Wildlife management aims and ecological processes: A case study of kangaroos

Boyle, Maria; Hone, Jim

doi:10.1002/wsb.429

Cited by 8 publications

(9 citation statements)

References 40 publications

(87 reference statements)

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“…Although SOI was commonly included in the best‐fitting models, its influence on population abundance was weak and variable, a result corroborated by other studies (e.g. Boyle & Hone 2014). Even though lagged rainfall was commonly included in the group of models with substantial support, its effect was only weakly positive on many kangaroo subpopulations.…”

Section: Discussionsupporting

confidence: 79%

“…1984; Bayliss 1985; Jonzén et al . 2005; Boyle & Hone 2014). Accumulated monthly rainfall data were obtained from the SILO spatially interpolated daily rainfall datasets (gridded datasets) at a resolution of 0.05° latitude by 0.05° longitude (approximately 5 × 5 km) (Queensland Government 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Sustained positive values of the SOI (greater than +7) are characteristic of a La Nina episode, and associated with higher than average rainfall in eastern and northern Australia (Bureau of Meteorology 2020). Boyle and Hone (2014) suggested that SOI was positively correlated with the rate of increase of Western Grey Kangaroo but the effect was weak. SOI was averaged over 12 months prior to each survey, lagged by three months.…”

Section: Methodsmentioning

confidence: 99%

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Assessing the spatial and temporal organization of Red Kangaroo, Western Grey Kangaroo and Eastern Grey Kangaroo populations in eastern Australia using multivariate autoregressive state‐space models

McLeod¹,

Finch²,

Wallace³

et al. 2021

Eco Management Restoration

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SummaryTo identify patterns in the temporal dynamics and spatial organization of kangaroo subpopulations that are commercially harvested, we fitted multivariate autoregressive state‐space (MARSS) models to time series of kangaroo abundance from the main harvest zones of eastern Australia (1990–2019 for New South Wales and 1984–2019 for Queensland). We found that the responses of most populations to process variation, that is variation due to environmental or demographic stochasticity were correlated and that populations responded synchronously to environmental changes. Furthermore, we examined the influence of the covariates lagged rainfall, Southern Oscillation Index (SOI) and harvest rate on kangaroo abundance. We found that lagged rainfall had a positive influence, SOI and harvest rate had negative influences but the influence of covariates was not consistent across species or between subpopulations. In terms of population spatial structure, the analysis identified two subpopulations of Red Kangaroo (Osphranter rufus) in New South Wales and four subpopulations of grey kangaroos (a combination of Eastern Grey Kangaroo (Macropus giganteus) and Western Grey Kangaroo (Macropus fuliginosus)), which appeared to be associated with a rainfall gradient from east‐west. In Queensland, separate subpopulations were identified in each of the three main harvest management zones for both Red Kangaroo and Eastern Grey Kangaroo. The implications of these results for the management of commercially harvested kangaroos are discussed.

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Section: Discussionsupporting

confidence: 79%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Assessing the spatial and temporal organization of Red Kangaroo, Western Grey Kangaroo and Eastern Grey Kangaroo populations in eastern Australia using multivariate autoregressive state‐space models

McLeod¹,

Finch²,

Wallace³

et al. 2021

Eco Management Restoration

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“…This is a simplification of reality as studies have shown annual variation in reproductive output (Santos et al, 2006;Holland et al, 2009) and seasonality (Santos et al, 2006;Canu et al, 2015) due to resource availability. Resource-based changes in per-individual reproductive output would introduce additional variation in reproductive output across years, which would increase the uncertainty in our quantitative predictions (Boyle and Hone, 2014) but should not affect the relative effects of different treatments. Similarly, we did not account for potential effects of density-dependent reproduction, which could decrease our predicted rates of population decline (i.e., efficiency; Melero et al, 2015).…”

Section: When To Cullmentioning

confidence: 99%

Efficiency of different spatial and temporal strategies for reducing vertebrate pest populations

