ORCID Profile
0000-0001-7520-126X
Current Organisation
Scion
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Publisher: Informa UK Limited
Date: 23-03-2016
Publisher: Informa UK Limited
Date: 29-11-2018
Publisher: MDPI AG
Date: 28-04-2021
DOI: 10.3390/RS13091706
Abstract: A major challenge in ecological restoration is assessing the success of restoration plantings in producing habitats that provide the desired ecosystem functions and services. Forest structural complexity and biomass accumulation are key measures used to monitor restoration success and are important factors determining animal habitat availability and carbon sequestration. Monitoring their development through time using traditional field measurements can be costly and impractical, particularly at the landscape-scale, which is a common requirement in ecological restoration. We explored the application of proximal sensing technology as an alternative to traditional field surveys to capture the development of key forest structural traits in a restoration planting in the Midlands of Tasmania, Australia. We report the use of a hand-held laser scanner (ZEB1) to measure annual changes in structural traits at the tree-level, in a mixed species common-garden experiment from seven- to nine-years after planting. Using very dense point clouds, we derived estimates of multiple structural traits, including above ground biomass, tree height, stem diameter, crown dimensions, and crown properties. We detected annual increases in most LiDAR-derived traits, with in idual crowns becoming increasingly interconnected. Time by species interaction were detected, and were associated with differences in productivity between species. We show the potential for remote sensing technology to monitor temporal changes in forest structural traits, as well as to provide base-line measures from which to assess the restoration trajectory towards a desired state.
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-10765
Abstract: & & Accurate characterization of land use and land cover (LULC) is important in a rapidly changing environment such as the Indonesian tropics. Over the past 30 years, native tropical forests have been cleared and replaced by fast-growing cash-crops, such as oil palm and rubber plantations. This change in land use dramatically alters the vegetation structure of the entire region. Vegetation structural complexity is highly variable in tropical forests, and provides habitat to a large number of native species. In addition, vegetation structure has an impact on micro-climate and the exchange of greenhouse gases (GHG), water and energy. Measuring vegetation structure in the field can be costly and time consuming, particularly in remote, inaccessible areas of tropical forest. In contrast, Airborne Laser Scanning (ALS) can provide very detailed three-dimensional information on forest structure without the need to reach remote areas in the field. Here, we aim to study the potential of ALS-derived measures of structural complexity as ecological indicators to highlight differences in forest structure across a gradient of LULC in Sumatra, Indonesia. We analysed the structural complexity of four main LULC types relevant to the region: tropical secondary forests, rubber agroforests, oil palm plantations and shrublands. Several structural metrics have been extracted from ALS data over 136 circular 0.1 ha plots (34 plots per LULC type): top height, height percentiles, rumple index, leaf area index (LAI), effective number of layers (ENL), vegetation cover, number of gaps. Results from a Principal Component Analysis (PCA) indicated number of gaps to be a major driver associated with the occurrence of oil palm plantations, while higher values of key structural metrics, such as top height, LAI and ENL were strongly linked with the presence of secondary tropical forest plots. Furthermore, a clear separation in metrics behaviour between forest and oil palm plots was evident from the pairwise comparison of these metrics, with rubber and shrubland plots behaving similarly to either forests or oil palm plantings according to different metrics. Our results show clear distinctions in several structural attributes among different LULC, which indicate the need for careful considerations regarding the impact of land-use change on ecosystem functioning, bio ersity and climate.& &
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-7375
Abstract: & & Indonesia is one of the hotspots of land transformation from forest ecosystems toward oil palm and other cash-crop monocultures. Land-cover changes directly impact below-canopy microclimate, which are critical drivers for many ecological functions, such as greenhouse gas exchange and soil microbial activity. However, microclimatic variability below canopies, even within the same land-use type can be quite large due to structural heterogeneity, vegetation age or vitality, and differences in management practices.& & & & In this study, we focused on the assessment of microclimatic differences within the most common land-use types in tropical lowland Jambi province (Sumatra, Indonesia), using mini-meteorological stations. We used a rapid assessment approach in which we monitored below-canopy key meteorological parameters at a total of 120 different locations from June to November 2021, covering lowland tropical rainforest, oil palm monoculture, rubber monoculture and agroforestry systems, and fallow shrublands. We clustered the study region into 16 micro-regions, each with a radius of four kilometres. In each micro-region, an open-land area served as a reference meteorological location. Based on the gradients of meteorological parameters between below-canopy and open-land conditions we derived the site-specific impact of the respective land-use type on below-canopy microclimate. To further explore microclimatic characteristics of the different land-use types, we used airborne laserscanning (ALS) data available at a subset of 90 plots as well as information on age, management intensities and ownerships of plantations, distance between plantations and forests, and overall land cover distribution.