Fine-scale temporal and spatial population fluctuations of medium sized carnivores in a Mediterranean agricultural matrix

Shamon, Hila; Saltz, David; Dayan, Tamar

doi:10.1007/s10980-017-0517-8

Cited by 19 publications

(19 citation statements)

References 55 publications

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“…Apart from habitat destruction and fragmentation, predation by carnivores-mainly wolves, but also jackals and straying dogs-is considered the major reason for the decline of gazelle populations in Israel (Gingold et al 2009; Yom-Tov 1 3 2013). This applies likewise to the G. gazella populations in northern Israel and the Golan Heights (Reichmann and Saltz 2005;Gingold et al 2009;Manor and Saltz 2004;Geffen et al 1999;Shamoon et al 2017), to the G. dorcas population in the Negev Desert and the Arava Valley (Shalmon 1986;Margolis et al 2008;Barocas et al 2018), but alsoas our study has shown-to the G. arabica population. Canine predators in Israel have noticeably increased in recent decades (Gingold et al 2009;Borkowski et al 2011;Talmon 2015), mainly due to foraging on human discard, unharvested or dropped agricultural products and undisposed carcasses of domestic livestock (Shalmon 1986;Reichmann and Saltz 2005;Margolis et al 2008;Gingold et al 2009;Talmon 2015;Barocas et al 2018), leading to an increased predation on their natural prey species.…”

Section: Fawn Survivalsupporting

confidence: 72%

Factors driving Arabian gazelles (Gazella arabica) in Israel to extinction: time series analysis of population size and juvenile survival in an unexploited population

Shalmon¹,

Sun

Wronski

2019

Biodivers Conserv

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Wild populations of Arabian gazelles (Gazella arabica) were once common on the Arabian Peninsula, but today disappeared from large parts of their former range. In Israel only a small population of currently 30 individuals survived, although it was-and still is-well protected from illegal hunting and habitat destruction. In our study we aimed to identify the factors influencing the population growth of G. arabica in Israel over the last two decades (1995-2017). We tested the impact of five environmental variables including annual mean maximum temperature, rainfall, the availability of two major food plants, competition with sympatric dorcas gazelle (G. dorcas) and predation (mainly by wolves) on two dependent variables relating to population viability (population size, percentage fawn survival) using a retrospective time series analysis. After testing for autocorrelations, two generalized least squares (GLS) models with autocorrelations at 3 and 6 years [GLS-AR(3, 6)] were identified as the best models to explain environmental effects on populations size. Wolf encounter rate had a significant negative effect on G. arabica population size, while G. dorcas population size had a significant positive effect, suggesting that wolf predation shapes the population size of both gazelle species. For percentage fawn survival, model residuals did not reveal any significant autocorrelation and the best fit GLS-AR(0) model retained only wolf encounter rate and mean annual maximal temperature as significant predictors. This result suggests a strong impact of wolf predation and increasing temperatures on the fawn survival of Arabian gazelles. Changed rainfall patterns, food availability and competition between gazelle species had no impact on fawn survival.

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Section: Fawn Survivalsupporting

confidence: 72%

Factors driving Arabian gazelles (Gazella arabica) in Israel to extinction: time series analysis of population size and juvenile survival in an unexploited population

Shalmon¹,

Sun

Wronski

2019

Biodivers Conserv

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“…N‐mixture models can be used to estimate spatial activity distribution (Shamoon et al. ) of unmarked individuals while accounting for imperfect detection (Royle ). N‐mixture models are a family of hierarchical models that use a two‐step approach to model a given species density.…”

Section: Methodsmentioning

confidence: 99%

“…We used the N‐mixture model to assess various explanatory variables for the camera trap data (see below), including the SEM's prediction of the deer distribution at the 20th year (termed here Deer_20 yr) using a generalized linear regression (Shamoon et al. ). We assessed and ranked the various models based on different combinations of the explanatory variables using multi‐model inferencing and Akaike's information criterion (AIC).…”

Section: Methodsmentioning

confidence: 99%

“…The effects of each predictor were quantified by proportional cumulative effect of the distance of each predictor pixel (25 × 25 m) within a buffer of 500 m (representing daily movement of the species) around each camera trap site measured by an exponential decay function (Shamoon et al. ). The result is a relative measurement of land‐cover‐type distance and proportion around each camera trap site.…”

Section: Methodsmentioning

confidence: 99%

“…The result would be higher with proximity of the sampled site to a predictor and increasing area of the predictor (Shamoon et al. ).…”

Section: Methodsmentioning

confidence: 99%

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Long‐term reevaluation of spatially explicit models as a means for adaptive wildlife management

