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Abstract Juvenile survival is critical to population persistence and evolutionary change. However, the survival of juvenile plants from emergence to reproductive maturity is rarely quantified. This is especially true for long‐lived perennials with extended pre‐reproductive periods. Furthermore, studies rarely have the replication necessary to account for variation among populations and cohorts. We estimated juvenile survival and its relationship to population size, density of conspecifics, distance to the maternal plant, age, year, and cohort forEchinacea angustifolia, a long‐lived herbaceous perennial. In 14 remnant prairie populations over seven sampling years, 2007–2013, we identified 886 seedlings. We then monitored these individuals annually until 2021 (8–15 years). Overall, juvenile mortality was very high; for almost all cohorts fewer than 10% of seedlings survived to age 8 or to year 2021. Only two of the seedlings reached reproductive maturity within the study period. Juvenile survival increased with distance from the maternal plant and varied more among the study years than it did by age or cohort. Juvenile survival did not vary with population size or local density of conspecific neighbors. Our results suggest that low juvenile survival could contribute to projected population declines.
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This content will become publicly available on February 1, 2026
Improving population analysis using indirect count data: A case study of chimpanzees and elephants
Abstract Estimating spatiotemporal patterns of population density is a primary objective of wildlife monitoring programs. However, estimating density is challenging for species that are elusive and/or occur in habitats with limited visibility. In such situations, indirect measures (e.g., nests, dung) can serve as proxies for counts of individuals. Scientists have developed approaches to estimate population density using these “indirect count” data, although current methods do not adequately account for variation in sign production and spatial patterns of animal density. In this study, we describe a modified hierarchical distance sampling model that maximizes the information content of indirect count data using Bayesian inference. We apply our model to assess the status of chimpanzee and elephant populations using counts of nests and dung, respectively, which were collected along transects in 2007 and 2021 in western Uganda. Compared with conventional methods, our modeling framework produced more precise estimates of covariate effects on expected animal density by accounting for both long‐term and recent variations in animal abundance and enabled the estimation of the number of days that animal signs remained visible. We estimated a 0.98 probability that chimpanzee density in the region had declined by at least 10% and a 0.99 probability that elephant density had increased by 50% from 2007 to 2021. We recommend applying our modified hierarchical distance sampling model in the analysis of indirect count data to account for spatial variation in animal density, assess population change between survey periods, estimate the decay rate of animal signs, and obtain more precise density estimates than achievable with traditional methods.
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- Award ID(s):
- 1954406
- PAR ID:
- 10595941
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 16
- Issue:
- 2
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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