Pepin

Davis

VerCauteren

2017

Ecological Modelling

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Understanding effectiveness of control strategies of pest species is fundamental for planning efficient and cost-effective management programs. In addition to culling rates, there are many potential factors that can determine efficiency of different management strategies, including demographic processes such as immigration rates, birth dynamics, and spatial ecology. We developed a stochastic, data-based simulation model of feral swine population dynamics which accounted for social dynamics in space. We tested the impacts of different spatio-temporal management strategies (i.e., culling rates, timing of culling during the year, spatial pattern of culling and strength of a barrier to immigration) on population response and efficiency. The spatial culling strategy dramatically impacted efficiency of control-using zonation required removal of fewer pigs (up to 46% less) to achieve similar reductions compared with other spatial strategies. Also, our spatially-explicit model predicted that lower culling intensities could be used to achieve population reductions when zonation was applied relative to predictions from harvesting theory based on simple logistic models. As culling intensity increased (≥50% of target population annually) and the target population reached low density (<5% of original density), effects of spatial strategy became less pronounced relative to immigration barrier effects. Lastly, for the same level of moderate culling effort, prioritization of culling during the low-birthing period generally resulted in faster population reduction to near zero abundance relative to prioritization during the high-birthing period, or spreading the work over a year period, but the significance of this effect depended on the spatial culling strategy and culling intensity. Our results imply that continually updating knowledge of current abundance during management may not only be important for determining culling quotas, but also for updating and optimizing management strategies. When the management goal is maximum population control, consideration of birth and spatial dynamics can increase return on management effort and bring to light management inefficiencies.

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“…In addition, despite considerable research effort devoted to understanding the ecology of kangaroos (e.g. Dawson 2012), and on-going monitoring of rangeland kangaroo populations (Industry and Development Assessment 2017; Natural Resources South Australia Arid Lands 2017; Office of Environment and Heritage 2017a; Department of Biodiversity, Conservation and Attractions 2019), there remain important sources of uncertainty surrounding the response of populations to management actions, for example the relative importance of compensatory versus additive mortality during phases of population increase and decrease (Boyle and Hone 2014), the impact of non-sex-biased culling on population viability (Shelly 1997) and the impacts of attempting to maintain populations above or below agreed thresholds (Chee and Wintle 2010).…”

Section: An Active Adaptive Management Framework For Kangaroosmentioning

confidence: 99%

Balancing stakeholder interests in kangaroo management – historical perspectives and future prospects

McLeod

Hacker

2019

Rangel. J.

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Kangaroos are commercially harvested in five mainland states of Australia, with the harvest regulated by state government wildlife management agencies and overseen by the Commonwealth government. Non-commercial culling is permitted, and although most kangaroos have traditionally been taken by the commercial kangaroo harvesting industry, the proportion taken non-commercially has increased in recent years. Management plans that guide the regulation of the harvest support the management objectives of wildlife management agencies and the kangaroo industry, but the plans do not successfully address the objectives of other stakeholders including pastoralists and animal protection groups, which focus on minimising the grazing impacts of kangaroos and animal welfare issues respectively. We reviewed the objectives outlined in the management plans for kangaroos in the Australian rangelands and examined alternative systems for managing natural resources to identify if improvements to management could be made. Current management plans for kangaroos principally use fixed harvest rates that are responsive only to the state of the kangaroo population and not to changes in the environments in which kangaroos live. This type of management is reactive, and opportunities for improving management of the environment are limited. A viable alternative is active adaptive management which focuses on explicit measurement of the response of the natural system to management actions and use of this information to modify interventions to better meet management objectives. Active adaptive management is appropriate when management actions can strongly influence system state but the impacts of management are uncertain. We argue that the management of kangaroos and the environments in which they live would benefit from the adoption of an active adaptive management approach by wildlife management agencies.

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Wildlife management aims and ecological processes: A case study of kangaroos

Cited by 8 publications

References 40 publications

Assessing the spatial and temporal organization of Red Kangaroo, Western Grey Kangaroo and Eastern Grey Kangaroo populations in eastern Australia using multivariate autoregressive state‐space models

Assessing the spatial and temporal organization of Red Kangaroo, Western Grey Kangaroo and Eastern Grey Kangaroo populations in eastern Australia using multivariate autoregressive state‐space models

Efficiency of different spatial and temporal strategies for reducing vertebrate pest populations

Balancing stakeholder interests in kangaroo management – historical perspectives and future prospects

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