Read age-specific survival without changing denominators

Survivorship follows a cohort

A cohort is a group beginning observation at a comparable age or event. Survivorship records the fraction still alive at successive ages. Type I patterns have relatively high survival until later life; Type II patterns have an approximately constant mortality risk through the interval considered; Type III patterns have large early losses followed by better survival among those remaining. These are descriptive patterns, not rigid rules for every individual or environment.

A constant mortality risk is proportional, not a constant number of deaths. If half the survivors die each interval, an initial 100 becomes 50, then 25, then 12.5 as an expected count. On a logarithmic survivorship scale, equal proportional survival over equal intervals gives a straight declining pattern. Check the axes before comparing curves.

Keep denominators visible

The original synthetic cohort begins at 100. Eighty survive to stage 1. Of those 80, 50% survive to stage 2, leaving 40. First-interval mortality is 20/100=20%; second-interval conditional mortality is 40/80=50%; cumulative mortality is 60/100=60%.

Adding the two interval percentages would give 70%, which is wrong because their denominators differ. Multiplying successive survival fractions, 0.8×0.5=0.4, gives the final surviving fraction. No births or migration enter this cohort model.

Change first-stage survival to 20 of 100 with the same second-stage conditional survival. Final expected survivors are 10, not 50. The second-stage percentage has not changed, but cumulative survival has. Interpret a reported percentage only after identifying the population to which it applies.

A curve needs more than three points

The lab has only three stages and cannot establish a complete empirical age-specific mortality curve. Exposure duration, censoring, follow-up loss and age determination can affect estimates. An organism not observed again is not automatically known to be dead. Repeated observations of the same individuals are not independent cohorts.

For a virtual comparison, specify equal age intervals and comparable observation effort. If one population has more young individuals in a cross-sectional sample, that is an age-structure observation, not necessarily a survivorship curve: births and migration can shape the count.

Transfer

A cohort retains 60% through one interval and 80% of those through the next. Final survival is 0.6×0.8=48%; cumulative mortality is 52%. Explain why this differs from adding 40% and 20%. Then describe what extra age-specific observations would distinguish high early mortality from constant proportional mortality across a lifespan. No animal tracking or capture is assigned by this computational lesson.

Link life history to curves without making a rigid rule

Greater investment in fewer offspring and longer lifetimes often accompany Type I or sometimes Type II survivorship; many small offspring with high early mortality often accompany Type III. These are tendencies associated with K-like and r-like strategies, not definitions that substitute for a cohort record. In an original equal-interval packet, 100→90→81 survivors gives the same 10% conditional mortality in each interval, consistent with Type II over those intervals. Change the record to 100→10→9: the first interval loses 90%, then the next loses 10%, consistent with stronger early loss. Predicting a full lifetime curve still requires more ages; parental care alone cannot identify the curve.

Source and evidence boundaries

Original explanations and synthetic calculations aligned with AP Environmental Science topics 3.3. Official sources checked 30 October 2026: course topic map and Fall 2026 clarifications, including the distinction between natural increase and migration. These are bounded virtual practice cases, not measured populations, independent assessment or supervised laboratory credit.

Exact-clause reconciliation checked 31 October 2026 against the official framework with Fall 2026 corrections. Added records are fictional, with explicit conditional interpretations.