Impact of climate on the population dynamics of an alpine ungulate: a long-term study of the Tatra chamois Rupicapra rupicapra tatrica

Ciach, Michał; Pęksa, Łukasz

doi:10.1007/s00484-018-1619-y

Cited by 12 publications

(12 citation statements)

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“…This suggests that snowfall may have slightly affected deer mortality during the winter in the present study. This is similar to results obtained from studying the alpine ungulate Rupicapra rupicapra [15], though their population dynamics are largely affected by summer temperature. At first glance, our results seem to suggest that the mortality rate during the winter will not change even if snowfall decreases due to global warming.…”

Section: Plos Onesupporting

confidence: 87%

“…Therefore, it is indispensable to estimate the effect of snow on the dynamics of deer populations. While some of the effects of global warming on population dynamics of ungulates have already been reported [14][15][16], models constructed in recent studies to describe deer population dynamics have not yet explicitly considered the effects of snow.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in order to assess the effects of deer browsing on ecosystem levels it is important to, at least, estimate the seasonal deer abundance. However, in many areas, the annual census of ungulates is held during a season that, although offers good visibility to track ungulates, is not suitable for plant growth [10,15,17].…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Plos Onesupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…Annual mean temperature was the second most important variable for Himalayan ibex, and temperature of wettest quarter the second most important for blue sheep. The dry habitats of both ibex and blue sheep have short growing seasons, and any weather fluctuation might leave species starving [75]. Artemisia and Ephedra shrubs are described as the ibex's main food sources [33].…”

Section: Plos Onementioning

confidence: 99%

Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan

Ali

Din²,

Bosso

et al. 2021

PLoS ONE

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Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.

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“…For mountain ungulates living in open areas, such as the ibex Capra ibex or the Alpine chamois Rupicapra rupicapra , ground counts from vantage points or transects are commonly used (Largo et al 2008, Herrero et al 2011). Long‐term data sets based on ground counts have been extensively used to investigate ungulate population dynamics (Jacobson et al 2004, Ciach and Pęksa 2018, Corlatti et al 2019). The main drawback of ground counts is that true population size is underestimated by an unknown quantity (Corlatti et al 2015a).…”

mentioning

confidence: 99%

Population reconstruction as an informative tool for monitoring chamois populations

Reiner

Zedrosser

Zeiler³

et al. 2020

Wildlife Biology

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Knowledge of population trends is of key importance for sustainable management of wildlife and finding reliable and cost–effective monitoring methods is therefore of great interest. In two populations of Alpine chamois Rupicapra rupicapra, we collected data on mortality from 12 424 individuals hunted or found dead and population size data based on ground counts over a period of 28 years. Our study had three aims: 1) we investigated if changes in population size obtained with a simple deterministic population reconstruction (DPR) approach using hunting and natural mortality covary with population size estimates obtained from ground count data. 2) We investigated if the performance of DPR is affected by the removal of natural mortality data. 3) We assessed how many years of mortality data are needed to obtain consistent population trends using DPR. Our results suggested that 1) population abundance from mortality data using DPR significantly and positively correlated with population abundance obtained with ground counts. 2) DPR without natural mortality data performed similarly as compared to DPR using full data (hunting and natural mortality). 3) Consistent estimates of population trends can be obtained with ≥10 years of mortality data, however, this time span was influenced by the mean age at death, which in turn was affected by the local hunting regime. Our results suggest that DPR and ground counts perform similarly for the estimation of temporal trends in Alpine chamois abundance. The consistence of ground counts and DPR supports the use of these methods as reliable tools for tracking abundance of chamois populations over time. However, the reliability of abundance estimates using DPR may vary between populations and the influence of different hunting regimes must be considered for the correct interpretation of results.

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Impact of climate on the population dynamics of an alpine ungulate: a long-term study of the Tatra chamois Rupicapra rupicapra tatrica

Cited by 12 publications

References 56 publications

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

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

Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan

Population reconstruction as an informative tool for monitoring chamois populations

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