Snow avalanche release in forest ecosystems: A case study in the Aosta Valley Region (NW-Italy)

Viglietti, Davide; Letey, S.; Motta, Renzo; Maggioni, Margherita; Freppaz, Michèle

doi:10.1016/j.coldregions.2010.08.007

Cited by 38 publications

(18 citation statements)

References 18 publications

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“…When the shrub density is much too high, the tree recruitment is impacted (Tasser et al 2007). Finally, dwarf shrubs play an important role in increasing the probability of avalanche release (Viglietti et al 2010). For these reasons, the measurement of the shrub biomass offers valuable data that complement the forest tree biomass data, and should help to decipher the functional role of this ecosystem compartment.…”

Section: Introductionmentioning

confidence: 99%

Allometric equations for biomass assessment of subalpine dwarf shrubs

et al. 2011

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Shrubs are an important component of mountain ecosystems in terms of productivity and diversity. The estimate of shrub biomass via allometric equations represents a non-destructive alternative to obtain quantitative data. We propose allometric equations to estimate aboveground biomass from easily acquirable descriptive parameters of plant height and cover using linear models for five of the most abundant subalpine shrub species in European mountain or boreal ecosystems: Rhododendron ferrugineum, Vaccinium myrtillus, V. uliginosum, V. vitisidaea and Juniperus sibirica. Samples used for the establishment of the equations are from non-disturbed Pinus cembra-Larix decidua stands, and from adjacent stands frequently disturbed by snow avalanches. The equations adequately predict shrub biomass for all species except V. uliginosum. They thus provide a useful and nondestructive method for estimating aboveground shrub biomass in subalpine ecosystems.

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Section: Introductionmentioning

confidence: 99%

Allometric equations for biomass assessment of subalpine dwarf shrubs

et al. 2011

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“…and beech (Fagus sylvatica L.) (1% each), Austrian pine (Pinus nigra J. F. Arnold) (0.5%), and riparian forests (0.5%) (INFC 2007). The maximum elevation of the tree line is about 2300 masl (Viglietti et al 2010).…”

Section: Study Areamentioning

confidence: 99%

Snow Avalanches in Forested Terrain: Influence of Forest Parameters, Topography, and Avalanche Characteristics on Runout Distance

Teich¹,

Bartelt

Grêt‐Regamey³

et al. 2012

Arctic, Antarctic, and Alpine Research

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“…Other authors have proposed regression trees (Amatulli et al, 2006), neural networks (Vega-García et al, 2007), Bayesian probability techniques (Romero-Calcerrada et al, 2008), and generalized additive models (Vilar et al, 2010). Compared to such algorithms, most of which are parametric, the machine-learning approach adopted by MaxEnt has been performing equally, if not better (Bar Massada et al, 2013).…”

Section: Analytical Approachmentioning

confidence: 99%

Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

Vacchiano

Foderi

Berretti

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Modeling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an Alpine region in Italy using a regional wildfire archive (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) and MaxEnt modeling. We analyzed separately (i) winter forest fires, (ii) winter fires on grasslands and fallow land, and (iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component. Collinearity among predictors was reduced by a principal component analysis. Regarding ignitions, 30 % occurred in agricultural areas and 24 % in forests. Ignitions peaked in the late winter-early spring. Negligence from agrosilvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study time frame, but increased from 6 to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of fit (AUC 0.90-0.95). Temperature was proportional to the probability of ignition, and precipitation was inversely proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different effect on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such a spatially explicit approach allows us to carry out spatially targeted fire management strategies and may assist in developing better fire management plans.

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Snow avalanche release in forest ecosystems: A case study in the Aosta Valley Region (NW-Italy)

Cited by 38 publications

References 18 publications

Allometric equations for biomass assessment of subalpine dwarf shrubs

Allometric equations for biomass assessment of subalpine dwarf shrubs

Snow Avalanches in Forested Terrain: Influence of Forest Parameters, Topography, and Avalanche Characteristics on Runout Distance

Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

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