ORCID Profile
0000-0002-6955-9203
Current Organisations
University of Melbourne
,
Danmarks Tekniske Universitet
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Publisher: Wiley
Date: 22-09-2023
DOI: 10.1111/ECOG.06435
Publisher: Wiley
Date: 10-2020
DOI: 10.1002/ECS2.3262
Publisher: Springer Science and Business Media LLC
Date: 15-03-2016
Publisher: Springer Science and Business Media LLC
Date: 10-02-2020
DOI: 10.1007/S10980-020-00974-1
Abstract: Land use change requires measuring shifting patterns in bio ersity at various spatial scales to inform landscape management. Assessing vegetation change at different scales is challenging in urban ecosystems managed by many in iduals. Thus, we do not know much about the structure and function of green spaces that support bio ersity. We aim to understand how vegetation structure and function indicators in urban community gardens vary with spatial scale, applying new and traditional methods in landscape ecology to inform future research and application. We performed two methods to assess garden vegetation structure (height) and function (species ersity, cover) at the garden- and garden plot scale. First, we used traditional field s ling to estimate garden vegetation at the garden scale (1 m 2 quadrats along transects) and at the plot scale (estimated within entire plot) to measure height, ersity and cover. Second, we used UAV aerial imagery to derive measures of garden and plot vegetation using canopy height models (CHMs). We evaluated differences in CHMs at each scale across the gardens, and compared field and UAV-derived measures. Garden vegetation characteristics vary with spatial scale. Plant species richness and vegetation cover, but not height, related to UAV-derived imagery. New technologies paired with traditional field methods can together inform how vegetation structure and function vary with spatial scale in urban landscapes. Spatial scale is key to accurate and meaningful urban vegetation analyses. New and traditional methods in urban ecology research should develop together to improve and streamline their future application.
Publisher: Oxford University Press (OUP)
Date: 2022
DOI: 10.1093/JUE/JUAC008
Abstract: Urban gardens are an integral part of urban agricultural systems, contributing to ecosystem services, bio ersity and human wellbeing. These systems occur at fine scales, can be highly complex and therefore offer the opportunity to test mechanisms of ecological patterns and processes. The capacity to confidently characterize urban gardens and their land uses is still lacking, while it could provide the basis for assessing ecosystem service provision. Land classifications from remote sensing platforms are common at the landscape scale, but imagery often lacks the resolution required to map differences in land use of fine-scale systems such as urban gardens. Here, we present a workflow to model and map land use in urban gardens using imagery from an unoccupied aerial vehicle (UAV) and machine learning. Due to high resolutions (& cm) from image acquisition at low altitudes, UAV remote sensing is better suited to characterize urban land use. We mapped six common land uses in 10 urban community gardens, exhibiting distinct spatial arrangements. Our models had good predictive performance, reaching 80% overall prediction accuracy in independent validation and up to 95% when assessing model performance per cover class. Extracting spatial metrics from these land use classifications, we found that at the garden and plot scale, plant species richness can be estimated by the total area and patchiness of crops. Land use classifications like these can offer an accessible tool to assess complex urban habitats and justify the importance of urban agriculture as a service-providing system, contributing to the sustainability and livability of cities.
Publisher: Wiley
Date: 24-10-2021
DOI: 10.1111/CSP2.566
Abstract: Wildlife can persist in a range of landscape configurations, but population densities can vary due to resource availability. Resources and environmental conditions shaping habitat suitability may be spatially dispersed or clumped, which can drive habitat availability. We explored how spatial configuration and aggregation of favorable feeding resources and climatic conditions affect populations of the greater glider ( Petauroides volans ), an arboreal marsupial in southeast Australia, vulnerable to climate change and disturbances. We hypothesized home‐range functionality from literature and field observations and used a generalized spatial framework based on neutral landscape models to test how spatial aggregation influences home‐range sizes and population structure. At the landscape scale, any decrease in climatic suitability also decreased potential population density, independent of the initial spatial configuration of the feeding landscape. At the stand scale however, the spatial configuration of feeding habitat drove population density. Dispersed resources required increased home‐range sizes for in idual greater gliders to obtain feeding resources and resulted in smaller populations. Clumped resources supported larger populations, even when only small fractions of the stand contained feeding habitat. Disturbances to these resources could either retain populations or lead to extinction, depending on spatial aggregation and disturbance intensity. Increasingly severe dispersed disturbances caused potential home ranges to disappear more rapidly and remaining home ranges to become larger and contain less feeding habitat. The ability of greater gliders to establish populations and persist under disturbance was therefore highly dependent on the spatial aggregation of habitat resources and the type and severity of disturbance. Changes in climate act at a different scale and may override favorable habitat conditions at the stand level. Our results have implications for the conservation and retention of critical feeding habitat for greater gliders and provide insights into important factors to ensure population persistence under climate change and forest management.
