Camarretta, Nicolò

[["dc.bibliographiccitation.firstpage","1706"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Camarretta, Nicolò"],["dc.contributor.author","Harrison, Peter A."],["dc.contributor.author","Lucieer, Arko"],["dc.contributor.author","Potts, Brad M."],["dc.contributor.author","Davidson, Neil"],["dc.contributor.author","Hunt, Mark"],["dc.date.accessioned","2021-07-05T15:00:49Z"],["dc.date.available","2021-07-05T15:00:49Z"],["dc.date.issued","2021"],["dc.description.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 individual 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."],["dc.description.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 individual 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."],["dc.description.sponsorship","Australian Research Council (ARC) Linkage Grant"],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3390/rs13091706"],["dc.identifier.pii","rs13091706"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/87910"],["dc.language.iso","en"],["dc.notes.intern","DOI Import DOI-Import GROB-441"],["dc.relation.eissn","2072-4292"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.rights","CC BY 4.0"],["dc.title","Handheld Laser Scanning Detects Spatiotemporal Differences in the Development of Structural Traits among Species in Restoration Plantings"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","127"],["dc.bibliographiccitation.issue","S2"],["dc.bibliographiccitation.journal","Ecological Management & Restoration"],["dc.bibliographiccitation.lastpage","139"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Harrison, Peter A."],["dc.contributor.author","Camarretta, Nicolò"],["dc.contributor.author","Krisanski, Sean"],["dc.contributor.author","Bailey, Tanya G."],["dc.contributor.author","Davidson, Neil J."],["dc.contributor.author","Bain, Glen"],["dc.contributor.author","Hamer, Rowena"],["dc.contributor.author","Gardiner, Riana"],["dc.contributor.author","Proft, Kirstin"],["dc.contributor.author","Taskhiri, Mohammad Sadegh"],["dc.contributor.author","Turner, Paul"],["dc.contributor.author","Turner, Darren"],["dc.contributor.author","Lucieer, Arko"],["dc.date.accessioned","2022-01-12T08:11:17Z"],["dc.date.available","2022-01-12T08:11:17Z"],["dc.date.issued","2021"],["dc.description.abstract","The benefits of using remote sensing technologies for informing and monitoring ecological restoration of forests from the community to the individual 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 individual-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."],["dc.identifier.doi","10.1111/emr.12505"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97983"],["dc.language.iso","en"],["dc.relation.issn","1442-7001"],["dc.relation.issn","1442-8903"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.title","From communities to individuals: Using remote sensing to inform and monitor woodland restoration"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3184"],["dc.bibliographiccitation.issue","19"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Camarretta, Nicolò"],["dc.contributor.author","A. Harrison, Peter"],["dc.contributor.author","Lucieer, Arko"],["dc.contributor.author","M. Potts, Brad"],["dc.contributor.author","Davidson, Neil"],["dc.contributor.author","Hunt, Mark"],["dc.date.accessioned","2021-01-27T12:35:39Z"],["dc.date.available","2021-01-27T12:35:39Z"],["dc.date.issued","2020"],["dc.description.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 individual 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 individual trees to understand the genetic basis of ecologically and economically significant traits important for guiding the management of natural resources. Individual 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 individual 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 divergent 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 diversity 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."],["dc.identifier.doi","10.3390/rs12193184"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/79484"],["dc.language.iso","en"],["dc.relation.issn","2072-4292"],["dc.title","From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","573"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","New Forests"],["dc.bibliographiccitation.lastpage","596"],["dc.bibliographiccitation.volume","51"],["dc.contributor.author","Camarretta, Nicolò"],["dc.contributor.author","Harrison, Peter A."],["dc.contributor.author","Bailey, Tanya"],["dc.contributor.author","Potts, Brad"],["dc.contributor.author","Lucieer, Arko"],["dc.contributor.author","Davidson, Neil"],["dc.contributor.author","Hunt, Mark"],["dc.date.accessioned","2021-01-27T12:35:54Z"],["dc.date.available","2021-01-27T12:35:54Z"],["dc.date.issued","2019-10"],["dc.identifier.doi","10.1007/s11056-019-09754-5"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/79486"],["dc.language.iso","en"],["dc.relation.issn","0169-4286"],["dc.relation.issn","1573-5095"],["dc.title","Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches"],["dc.type","review"],["dc.type.internalPublication","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","447"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Restoration Ecology"],["dc.bibliographiccitation.lastpage","458"],["dc.bibliographiccitation.volume","28"],["dc.contributor.author","Camarretta, Nicolò"],["dc.contributor.author","Harrison, Peter A."],["dc.contributor.author","Bailey, Tanya"],["dc.contributor.author","Davidson, Neil"],["dc.contributor.author","Lucieer, Arko"],["dc.contributor.author","Hunt, Mark"],["dc.contributor.author","Potts, Brad M."],["dc.date.accessioned","2021-01-27T12:35:48Z"],["dc.date.available","2021-01-27T12:35:48Z"],["dc.date.issued","2020-03"],["dc.description.abstract","The stability of species and provenance performance across diverse environments is a major issue in restoration, particularly for assisted migration and climate-adjusted provenancing strategies. This study examines how differences in species and provenance performance are affected by plant community composition in a dry sclerophyll forest restoration experiment. Five indices were measured over six years post-establishment to evaluate the relative performance of community composition using ten provenances of two focal eucalypts (Eucalyptus pauciflora and E. tenuiramis) under six community treatments for E. pauciflora and five for E. tenuiramis. Community treatments varied according to the species planted as the immediate neighbour to the focal species, and included same species, same genus or one of three different genera. Significant species and provenance differences were observed for all measured performance indices, with no evidence of interaction effects with community treatments. E. tenuiramis was more susceptible to insects and frost, had poorer establishment but greater growth of the survivors than E. pauciflora. Generally, non-local provenances were more susceptible to insect herbivory and frost damage and had higher mortality than local provenances. At this early life-stage there was no evidence that co-planted species affected the relative performance of focal species or provenances, arguing transfer functions are likely stable across different planted communities. While species and provenance performance was not affected by community context, focal species differed in their response to upslope migration and any climate-adjusted provenancing may require staged transfers to avoid maladaptation under contemporary growing conditions."],["dc.identifier.doi","10.1111/rec.13098"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/79485"],["dc.language.iso","en"],["dc.relation.issn","1061-2971"],["dc.relation.issn","1526-100X"],["dc.title","Stability of species and provenance performance when translocated into different community assemblages"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]