Abstract
Carrying capacity, K, is a fundamental quantity in theoretical and applied ecology. When populations are distributed over space, carrying capacity becomes a complicated function of local, global and nearby environments, dispersal rate, and the relationship between population growth parameters, e.g., r and K. Expressions for the total carrying capacity, Ktotal, in an n-patch model that explicitly disentangle all of these factors are currently lacking. Therefore, here we derive Ktotal for a linear spatial array of n habitat patches with logistic growth and strong or weak random dispersal of individuals between adjacent patches. With strong dispersal, Ktotal depends on the mean r and K over all patches (〈r〉 and 〈K〉), the among-patch variance in K, and the linear regression coefficient of r on K, βr,K. Strong dispersal increases Ktotal only if βr, K > 〈r〉/〈K〉 which requires a positive convex or negative concave association between r and K, and decreases Ktotal if βr, K < 〈r〉/〈K〉. Alternatively, weak dispersal increases Ktotal only if the within-patch covariance of r and K, cov(r, K) is greater than the spatial covariance between r and K, cov(r, Km), defined as the average covariance between r in a focal patch and K in neighboring patches. Unlike the strong dispersal limit, this condition depends not only on the magnitude of environmental heterogeneity, but explicitly on the spatial distribution of heterogeneity (i.e., habitat clustering). This work clarifies how the interaction between dispersal, habitat heterogeneity, and population growth parameters shape carrying capacity in spatial populations, with implications for species management, conservation and evolution.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 115-124 |
| Number of pages | 10 |
| Journal | Journal of Theoretical Biology |
| Volume | 460 |
| DOIs | |
| State | Published - Jan 7 2019 |
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Keywords
- Biomass yield
- Connectivity
- Dispersal
- Environmental heterogeneity
- Metapopulation
- Patchy habitat
- SLOSS
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics
Cite this
Carrying capacity of a spatially-structured population : Disentangling the effects of dispersal, growth parameters, habitat heterogeneity and habitat clustering. / Van Dyken, James; Zhang, Bo.
In: Journal of Theoretical Biology, Vol. 460, 07.01.2019, p. 115-124.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Carrying capacity of a spatially-structured population
T2 - Disentangling the effects of dispersal, growth parameters, habitat heterogeneity and habitat clustering
AU - Van Dyken, James
AU - Zhang, Bo
PY - 2019/1/7
Y1 - 2019/1/7
N2 - Carrying capacity, K, is a fundamental quantity in theoretical and applied ecology. When populations are distributed over space, carrying capacity becomes a complicated function of local, global and nearby environments, dispersal rate, and the relationship between population growth parameters, e.g., r and K. Expressions for the total carrying capacity, Ktotal, in an n-patch model that explicitly disentangle all of these factors are currently lacking. Therefore, here we derive Ktotal for a linear spatial array of n habitat patches with logistic growth and strong or weak random dispersal of individuals between adjacent patches. With strong dispersal, Ktotal depends on the mean r and K over all patches (〈r〉 and 〈K〉), the among-patch variance in K, and the linear regression coefficient of r on K, βr,K. Strong dispersal increases Ktotal only if βr, K > 〈r〉/〈K〉 which requires a positive convex or negative concave association between r and K, and decreases Ktotal if βr, K < 〈r〉/〈K〉. Alternatively, weak dispersal increases Ktotal only if the within-patch covariance of r and K, cov(r, K) is greater than the spatial covariance between r and K, cov(r, Km), defined as the average covariance between r in a focal patch and K in neighboring patches. Unlike the strong dispersal limit, this condition depends not only on the magnitude of environmental heterogeneity, but explicitly on the spatial distribution of heterogeneity (i.e., habitat clustering). This work clarifies how the interaction between dispersal, habitat heterogeneity, and population growth parameters shape carrying capacity in spatial populations, with implications for species management, conservation and evolution.
AB - Carrying capacity, K, is a fundamental quantity in theoretical and applied ecology. When populations are distributed over space, carrying capacity becomes a complicated function of local, global and nearby environments, dispersal rate, and the relationship between population growth parameters, e.g., r and K. Expressions for the total carrying capacity, Ktotal, in an n-patch model that explicitly disentangle all of these factors are currently lacking. Therefore, here we derive Ktotal for a linear spatial array of n habitat patches with logistic growth and strong or weak random dispersal of individuals between adjacent patches. With strong dispersal, Ktotal depends on the mean r and K over all patches (〈r〉 and 〈K〉), the among-patch variance in K, and the linear regression coefficient of r on K, βr,K. Strong dispersal increases Ktotal only if βr, K > 〈r〉/〈K〉 which requires a positive convex or negative concave association between r and K, and decreases Ktotal if βr, K < 〈r〉/〈K〉. Alternatively, weak dispersal increases Ktotal only if the within-patch covariance of r and K, cov(r, K) is greater than the spatial covariance between r and K, cov(r, Km), defined as the average covariance between r in a focal patch and K in neighboring patches. Unlike the strong dispersal limit, this condition depends not only on the magnitude of environmental heterogeneity, but explicitly on the spatial distribution of heterogeneity (i.e., habitat clustering). This work clarifies how the interaction between dispersal, habitat heterogeneity, and population growth parameters shape carrying capacity in spatial populations, with implications for species management, conservation and evolution.
KW - Biomass yield
KW - Connectivity
KW - Dispersal
KW - Environmental heterogeneity
KW - Metapopulation
KW - Patchy habitat
KW - SLOSS
UR - http://www.scopus.com/inward/record.url?scp=85055040814&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055040814&partnerID=8YFLogxK
U2 - 10.1016/j.jtbi.2018.09.015
DO - 10.1016/j.jtbi.2018.09.015
M3 - Article
VL - 460
SP - 115
EP - 124
JO - Journal of Theoretical Biology
JF - Journal of Theoretical Biology
SN - 0022-5193
ER -