Carrying capacity of a spatially-structured population: Disentangling the effects of dispersal, growth parameters, habitat heterogeneity and habitat clustering

James Van Dyken, Bo Zhang

Research output: Contribution to journalArticle

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.

LanguageEnglish (US)
Pages115-124
Number of pages10
JournalJournal of theoretical biology
Volume460
DOIs
StatePublished - Jan 7 2019

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spatiotemporal analysis
metapopulation
habitat quality
carrying capacity
cluster analysis
connectivity
biomass
habitat
population growth
conservation management
effect
parameter
logistics
spatial distribution

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

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title = "Carrying capacity of a spatially-structured population: Disentangling the effects of dispersal, growth parameters, habitat heterogeneity and habitat clustering",
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.",
keywords = "Biomass yield, Connectivity, Dispersal, Environmental heterogeneity, Metapopulation, Patchy habitat, SLOSS",
author = "{Van Dyken}, James and Bo Zhang",
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AU - Zhang, Bo

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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

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KW - Dispersal

KW - Environmental heterogeneity

KW - Metapopulation

KW - Patchy habitat

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