& & & & Preliminary results show that forests and fallow shrublands are generally cooler, wetter and receive lower below-canopy radiation compared to agricultural systems and open land. Forests show a strong capacity to buffer high levels of open-land air temperature and atmospheric vapour pressure deficit (VPD) variability by, on average, 1.7& #176 C and 6.4 hPa, respectively, while oil palm showed very little buffering capacities (0.2& #176 C and 2.2 hPa). At a regional scale, mixed land-use systems tend to be slightly warmer (+0.36& #177 .18& #176 C) and drier (+1.47& #177 .52 hPa VPD) compared to forest-dominated land-use systems. Within the mixed land-use systems, forests tend to be drier (+1.05& #177 .41 hPa VPD) while below-canopy temperature remains similar (+0.38& #177 .34& #176 C) compared to forests in the forest-dominated land-use systems. Interception is an important component in the hydrology of the studied forest locations, with approx. 66% of precipitation being intercepted, while at fallow shrubland, rubber and oil palm locations, only 24, 25 and 17%, respectively, of precipitation was intercepted. Overall, our preliminary results show that there is high variability in meteorological conditions, even within the same micro-region or land-use type.& &
Publisher: MDPI AG
Date: 26-11-2021
DOI: 10.3390/RS13234794
Abstract: Many Indonesian forests have been cleared and replaced by fast-growing cash crops (e.g., oil palm and rubber plantations), altering the vegetation structure of entire regions. Complex vegetation structure provides habitat niches to a large number of native species. Airborne laser scanning (ALS) can provide detailed three-dimensional information on vegetation structure. Here, we investigate the potential of ALS metrics to highlight differences across a gradient of land-use management intensities in Sumatra, Indonesia. We focused on tropical rainforests, jungle rubber, rubber plantations, oil palm plantations and transitional lands. Twenty-two ALS metrics were extracted from 183 plots. Analysis included a principal component analysis (PCA), analysis of variance (ANOVAs) and random forest (RF) characterization of the land use/land cover (LULC). Results from the PCA indicated that a greater number of canopy gaps are associated with oil palm plantations, while a taller stand height and higher vegetation structural metrics were linked with rainforest and jungle rubber. A clear separation in metrics performance between forest (including rainforest and jungle rubber) and oil palm was evident from the metrics pairwise comparison, with rubber plantations and transitional land behaving similar to forests (rainforest and jungle rubber) and oil palm plantations, according to different metrics. Lastly, two RF models were carried out: one using all five land uses (5LU), and one using four, merging jungle rubber with rainforest (4LU). The 5LU model resulted in a lower overall accuracy (51.1%) due to mismatches between jungle rubber and forest, while the 4LU model resulted in a higher accuracy (72.2%). Our results show the potential of ALS metrics to characterize different LULCs, which can be used to track changes in land use and their effect on ecosystem functioning, bio ersity and climate.
Publisher: Springer Science and Business Media LLC
Date: 28-02-2023
DOI: 10.1007/S10980-023-01609-X
Abstract: In forestry, edge zones created by forest degradation and fragmentation are more susceptible to disturbances and extreme weather events. The increase in light regime near the edge can greatly alter forest microclimate and forest structure in the long term. In this context, understanding edge effects and their impact on forest structure could help to identify risks, facilitate forest management decisions or prioritise areas for conservation. In this paper, we focus on the application of airborne laser scanning (ALS) data to assess the impact of edge effects on forest structural metrics in degraded rainforests in Sumatra, Indonesia. Changes in structural heterogeneity with respect to distance from an edge were also quantified. We used 22 ALS structural metrics extracted from 105 plots in secondary forests adjacent to oil palm plantations and analysed the change in canopy structure across edge-to-interior transects. In addition, 91 plots taken from less disturbed areas were used as reference for comparison with the near-to-edge plots. Our analysis found strong evidence of degradation in the secondary forests studied, with multiple edge interactions resulting in a non-diminishing effect even at long distances from the forest edge. On average, we observed a large decrease of about 40% in all metrics of canopy height and about 25% in some metrics of canopy structure across all distances from an edge when compared to the interior forest conditions. Thus, in our forests, canopy height and structure were more susceptible to edge effects than metrics related to canopy gaps. Finally, the degraded forest in our study exhibited lower structural complexity, both at patch and landscape levels, suggesting that disturbances can greatly alter structural complexity in tropical rainforests. Our study confirms the potential of ALS-derived vegetation metrics to study and understand the effects of forest edges and the associated changes in structural complexity over large areas in tropical rainforests. The approach followed here is transferrable to similarly fragmented landscapes in the tropics.
