Drivers of periodicity in population dynamic models of long-lived, large mammals

TL;DR

This study develops a synthetic model to understand long-term population cycles in large mammals, highlighting the role of cohort effects and density dependence in driving oscillations, with implications for conservation and management.

Contribution

The paper introduces a novel modeling framework that links cohort effects and density dependence to population cycles in long-lived mammals, expanding understanding beyond short-lived species.

Findings

Cohort effects, especially on survival, can cause long-period oscillations.

Population cycles are influenced by both endogenous factors and environmental stochasticity.

The model is applicable to other large, long-lived species with complex demography.

Abstract

Population cycles are important components of many natural systems. Most studied in short-lived and small-bodied species, cycles frequently appear to be driven by density-dependent feedbacks. However, compelling evidence of cycles -- often more qualitative than quantitative -- also exists in large mammals. Among ungulates, both density-dependent vital rates and 'cohort effects' (lasting impacts of birth conditions on fecundity and survival) exist, but the implications of such feedbacks for oscillatory population dynamics have not been explored. Here, we present a synthetic model of ungulate population dynamics, parameterized for barren-ground caribou (Rangifer tarandus groenlandicus) and motivated by extensive Indigenous knowledge suggesting decades-long fluctuations in abundance. Caribou herds are theorized to be subject to both cohort effects and density dependence, and we linked these endogenous factors with environmental stochasticity to understand cycling. Using wavelet analysis, we characterized periodic phenomena and performed sensitivity analyses to clarify the drivers and characteristics of population cycles. We found that cohort effects, predominantly those impacting survival, can produce long-period oscillatory behavior across a wide range of environments and demographic structures. Our modeling framework is generalizable to other long-lived, large-bodied species with complex demography, and collectively, these efforts broaden the scope of inquiry into proximal drivers of population cycling.