Seasonality, local resources and environmental factors influence patterns of brown bear damages: implications for management

Zarzo‐Arias, Alejandra; Delgado, María del Mar; Palazón, Santiago; Jordana, I. Alfonso; Bombieri, Giulia; González-Bernardo, Enrique; Ordiz, Andrés; Bettega, Chiara; García‐González, Ricardo; Penteriani, Vincenzo

doi:10.1111/jzo.12839

Cited by 18 publications

(15 citation statements)

References 58 publications

(84 reference statements)

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“…In particular, our findings show that bear damages occurred throughout the bear-active period and increased from spring to late summer and autumn for all types of farms, but especially for livestock farms. This confirms trends documented by studies in other regions at similar latitudes and in similar ecological settings (e.g., Greece: [ 52 ]; Spain: [ 53 , 54 ]). Specifically, similar to many other European countries [ 8 ], among all types of damages made by bear in the PNALM, livestock depredations were the most frequent and economically impacting (60% of annual compensation costs paid for bear damages).…”

Section: Discussionsupporting

confidence: 90%

Cost of Coexisting with a Relict Large Carnivore Population: Impact of Apennine Brown Bears, 2005–2015

Galluzzi

Donfrancesco

Mastrantonio

et al. 2021

Animals

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Human-carnivore conflicts are a major conservation issue. As bears are expanding their range in Europe’s human-modified landscapes, it is increasingly important to understand, prevent, and address human-bear conflicts and evaluate mitigation strategies in areas of historical coexistence. Based on verified claims, we assessed costs, patterns, and drivers of bear damages in the relict Apennine brown bear population in the Abruzzo Lazio and Molise National Park (PNALM), central Italy. During 2005–2015, 203 ± 71 (SD) damage events were verified annually, equivalent to 75,987 ± 30,038 €/year paid for compensation. Most damages occurred in summer and fall, with livestock depredation, especially sheep and cattle calves, prevailing over other types of damages, with apiaries ranking second in costs of compensation. Transhumant livestock owners were less impacted than residential ones, and farms that adopted prevention measures loaned from the PNALM were less susceptible to bear damages. Livestock farms chronically damaged by bears represented 8 ± 3% of those annually impacted, corresponding to 24 ± 6% of compensation costs. Further improvements in the conflict mitigation policy adopted by the PNALM include integrated prevention, conditional compensation, and participatory processes. We discuss the implications of our study for Human-bear coexistence in broader contexts.

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Section: Discussionsupporting

confidence: 90%

Cost of Coexisting with a Relict Large Carnivore Population: Impact of Apennine Brown Bears, 2005–2015

Galluzzi

Donfrancesco

Mastrantonio

et al. 2021

Animals

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“…Among large carnivores, the brown bear Ursus arctos represents a good model species to study bold behaviour and its association with movement ecology because bears: (1) are among the most common large carnivores inhabiting human‐modified landscapes (Haroldson et al., 2020; Morales‐González et al., 2020; Swenson et al., 2020); (2) live in proximity to humans in many areas of their distribution (Chapron et al., 2014; Elfström et al., 2014); (3) cause conspicuous damage to human property (Bautista et al., 2017; A. Zarzo‐Arias et al., 2020); and, under specific conditions, (4) may represent a risk to human safety (Bombieri et al., 2019; Kudrenko et al., 2020; Smith and Herrero, 2018; Støen et al., 2018). Although management plans in some countries still imply reactive lethal strategies or generalized culling to deal with bear conflicts, existing knowledge suggests that proactive and selective management that targets individuals may represent a more effective solution, as well as being, in general, more socially accepted (Majić Skrbins\̌ek and Krofel, 2015; Swan et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Towards understanding bold behaviour of large carnivores: the case of brown bears in human‐modified landscapes

