Spatial heterogeneity in the carrying capacity of sika deer in Japan

Iijima, Hayato; Ueno, Mayumi

doi:10.1093/jmammal/gyw001

Cited by 41 publications

(28 citation statements)

References 48 publications

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“…Nonetheless, both among-and within-population variation can influence fluctuations in abundance around K. Therefore, an examination of the effect of variation in K both within and among populations on fluctuations in abundance around K is necessary. Furthermore, population growth parameters are often estimated over a substantial part of a species' geographic range 18,22,23 , where environmental heterogeneity tends to be large, and so is variation in K. Two studies, however, indicate considerable variation in K within a small part of a species' geographic range 7,24 , so variation in β and process variance at this spatial scale seems plausible. Thus, an examination of population dynamics within and among populations in r and K over a smaller part of the geographic range of a species is warranted.…”

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confidence: 99%

Elk population dynamics when carrying capacities vary within and among herds

Koetke

Duarte

Weckerly

2020

Sci Rep

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Population and land management relies on understanding population regulation and growth, which may be impacted by variation in population growth parameters within and among populations. We explored the interactions between variation in carrying capacity (K), intrinsic population growth rate (r), and strength of density dependence (β) within and among elk (Cervus elaphus) herds in a small part of the geographic range of the species. We also estimated stochastic fluctuations in abundance around K for each herd. We fit linear Ricker growth models using Bayesian statistics to seven time series of elk population survey data. Our results indicate that K and β varied among herds, and that r and β varied temporally within herds. We also found that herds with smaller K had less stochastic fluctuation in abundances around K, but higher temporal variation in β within herds. Population regulation and the rate of return to the equilibrium abundance is often understood in terms of β, but ecological populations are dynamic systems, and temporal variation in population growth parameters may also influence regulation. Population models which accommodate variation both within and among herds in population growth parameters are necessary, even in mild climates, to fully understand population dynamics and manage populations.

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confidence: 99%

Elk population dynamics when carrying capacities vary within and among herds

Koetke

Duarte

Weckerly

2020

Sci Rep

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“…As populations exist on landscapes with heterogeneous resources within which they disperse (e.g., Iijima and Ueno [44], Sirén [45]), these mathematical predictions are important to determine which distribution of resource could support a larger metapopulation abundance. Despite these implications, these results were not tested empirically until recently.…”

Section: Empirical Testing Of Mathematical Resultsmentioning

confidence: 99%

Carrying Capacity of Spatially Distributed Metapopulations

Zhang

Jiang

2021

Trends in Ecology & Evolution

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Carrying capacity is a key concept in ecology. A body of theory, based on the logistic equation, has extended predictions of carrying capacity to spatially distributed, dispersing populations. However, this theory has only recently been tested empirically. The experimental results disagree with some theoretical predictions of when they are extended to a population dispersing randomly in a twopatch system. However, they are consistent with a mechanistic model of consumption on an exploitable resource (consumer-resource model). We argue that carrying capacity, defined as the total equilibrium population, is not a fundamental property of ecological systems, at least in the context of spatial heterogeneity. Instead, it is an emergent property that depends on the population's intrinsic growth and dispersal rates. A Brief History of Carrying Capacitya Fundamental but Confusing Concept Carrying capacity (commonly defined as the upper limit on the size of the population), has been one of the most important concepts in ecology for the last century. As such, it has been broadly used, from cell populations up to that of ecological communities at landscape and ecosystem levels [1,2]. Wildlife biologists introduced the term in the early 20th century as a tool in wildlife management. Aldo Leopold viewed carrying capacity as the population density reached at a particular site, determined by both the resources available and intraspecific competition [3]. Although, in Leopold's view, the realized carrying capacity was usually less than the maximum population density reached under optimum conditions. He called this the saturation pointthe maximum density that could be achieved by careful habitat manipulation. Leopold's definition was by no means the only one held among ecologists. For instance, Paul Errington viewed carrying capacity as the maximum size that a population could reach if there was refuge from predation available. Dhondt [4] documented the use of both Leopold's and Errington's definitions by other wildlife biologists and ecologists, noting, for example, that Dasmann [5] carried distinctions further by introducing four different definitions related to carrying capacity: subsistence density, optimum density, security density, and tolerance density. Dhondt [4] reviewed the multiplicity of views of carrying capacity and called it confusing, concluding that, at least for wildlife biology, the term should be avoided. However, carrying capacity had already entered the mainstream of ecology. Odum [6] took the first step of giving carrying capacity a formal mathematical meaning. He defined it as the constant K in the Pearl-Verhulst form of the logistic population equation: dN dt ¼ r 1− N K N ½1 where N is population size and r is the intrinsic population growth rate. This equation defines the carrying capacity as the equilibrium point that a population would always approach from lesser or

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“…We did not include a density-dependence parameter in the population growth rate. The density dependence in population growth of sika deer within only 25.3 km 2 in open ecosystem (4,465 km 2 ) was found [27]. However, it was largely depended on the habitat environment.…”

Section: State-space Modelmentioning

confidence: 89%

Seasonal and annual fluctuations of deer populations estimated by a Bayesian state–space model

et al. 2020

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Deer overabundance is a contributing factor in the degradation of plant communities and ecosystems worldwide. The management and conservation of the deer-affected ecosystems requires us to urgently grasp deer population trends and to identify the factors that affect them. In this study, we developed a Bayesian state-space model to estimate the population dynamics of sika deer (Cervus nippon) in a cool-temperate forest in Japan, where wolves (Canis lupus hodophilax) are extinct. The model was based on field data collected from block count surveys, road count surveys by vehicles, mortality surveys during the winter, and nuisance control for 12 years (2007-2018). We clarified the seasonal and annual fluctuation of the deer population. We found a peak of deer abundance (2010) over 12 years. In 2011 the estimated deer abundance decreased drastically and has remained at a low level then. The deer abundance gradually increased from April to December during 2013-2018. The seasonal fluctuation we detected could reflect the seasonal migration pattern of deer and the population recruitment through fawn births in early summer. In our model, snowfall accumulation, which can be a lethal factor for deer, may have slightly affected their mortality during the winter. Although we could not detect a direct effect of snow on population dynamics, snowfall decrease due to global warming may decelerate the winter migration of deer; subsequently, deer staying on-site may intensively forage evergreen perennial plants during the winter season. The nuisance control affected population dynamics. Even in wildlife protection areas and national parks where hunting is regulated, nuisance control could be effective in buffering the effect of deer browsing on forest ecosystems.

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Spatial heterogeneity in the carrying capacity of sika deer in Japan

Cited by 41 publications

References 48 publications

Elk population dynamics when carrying capacities vary within and among herds

Elk population dynamics when carrying capacities vary within and among herds

Carrying Capacity of Spatially Distributed Metapopulations

Seasonal and annual fluctuations of deer populations estimated by a Bayesian state–space model

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