A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival
Abstract Variation in habitat quality affects individual fitness through the accumulation of benefits and costs over time. Although an individual's fitness and susceptibility to mortality are consequences of these past experiences, current analytical models do not quantify the cumulative effect...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Methods in Ecology and Evolution |
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| Online Access: | https://doi.org/10.1111/2041-210X.70054 |
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| author | Anna K. Moeller Molly C. McDevitt Andrew J. Lindbloom Winsor Lowe Paul M. Lukacs |
| author_facet | Anna K. Moeller Molly C. McDevitt Andrew J. Lindbloom Winsor Lowe Paul M. Lukacs |
| author_sort | Anna K. Moeller |
| collection | DOAJ |
| description | Abstract Variation in habitat quality affects individual fitness through the accumulation of benefits and costs over time. Although an individual's fitness and susceptibility to mortality are consequences of these past experiences, current analytical models do not quantify the cumulative effects of resources, risks, and environmental conditions on survival. We developed the Survival and Habitat Quality model (SHQ), which redefines survival as a cumulative process and measures habitat quality by its aggregate effect on survival through time. SHQ is an autoregressive time‐series model that uses fine‐scale tracking data, remotely sensed environmental data, and computational power to quantify the cumulative effects of spatial variation in habitat quality on survival without relying on subjective, user‐defined lag effects. We tested SHQ on simulated data and on pronghorn data in South Dakota, USA. Compared to a traditional survival model, SHQ was more precise and accurate at estimating cumulative effects of habitat on survival. Using model output, we were also able to generate maps predicting areas of high and low pronghorn survival. SHQ is a conceptual and methodological advance that explicitly integrates individuals' day‐to‐day interactions with their surroundings to identify ultimate sources of mortality. The model is a novel and accurate tool for assessing habitat quality and identifying management actions that increase individual survival and population growth. More broadly, SHQ's flexible mathematical framework captures the full spatial and temporal scope of processes affecting survival, providing a powerful means for understanding the environmental basis of fitness. |
| format | Article |
| id | doaj-art-e3cef45673854f4e9e4f3ee03c1322d4 |
| institution | OA Journals |
| issn | 2041-210X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Methods in Ecology and Evolution |
| spelling | doaj-art-e3cef45673854f4e9e4f3ee03c1322d42025-08-20T02:36:16ZengWileyMethods in Ecology and Evolution2041-210X2025-06-011661173118510.1111/2041-210X.70054A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survivalAnna K. Moeller0Molly C. McDevitt1Andrew J. Lindbloom2Winsor Lowe3Paul M. Lukacs4Department of Natural Resource Ecology and Management Oklahoma State University Stillwater Oklahoma USAWildlife Biology Program University of Montana Missoula Montana USASouth Dakota Game, Fish & Parks Rapid City South Dakota USAWildlife Biology Program University of Montana Missoula Montana USAWildlife Biology Program University of Montana Missoula Montana USAAbstract Variation in habitat quality affects individual fitness through the accumulation of benefits and costs over time. Although an individual's fitness and susceptibility to mortality are consequences of these past experiences, current analytical models do not quantify the cumulative effects of resources, risks, and environmental conditions on survival. We developed the Survival and Habitat Quality model (SHQ), which redefines survival as a cumulative process and measures habitat quality by its aggregate effect on survival through time. SHQ is an autoregressive time‐series model that uses fine‐scale tracking data, remotely sensed environmental data, and computational power to quantify the cumulative effects of spatial variation in habitat quality on survival without relying on subjective, user‐defined lag effects. We tested SHQ on simulated data and on pronghorn data in South Dakota, USA. Compared to a traditional survival model, SHQ was more precise and accurate at estimating cumulative effects of habitat on survival. Using model output, we were also able to generate maps predicting areas of high and low pronghorn survival. SHQ is a conceptual and methodological advance that explicitly integrates individuals' day‐to‐day interactions with their surroundings to identify ultimate sources of mortality. The model is a novel and accurate tool for assessing habitat quality and identifying management actions that increase individual survival and population growth. More broadly, SHQ's flexible mathematical framework captures the full spatial and temporal scope of processes affecting survival, providing a powerful means for understanding the environmental basis of fitness.https://doi.org/10.1111/2041-210X.70054cumulative effectshabitat qualityincremental effectssurvival analysistime seriestime‐dependent covariates |
| spellingShingle | Anna K. Moeller Molly C. McDevitt Andrew J. Lindbloom Winsor Lowe Paul M. Lukacs A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival Methods in Ecology and Evolution cumulative effects habitat quality incremental effects survival analysis time series time‐dependent covariates |
| title | A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival |
| title_full | A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival |
| title_fullStr | A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival |
| title_full_unstemmed | A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival |
| title_short | A lifetime of experiences: Modelling habitat quality through cumulative effects on individual survival |
| title_sort | lifetime of experiences modelling habitat quality through cumulative effects on individual survival |
| topic | cumulative effects habitat quality incremental effects survival analysis time series time‐dependent covariates |
| url | https://doi.org/10.1111/2041-210X.70054 |
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