Bombieri

Penteriani

Delgado

et al. 2021

Animal Conservation

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Human–wildlife conflicts sometimes involve bold animals that do not fear humans and their activities. Such behaviour is detrimental to both wildlife and people and may lead to conflicts, which can be especially serious for large carnivores. Like most wildlife, these species have adapted to live in highly humanized landscapes by adopting human avoidance behaviours. However, bold individuals exist, which represent a main cause of conflicts, public fear and negative attitudes, that greatly influence management and conservation actions. Although costly decisions are constantly made to deal with such individuals, evidence‐based knowledge of their behaviour, that is how and when they move, especially in relation to human activities, is lacking. We analysed telemetry data of brown bears (Ursus arctos) that were GPS‐collared across Slovenia and Trentino (Italy) to explore spatial behaviour and rhythms of activity of bears that were identified as bold by managers and to assess if and how their behaviour differs from that of their ‘non‐bold’ conspecifics (hereafter, control individuals). Because other factors such as sex and age of the bear, season, daytime and region may affect behaviour, we also included these variables in our analyses. On one hand, bold bears were more active at the daytime and used open areas considerably more often than control bears. On the other hand, although differences in distance to settlements and roads, movement rates and daily home ranges were also found, they were not as pronounced as expected. Instead, other factors were found to affect bear behaviour and, most importantly, we found strong inter‐individual differences in all behaviours. Such results suggest that, although bold bears have some behavioural attributes in common that distinguish them from control bears, each individual differs from one another. Our study represents a first step towards understanding bold bears’ behaviour and provide novel evidence‐based knowledge that can help to better know and manage these individuals.

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“…Traces include footprints or scats, usually located in already existing trails or mountain paths, and hairs are commonly found in rub trees or fences in the fields (González‐Bernardo et al, 2021). On the other hand, damages are linked to human activities, and they are mainly driven by the accessibility of easy resources such as apiaries, fruit trees, or livestock (Zarzo‐Arias et al, 2020). Also, they are commonly georeferenced not from the location at which the damage occurred, but from where the damaged property is registered (i.e., the home of the owner).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, ecologically speaking, if looking for habitat suitability, the sensible choice would be to combine observations and traces, as those are the occurrences showing the natural behavior of the species. Damages, on the other hand, would not make good input data as animals approach human activities predominantly due to the presence of easily accessible resources, thus not reflecting the natural behavior (Zarzo-Arias et al, 2020).…”

Section: Analysis Grain and Type Of Occurrence Datamentioning

confidence: 99%

Importance of data selection and filtering in species distribution models: A case study on the Cantabrian brown bear

et al. 2022

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Species distribution models (SDMs) are powerful tools in ecology and conservation. Choosing the right environmental drivers and filtering species' occurrences taking their biases into account are key factors to consider before modeling. In this case study, we address five common problems arising during the selection of input data for presence‐only SDMs on an example of a generalist species: the endangered Cantabrian brown bear. First, we focus on the selection of environmental variables that may drive its distribution, testing if climatic variables should be considered at a 1‐km analysis grain. Second, we investigate how filtering the species' data in view of (1) their collection procedures, (2) different time frames, (3) dispersal areas, and (4) subpopulations affects the performance and outputs of the models at three different spatial analysis grains (500 m, 1 km, and 5 km). Our results show that models with different input data yielded only minor differences in performance and behaved properly in terms of model validation, although coarsening the analysis grain deteriorated model performance. Still, the contribution of individual variables and the habitat suitability predictions differed among models. We show that a combination of limited data availability and poor selection of environmental variables can lead to inaccurate predictions. Specifically for the brown bear, we conclude that climatic variables should not be considered for exploring habitat suitability and that the best input data for modeling habitat suitability in the study area originate from (1) observations and traces from the (2) most recent period (2006–2019) in which the population is expanding, (3) not considering cells of dispersing bear occurrences and (4) modeling subpopulations independently (as they show distinct habitat preferences). In conclusion, SDMs can serve as a useful tool for generalist species including all available data; still, expert evaluation from the perspective of data suitability for the purpose of modeling and possible biases is recommended. This is especially important when the results are intended for management and conservation purposes at the local level, and for species that respond to the environment at coarse analysis grains.

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Seasonality, local resources and environmental factors influence patterns of brown bear damages: implications for management

Cited by 18 publications

References 58 publications

Cost of Coexisting with a Relict Large Carnivore Population: Impact of Apennine Brown Bears, 2005–2015

Cost of Coexisting with a Relict Large Carnivore Population: Impact of Apennine Brown Bears, 2005–2015

Towards understanding bold behaviour of large carnivores: the case of brown bears in human‐modified landscapes

Importance of data selection and filtering in species distribution models: A case study on the Cantabrian brown bear

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