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Marchi, Niccolò (2019) Deadwood assessment using LiDAR technology in disturbance ecology. [Ph.D. thesis]

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Abstract (italian or english)

Deadwood is a key component of the forest ecosystems, due to its importance as a life substrate for several organisms, such as plants, animals, fungi and lichens. This huge versatility is being recognised only in the last decades also by legislation after the increasing findings by the scientific community what biodiversity is and on what it is based. Nevertheless, at an operational level, deadwood conservation measures are not so well implemented yet because it is still widely considered as an issue for many of the forest stakeholders ). While from a production point of view it can be seen as an income loss, it is generally evaluated as a risk for all the ones who frequent forests for work or leisure.
While this applies mostly to finer scales, at larger scales the presence of big amounts of deadwood surely derives from an economical damage for the land manager and appears as a sign negligence to the local population. Such is the case of natural disturbances, e.g. wildfires, windstorms, ice and snow damages, events that strongly affect communities both in ecological and economical terms. Due to an estimated increase of extreme events
in the future in relation to global warming, it is important to timely assess wide scale processes in order to understand the underlying dynamics and properly manage the available forest resources. Extreme events can indeed alter the ecosystem functionality threatening the provision of forest services such as conservation of drinking water, protection from natural hazards and preservation of biodiversity. Deadwood is strictly connected to fine and large scale disturbances, enhancing (e.g. severity of wildfires) or
mitigating them (e.g. favouring the natural regeneration after a destructive event), but the dynamics at landscape level are not always well known. Related data, indeed, was always collected through ground surveys, methods that required huge efforts in terms of time and energies. In this perspective, remote sensing technologies can help to catch useful
information within less time across wide areas or with higher detail. Optical sensors, such as aerial photographs, became more easily accessible in the last decades but the information that can be obtained, even with the application of photogrammetry techniques, lacks of reliability for what concerns structural parameters of forests. The recent advent and development of active sensors provided the possibility of extracting
information on all the three dimensions of the forest structure, allowing the study of structure characteristics and the identification of what lies beneath canopies. It is the case of Light Detection and Ranging (LiDAR), a laser-based technology that is widely proving its effectiveness in providing valuable data in the forestry field.
LiDAR technology was chosen as main tool within the present research project dedicated to the application and development of methodologies for the identification and quantification of several deadwood components. The research approach followed a thorough literature review to describe the state-of-the-art on the topic and define the knowledge gaps and future perspectives. This work lead to the definition of three specific study cases that would have deepened: 1) the assessment of ice-storm damages on alpine production stands, 2) the characterisation of deadwood and the description of its role in the regeneration establishment within a post-fire restoration site and 3) the quantification and description of the three-dimensional spatial distribution of surface fuels in conifer-dominated stands. The results obtained in the three case studies show the feasibility of capturing important structural information about different elements of
deadwood, useful to describe local and global processes for the study of ecological dynamics related deadwood in the context of natural disturbances.

EPrint type:Ph.D. thesis
Tutor:Lingua, Emanuele
Ph.D. course:Ciclo 31 > Corsi 31 > LAND, ENVIRONMENT, RESOURCES, HEALTH (LERH)
Data di deposito della tesi:25 February 2019
Anno di Pubblicazione:26 February 2019
Key Words:deadwood, lidar, disturbance ecology
Settori scientifico-disciplinari MIUR:Area 07 - Scienze agrarie e veterinarie > AGR/05 Assestamento forestale e selvicoltura
Struttura di riferimento:Dipartimenti > Dipartimento Territorio e Sistemi Agro-Forestali
Codice ID:11819
Depositato il:06 Nov 2019 14:04
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