Publisher: Wiley
Date: 09-01-2020
DOI: 10.1111/REC.13098
Publisher: MDPI AG
Date: 29-09-2020
DOI: 10.3390/RS12193184
Abstract: The use of unmanned aerial vehicles (UAVs) for remote sensing of natural environments has increased over the last decade. However, applications of this technology for high-throughput in idual tree phenotyping in a quantitative genetic framework are rare. We here demonstrate a two-phased analytical pipeline that rapidly phenotypes and filters for genetic signals in traditional and novel tree productivity and architectural traits derived from ultra-dense light detection and ranging (LiDAR) point clouds. The goal of this study was rapidly phenotype in idual trees to understand the genetic basis of ecologically and economically significant traits important for guiding the management of natural resources. In idual tree point clouds were acquired using UAV-LiDAR captured over a multi-provenance common-garden restoration field trial located in Tasmania, Australia, established using two eucalypt species (Eucalyptus pauciflora and Eucalyptus tenuiramis). Twenty-five tree productivity and architectural traits were calculated for each in idual tree point cloud. The first phase of the analytical pipeline found significant species differences in 13 of the 25 derived traits, revealing key structural differences in productivity and crown architecture between species. The second phase investigated the within species variation in the same 25 structural traits. Significant provenance variation was detected for 20 structural traits in E. pauciflora and 10 in E. tenuiramis, with signals of ergent selection found for 11 and 7 traits, respectively, putatively driven by the home-site environment shaping the observed variation. Our results highlight the genetic-based ersity within and between species for traits important for forest structure, such as crown density and structural complexity. As species and provenances are being increasingly translocated across the landscape to mitigate the effects of rapid climate change, our results that were achieved through rapid phenotyping using UAV-LiDAR, raise the need to understand the functional value of productivity and architectural traits reflecting species and provenance differences in crown structure and the interplay they have on the dependent biotic communities.
Publisher: Wiley
Date: 11-07-2022
Abstract: Vegetation canopy height is a relevant proxy for aboveground biomass, carbon stock, and bio ersity. Wall‐to‐wall information of canopy height with high spatial resolution and accuracy is not yet available on large scales. For the globally consistent TanDEM‐X data, simplifications are necessary to estimate canopy height with semi‐empirical models based on polarimetric synthetic aperture radar interferometry (PolInSAR). We trained the semi‐empirical models with s led GEDI data, because the assumptions behind the application of such simplifications are not always valid for TanDEM‐X. General linear as well as sinc models and empirical parameterizations of these models were applied to estimate the canopy height in tropical landscapes of Sumatra, Indonesia. Airborne laser scanning (ALS) data were consistently used as an independent reference. The general simplified models were compared with the trained empirical versions to assess the potential improvement of the empirical parameterization of the models. The residuals of the different canopy height models were further evaluated in relation to land use and structural information of the vegetation. Our results indicated that the empirical parameters substantially improved the estimation from a root‐mean‐square‐error (RMSE) of 10.3 m (55.8%) to 8.8 m (47.7%), when using the linear model. In contrast, the improvement of the sinc model with empirical parameters was not substantial compared to the general sinc model (7.4 m [40.4%] vs. 6.9 m [37.5%]). A consistent improvement was observed in the linear model, whereas the improvement of the sinc model was dependent on the land‐use type. Structural attributes like the canopy height itself and vegetation cover had a significant effect on the accuracies, with higher and denser vegetation generally resulting in higher residuals. We demonstrate the potential of the combined exploitation of the TanDEM‐X and GEDI missions for a wall‐to‐wall canopy height estimation in a tropical region. This study provides relevant findings for a consistent mapping of vegetation canopy height in tropical landscapes and on large scales with spaceborne laser and SAR data.
Publisher: Springer Science and Business Media LLC
Date: 09-10-2019
Publisher: Elsevier BV
Date: 10-2021
Publisher: Informa UK Limited
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 06-02-2017
Publisher: Wiley
Date: 12-2021
DOI: 10.1111/EMR.12505
Abstract: The benefits of using remote sensing technologies for informing and monitoring ecological restoration of forests from the community to the in idual are presented. At the community level, we link remotely sensed measures of structural complexity with animal behaviour. At the plot level, we monitor the return of vegetation structure and ecosystem services (e.g. carbon sequestration) using data‐rich three‐dimensional point clouds. At the in idual‐level, we use high‐resolution images to accurately classify plants to species and provenance and show genetic‐based variation in canopy structural traits. To facilitate the wider use of remote sensing in restoration, we discuss the challenges that remain to be resolved.
Location: Italy
No related grants have been discovered for Nicolò Camarretta.