constructed an age-classified matrix population model to determine the status and viability of the only known diamondback terrapin population in Rhode Island. Female diamondback terrapins were captured, marked, and recaptured while nesting during 1990–2001. Population growth rate (λ) was 1.034 (95% confidence interval = 1.012–1.056). For the preceding 5 years, however, abundance had been stable at about 188 breeding females. Adult apparent survival was high but declined slightly by 0.14% per year from 0.959 in 1990 to 0.944 in 2000. Recruitment of breeding females also decreased during the study period; therefore, survival was increasingly a greater component of population growth rate. Juvenile survival was 0.565 at λ = 1.034 and 0.446 at λ = 1. Both retrospective (mark–recapture) and prospective (matrix population model) analyses showed a greater influence of survival versus reproduction on population growth. Population- model projections showed that capping nests to improve reproductive success could increase population growth rate, but the magnitude of increase was positively related to pre-reproductive survival, therefore negating nest capping as a remedy for declining populations or poor survival. Extinction attributable to demographic stochasticity is unlikely.

1980 ◽  
Vol 51 (3) ◽  
pp. 831-837 ◽  
Author(s):  
John N. McCall

A simulated completed family population model was used to illustrate bias in single-age samples which results from changes in population growth rate. The model comprised 100 families or 238 individuals who ranged from 2 to 22 yr. in age. IQ-codes from a normal distribution were assigned to these individuals so that IQ correlated –.25 with family size and –.39 with occupational level. This produced a correlation of –.27 between birth order and IQ. A random sample, stratified random sample, and a random family unit sample estimated this last correlation quite closely. But estimates of this same correlation were spuriously high for 6 of the 11 single-age groups. These results were linked to an excess of early-borns in small families and an excess of later-borns in large families.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Helena Bestová ◽  
Jules Segrestin ◽  
Klaus von Schwartzenberg ◽  
Pavel Škaloud ◽  
Thomas Lenormand ◽  
...  

AbstractThe Metabolic Scaling Theory (MST), hypothesizes limitations of resource-transport networks in organisms and predicts their optimization into fractal-like structures. As a result, the relationship between population growth rate and body size should follow a cross-species universal quarter-power scaling. However, the universality of metabolic scaling has been challenged, particularly across transitions from bacteria to protists to multicellulars. The population growth rate of unicellulars should be constrained by external diffusion, ruling nutrient uptake, and internal diffusion, operating nutrient distribution. Both constraints intensify with increasing size possibly leading to shifting in the scaling exponent. We focused on unicellular algae Micrasterias. Large size and fractal-like morphology make this species a transitional group between unicellular and multicellular organisms in the evolution of allometry. We tested MST predictions using measurements of growth rate, size, and morphology-related traits. We showed that growth scaling of Micrasterias follows MST predictions, reflecting constraints by internal diffusion transport. Cell fractality and density decrease led to a proportional increase in surface area with body mass relaxing external constraints. Complex allometric optimization enables to maintain quarter-power scaling of population growth rate even with a large unicellular plan. Overall, our findings support fractality as a key factor in the evolution of biological scaling.


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