Shrub fuel characteristics estimated from overstory variables in NW Spain pine stands

Castedo‐Dorado, Fernando; Gómez-Vázquez, Ibán; Fernandes, Paulo M.; Crecente-Campo, Felipe

doi:10.1016/j.foreco.2012.03.002

Cited by 31 publications

(20 citation statements)

References 53 publications

(85 reference statements)

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“…This general trend is consistent with other studies, reporting that the maximum shrub development was also limited by overstory variables such as basal area (G -Coll et al 2011, Castedo-Dorado et al 2012). Thus G serves as an indicator of stand competition, and has the advantage of being relatively simple to obtain in the field or to be inferred from growth and yield models (Castedo-Dorado et al 2012).…”

Section: Discussionsupporting

confidence: 92%

A model of shrub biomass accumulation as a tool to support management of Portuguese forests

Botequim¹,

Zubizarreta-Gerendiain²,

García-Gonzalo³

et al. 2015

iForest

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© iForest -Biogeosciences and Forestry IntroductionDuring the last decades, significant land use change took place in Portugal and elsewhere in the Mediterranean region. Many marginal agricultural or grazing lands were either abandoned or afforested. Natural succession led to changes in vegetation structure and composition where agricultural activities ceased, thus contributing to the expansion of shrubland, woodland and forests with a well-developed shrub understory (Fernán-dez Alés et al. 1992). These changes resulted in higher carbon stocks as well as in more flammable ecosystems prone to large and high-severity fires (Pausas 2004, Castro & Freitas 2009).Fuel dynamics refers to the structural and temporal modifications undergone by a fuel layer or fuel complex. Shrub accumulation models could assist in forecasting the dynamics of biomass and carbon storage. Many modeling of fuel dynamics follows the simple model by Olson (1963) that describes the relationship between production and decomposition as a modified exponential function that flattens out to a plateau. Other studies describe fuel and shrub dynamics by timedependent models of forest fire hazard (Gould et al. 2011). However, shrub biomass accumulation information for Mediterranean areas is very limited. Few studies addressed the temporal dynamics of shrub structure and/or biomass in shrublands (Baeza et al. 2006), which are expected to be different under a forest canopy, due to competition for resources (i.e., light, water). Hence, little attention has been given to understory vegetation, likely due to its limited economic importance. Nonetheless, the ecological significance of the understory is high, since it plays an important role on nutrient cycles, carbon storage and fire hazard.Currently available carbon models still lack details on biomass dynamics, which in turn affect the calculation of these processes. A recent study by Rosa et al. (2011) to estimate pyrogenic emissions of greenhouse gases, aerosols and other trace gases from wildfires in Portugal identified shrub biomass as the variable with the greatest impact on the uncertainty inherent in such estimates. Therefore, it is essential to improve the assessment of forest biomass, including its spatial and temporal variation.In the Mediterranean region, fire is one of the most important factors affecting forest ecosystems, both ecologically and economically (Pereira & Santos 2003). Higher shrub loading implies higher flammability, likelihood of crowning fire, and difficulty in fire control (Schmidt et al. 2002, Fernandes 2009a. Fernandes et al. (2004) observed differences in fire behavior and severity among maritime pine (Pinus pinaster) plots depending on fuel age (i.e., time since last treatment) and the presence or absence of surface fuel treatments. Furthermore, recent research aimed at developing wildfire occurrence models in Portugal included the understory shrubs biomass as a significant variable. Indeed, shrubs have a large impact on fire risk with obvious implications to forest plannin...

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Section: Discussionsupporting

confidence: 92%

A model of shrub biomass accumulation as a tool to support management of Portuguese forests

Botequim¹,

Zubizarreta-Gerendiain²,

García-Gonzalo³

et al. 2015

iForest

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“…Canopy cover, i.e., the proportion of the forest floor covered by the vertical projection of the tree crowns, is suitable for describing stand-level microclimate and can easily be estimated, thus, most forest inventories record it routinely [32,33]. Canopy and shrub covers are expected to be correlated in forest stands [34]. The soil and physiographic variables were: texture, content of organic matter, rockiness, slope, altitude, and aspect.…”

Section: Species Data Set and Study Variablesmentioning

confidence: 99%

Large-Scale Regeneration Patterns of Pinus nigra Subsp. salzmannii: Poor Evidence of Increasing Facilitation Across a Drought Gradient

Tíscar

Linares

2013

Forests

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Tree recruitment is a key process underlying stand dynamics and sustainability in managed forests. Woody plant cover is known to affect the regeneration success of Pinus nigra, suggesting the existence of facilitative plant-plant interactions. The regeneration patterns of this Mediterranean pine were analyzed across its distribution area, using data from 3226 plots of the Spanish National Forest Inventory. We aimed to test the hypothesis that seedlings establishment occurs under higher values of either canopy or shrub cover in the driest populations, as predicted by the stress-gradient hypothesis. Data were analyzed by means of Generalized Linear Models and multivariate methods. Results revealed that regeneration failure occurs on a regional scale, and that regeneration is facilitated by tree canopy cover of 55%-80%. A non-linear pattern of interaction along an aridity gradient was identified, with competition at the wettest site, high facilitation at the mid-dry sites, and low facilitation at the driest site. Evidence suggests that some shrub species may facilitate recruitment in the harsher areas. Collectively, our results reduce the possibilities of adapting forest management to drying climates by the application of alternative silvicultural prescriptions involving canopy cover.

