Mobile Laser Scanner understory characterization: an exploratory study on hazel grouse in Italian Alps

Galluzzi, Marta; Puletti, Nicola; Armanini, Marco; Chirichella, Roberta; Mustoni, Andrea

doi:10.1101/2022.04.26.489487

Cited by 5 publications

(3 citation statements)

References 37 publications

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“…For example, a form of the DCB metric has been previously used to quantify forest structure [45,46], but this study is the first we are aware of that directly applies this approach to habitat quantification. There has been previous work using TLS for understory habitat classification [58,59], as well as excellent R packages that have been developed to quantify the viewshed specifically for habitat characterization [60]. The advantage of our metrics is the ability to be applied to single-point TLS scans as well as account for slope.…”

Section: Tls Metricsmentioning

confidence: 99%

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Batchelor,

Hudak,

Gould

et al. 2023

Remote Sensing

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The Canada lynx is listed as a threatened species, and as such, the identification and conservation of lynx habitats is of significant concern. Lynxes require areas with high amounts of horizontal cover made up of ground vegetation. Lidar offers a robust method of quantifying vegetation structure, and airborne lidar has been acquired across large areas of potential lynx habitat. Unfortunately, airborne lidar is often not able to directly measure understory horizontal cover due to occlusion from the upper branches. Terrestrial lidar does directly measure understory horizontal cover and can be used as training data for larger area models using airborne lidar. In this study, we acquired 168 individual terrestrial lidar scans (TLS) across 42 sites in north-central Washington state. We generated metrics from the single-scan TLS plots using depth maps, a digital cover board, and voxels. Using our TLS metrics as the training data for the airborne lidar acquired for the entire Loomis State Forest, we were able to produce a model using xgboost with 85% accuracy. We believe our study shows that single-scan TLS plots can be used effectively to quantify fine-scale forest structure elements relevant to species habitat, to then inform larger area models using airborne lidar.

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Section: Tls Metricsmentioning

confidence: 99%

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Batchelor,

Hudak,

Gould

et al. 2023

Remote Sensing

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show abstract

“…Widespread knowledge of three-dimensional forest structures is essential for effective forest planning and management, particularly in dealing with biodiversity and wildlife communities. Features associated with forest structure are important to understand and prospect the wildlife species presence and thus the habitat suitability [ 1 , 2 ]. The understory has significant implications not only for forest health but also for wildlife habitat, nesting, and food resources [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, understory vegetation influences forest ecosystem processes, such as overstory regeneration, carbon sequestration, soil nutrient cycling, erosion, and fire intensity, and spreads in a variety of ways [ 3 , 4 , 5 ]. Given its importance, precise information on understory spatial distribution, particularly across wide areas, is becoming increasingly crucial in the forest planning and management context [ 1 , 2 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Mapping Understory Vegetation Density in Mediterranean Forests: Insights from Airborne and Terrestrial Laser Scanning Integration

Ferrara

Puletti

Guasti

et al. 2023

Sensors

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The understory is an essential ecological and structural component of forest ecosystems. The lack of efficient, accurate, and objective methods for evaluating and quantifying the spatial spread of understory characteristics over large areas is a challenge for forest planning and management, with specific regard to biodiversity and habitat governance. In this study, we used terrestrial and airborne laser scanning (TLS and ALS) data to characterize understory in a European beech and black pine forest in Italy. First, we linked understory structural features derived from traditional field measurements with TLS metrics, then, we related such metrics to the ones derived from ALS. Results indicate that (i) the upper understory density (5–10 m above ground) is significantly associated with two ALS metrics, specifically the mean height of points belonging to the lower third of the ALS point cloud within the voxel (HM1/3) and the corresponding standard deviation (SD1/3), while (ii) for the lower understory layer (2–5 m above ground), the most related metric is HM1/3 alone. As an example application, we have produced a map of forest understory for each layer, extending over the entire study region covered by ALS data, based on the developed spatial prediction models. With this study, we also demonstrated the power of hand-held mobile-TLS as a fast and high-resolution tool for measuring forest structural attributes and obtaining relevant ecological data.

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Early-succession secondary forests following agropastoral abandonment are key winter habitats for the conservation of a priority bird in the European Alps

et al. 2022

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In contrast to old-growth forests, early-successional stands remain understudied despite potentially harbouring species of conservation interest. With this work, focused on hazel grouse Tetrastes bonasia, a cryptic and indicator species known to select for close-to-natural forests, we evaluated winter densities, home range, microhabitat selection and diet, combining DNA-based mark-recapture and metabarcoding from faecal samples. In total, 216 droppings, collected over 2 years along forest transects in the Italian Alps, were successfully genotyped and 43 individuals were identified. Density estimates were similar to values reported by other studies in the Alps with an average of 4.5 and 2.4 individuals/km2 in the first and second study year, respectively, and mean home ranges estimated at 0.95 km2. According to habitat selection models and eDNA-based diet analysis, hazel grouse selected early-succession secondary-growth forests formed after the abandonment of traditional agropastoral activities. These forests, mostly composed of hazel Corylus avellana, Norway spruce Picea abies and Sorbus spp., provided winter food resources and shelter. The diet analysis also highlighted forest arthropods as a non-negligible source of food. Birds avoided areas subject to intensive browsing by ungulates; small forest roads seasonally closed to traffic had positive influence on hazel grouse (i.e. higher abundance of droppings), while roads open to traffic had no effect. Importantly, despite the high coverage of mature forest habitats of Community Interest (53% of our study area), droppings were more abundant in non-listed early-succession secondary forests with similar plant composition. Our results suggest that forest succession after agropastoral abandonment may be beneficial for some forest birds of conservation interest, while acknowledging its negative effects on the previous grassland biodiversity. Graphical abstract

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Mobile Laser Scanner understory characterization: an exploratory study on hazel grouse in Italian Alps

Cited by 5 publications

References 37 publications

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Terrestrial and Airborne Lidar to Quantify Shrub Cover for Canada Lynx (Lynx canadensis) Habitat Using Machine Learning

Mapping Understory Vegetation Density in Mediterranean Forests: Insights from Airborne and Terrestrial Laser Scanning Integration

Early-succession secondary forests following agropastoral abandonment are key winter habitats for the conservation of a priority bird in the European Alps

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