Cohen

Shamon

Dolev

et al. 2020

Ecological Applications

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2020. Longterm reevaluation of spatially explicit models as a means for adaptive wildlife management. Ecological Applications 30(4):Abstract. We evaluated a 20-yr-old spatially explicit model (SEM) that predicted the spatial expansion of reintroduced Persian fallow deer in northern Israel. Using the current distribution of the deer and based on multi-model inference we assessed the accuracy of the SEM's prediction and what other factors affected the population's current distribution. If the SEM's projection was still valid, the leading model in the multi-model inference would include only the SEM's projection as an explanatory variable with a good fit. Different leading models would reveal key variables overlooked when the SEM was constructed or changes in the landscape unforeseen at the time, thus assisting adaptive management and decisionmaking. We assessed deer presence from camera trap encounter counts analyzed using Nmixture models. Models included various combinations of seven predictors: the 20-yr predictions of an SEM developed during the initial phases of the reintroduction, three key landscape characteristics on which the SEM was originally based but updated to reflect current conditions, distance from the release site, elevation, and the distribution of gray wolves (a predator that was absent from the area when the SEM was developed). Competing models were ranked by Akaike information criterion (AIC). Wolf distribution was the key predictor explaining the current deer distribution, appearing in all three leading models (ΔAIC < 2.0) and carrying 71% of the AIC weight (coefficient = À14.86 AE 5.6 [mean AE SE]). Of these three models, the SEM 20-yr prediction appeared in two, but explained only a fraction of the variance (coefficient = 0.001 AE 0.08). The contribution of all other predictors was negligible. While the SEM failed to accurately predict the 20-yr deer distribution, the divergence between its projection and reality pointed to the probable cause (wolves) of this discrepancy. The inclusion of the SEM prediction in the leading models indicates that had the wolves not spread to the study area, the predictions would still have merit suggesting that long-term SEMs can potentially be robust. Long-term reevaluation of SEMs can be beneficial even if model projections fail, as the process can uncover the specific factors driving this failure, supporting adaptive management procedures.

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Environmental filtering drives the assembly of mammal communities in a heterogeneous Mediterranean region

Suárez-Tangil

Rodrı́guez

2023

Ecological Applications

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Agricultural expansion and intensification are major drivers of global change. Quantifying the importance of different processes governing the assembly of local communities in agroecosystems is essential to guide the conservation effort allocated to enhancing habitat connectivity, improving habitat quality or managing species interactions. We used multiple detection methods to record the occurrence of medium‐sized and large‐sized mammals in three managed landscapes of a heterogeneous Mediterranean region. Then we used a joint species distribution model to evaluate the relative influence of dispersal limitation, environmental filtering, and interspecific interactions on the local assembly of mammal communities in 4‐km2 plots. The partitioning of the explained variation in species occurrence was attributed on average 99% to environmental filters and 1% to dispersal filters. No role was attributed to biotic filters, in agreement with the scarce support for strong competition or other negative interactions found after a literature review. Four principal environmental factors explained on average 63% of variance in species occurrence and operated mainly at the landscape scale. The amount of shrub cover in the neighboring landscape was the most influential factor favoring mammal occurrence and accounted for nearly one‐third of the total variance. The proportion of intensively managed croplands and proxies of human activity within landscape samples limited mammal presence. At the microhabitat scale (~80 m2 plots) the mean percentage area deprived of woody vegetation also had a negative effect. Functional traits such as body mass or social behavior accounted for a substantial fraction of the variation attributed to environmental factors. We concluded that multiscale environmental filtering governed local community assembly, whereas the role of dispersal limitation and interspecific interactions was negligible. Our results suggest that further removal of shrubland, the expansion of intensive agriculture, and the increase of human activity are expected to result in species losses. The fact that community integrity responds to a single type of ecological process simplifies practical recommendations. Management strategies should focus on the conservation and restoration of shrubland, adopting alternatives to intensive schemes of agricultural production, and minimizing recreational and other human activities in remnant natural habitats within agroecosystems or mosaic landscapes.

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Fine-scale temporal and spatial population fluctuations of medium sized carnivores in a Mediterranean agricultural matrix

Cited by 19 publications

References 55 publications

Factors driving Arabian gazelles (Gazella arabica) in Israel to extinction: time series analysis of population size and juvenile survival in an unexploited population

Factors driving Arabian gazelles (Gazella arabica) in Israel to extinction: time series analysis of population size and juvenile survival in an unexploited population

Long‐term reevaluation of spatially explicit models as a means for adaptive wildlife management

Environmental filtering drives the assembly of mammal communities in a heterogeneous Mediterranean region

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