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“…The proposed classes were a generalization of the schema proposed by Fernandes (2009), where fire risk (characterized by variables as propagation, intensity or crown fire potential) was related to forest structure, defined by tree density and height. In the same direction is the work developed by Castedo et al (2012), which shows that, in general and also in particular for maritime pine in Galicia, the higher the tree density, the lower the above ground fuel load (due to the shadowing effect of the trees on the understory), and therefore the fuel model would lead to wildfires of a lower magnitude. With respect to the height of the forest stand, in general, the higher the trees, the lower the probability of a fire reaching the crowns and propagating through them, increasing the magnitude of the wildfire, as Gómez-Vázquez et al (2014) found for maritime pine.…”

Section: Classification Of the Forest Stands Regarding The Magnitude mentioning

confidence: 73%

“…When applying the proposed methodology, it should be taken into account that, although the threshold values chosen to define the magnitude of the wildfires are coherent with the fire behaviour models that were set as a reference (Fernandes 2009;Castedo et al, 2012) and that they have been considered to be suitable for the study area, a different choice would have led to different results. The difficulty of setting these values lays in the fact that the fire behaviour models we used do not specify what is considered to be a dense or a tall stand, and therefore the user has to establish these values arbitrarily.…”

Section: Identification Of the Forested Areasmentioning

confidence: 99%

Caracterización del interfaz forestal/urbano empleando LiDAR como herramienta para la estimación del riesgo de daños por incendios forestales

2016

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Galicia is a region in NW Spain which is usually affected by a high number of forest fires, and it should meet the current regulations regarding the distance between forests and buildings. This paper aims to identify and characterize woodlands and classify buildings according to their fire risk, for a 36 km 2 area in Forcarei (Pontevedra, Spain). We used LiDAR data to generate three spatial models (DTM: Digital Terrain Model, DSM: Digital Surface Model and nDSM: Normalized Digital Surface Model) and two statistics to characterize the forest stands (density of dominant trees per hectare and their average height). The identification of forested areas was performed using an object-based classification method using the intensity image, the height model and an orthophotograph of the area, and a kappa coefficient of 0.82 was obtained in the validation. The woodlands were reclassified according to the magnitude of a possible fire, based on the density and the average height of the woodlands. The forest stands were mapped according to the magnitude of a possible fire and it was found that 1.18 km 2 would be susceptible to a low magnitude fire, 3.75 km 2 to a medium magnitude fire and 2.25 km 2 to a fire of a high magnitude. Afterwards, it was determined whether the buildings in the area complied with the legislation relating to minimum distance from the forested areas (30 meters). For those that did not meet this distance, the risk of damage in case of a wildfire was calculated. The result was that 43.01% of buildings in the area complied with the regulations, 9.95% were located in a very low risk area, 25.74% in a low risk location, 12.37% in a medium risk area and 8.93% were in a high or very high risk area.Key words: LiDAR, woodlands, buildings, forest fire, OBIA, PNOA. Caracterización del interfaz forestal/urbano empleando LiDAR como herramienta para la estimación del riesgo de daños por incendios forestalesResumen: Galicia (NO de España), afectada por alto número de incendios forestales, debería cumplir la normativa vigente en relación a la distancia entre masas forestales y edificaciones. Este trabajo tiene como objetivos identificar y caracterizar las masas forestales y clasificar las edificaciones en función del riesgo en caso de incendio para un área de 36 km 2 del municipio de Forcarei (Pontevedra). A partir de los datos LiDAR se obtuvo la imagen de intensidades, modelos espaciales (MDT: Modelo Digital del Terreno, MDS: Modelo Digital de Superficies y MANO: Modelo de Alturas Normalizadas de Objetos) y dos estadísticos para la caracterización de las masas forestales (densidad de pies dominantes por hectárea y altura promedio de dominantes). La identificación de las masas forestales se realizó con un método de clasificación orientado a objetos empleando la imagen de intensidades, el modelo de alturas y ortofotografía de la zona, obteniéndose coeficiente kappa de grado de correspondencia de 0,82 en la validación. Las masas forestales se reclasificaron en función de la magnitud de un posible incendio, ba...

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Shrub fuel characteristics estimated from overstory variables in NW Spain pine stands

Cited by 31 publications

References 53 publications

A model of shrub biomass accumulation as a tool to support management of Portuguese forests

A model of shrub biomass accumulation as a tool to support management of Portuguese forests

Large-Scale Regeneration Patterns of Pinus nigra Subsp. salzmannii: Poor Evidence of Increasing Facilitation Across a Drought Gradient

Caracterización del interfaz forestal/urbano empleando LiDAR como herramienta para la estimación del riesgo de daños por incendios forestales

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