Publisher: Wiley
Date: 12-2021
DOI: 10.1002/ECE3.8428
Abstract: Herbivore foraging decisions are closely related to plant nutritional quality. For arboreal folivores with specialized diets, such as the vulnerable greater glider ( Petauroides volans ), the abundance of suitable forage trees can influence habitat suitability and species occurrence. The ability to model and map foliar nitrogen would therefore enhance our understanding of folivore habitat use at finer scales. We tested whether high‐resolution multispectral imagery, collected by a lightweight and low‐cost commercial unoccupied aerial vehicle (UAV), could be used to predict total and digestible foliar nitrogen (N and digN) at the tree canopy level and forest stand‐scale from leaf‐scale chemistry measurements across a gradient of mixed‐species Eucalyptus forests in southeastern Australia. We surveyed temperate Eucalyptus forests across an elevational and topographic gradient from sea level to high elevation (50–1200 m a.s.l.) for forest structure, leaf chemistry, and greater glider occurrence. Using measures of multispectral leaf reflectance and spectral indices, we estimated N and digN and mapped N and favorable feeding habitat using machine learning algorithms. Our surveys covered 17 Eucalyptus species ranging in foliar N from 0.63% to 1.92% dry matter (DM) and digN from 0.45% to 1.73% DM. Both multispectral leaf reflectance and spectral indices were strong predictors for N and digN in model cross‐validation. At the tree level, 79% of variability between observed and predicted measures of nitrogen was explained. A spatial supervised classification model correctly identified 80% of canopy pixels associated with high N concentrations (≥1% DM). We developed a successful method for estimating foliar nitrogen of a range of temperate Eucalyptus species using UAV multispectral imagery at the tree canopy level and stand scale. The ability to spatially quantify feeding habitat using UAV imagery allows remote assessments of greater glider habitat at a scale relevant to support ground surveys, management, and conservation for the vulnerable greater glider across southeastern Australia.
Publisher: Wiley
Date: 2020
DOI: 10.1002/BES2.1807
Publisher: MDPI AG
Date: 23-02-2023
Abstract: Structural features of the overstorey in managed and unmanaged forests can significantly influence plant community composition. Native Acacia species are common in temperate eucalypt forests in southeastern Australia. In these forests, intense disturbances, such as logging and wildfire, lead to high densities of regenerating trees, shrubs, and herbs. The tree layer is dominated by Acacia and Eucalyptus, that compete intensely for resources in the first decades after stand establishment. The relative abundance and size of Acacia and Eucalyptus varies widely due to stochastic factors such as dispersal, microsite variability, and weather and climatic conditions. This variability may influence the structure and composition of the herbaceous and shrub species. In the temperate forests of southeastern Australia, understorey plant ersity is assumed to be influenced by Acacia species density, rather than Eucalyptus density. To quantify the influence of Acacia and Eucalyptus density on plant community composition, we used remote sensing and machine learning methods to map canopy composition and then compare it to understorey composition. We combined unoccupied aerial vehicle (UAV or drone) imagery, supervised image classifications, and ground survey data of plant composition from post-logging regrowth forests in the Central Highlands of southeastern Australia. We found that aggregation and patch metrics of Eucalyptus and Acacia were strongly associated with understorey plant beta ersity. Increasing aggregation of Acacia and the number of Acacia patches had a significant negative effect on plant beta ersity, while the number of Eucalyptus patches had a positive influence. Our research demonstrates how accessible UAV remote sensing can be used to quantify variability in plant bio ersity in regrowth forests. This can help forest managers map patterns of plant ersity at the stand-scale and beyond to guide management activities across forested landscapes.
Publisher: Frontiers Media SA
Date: 11-02-2022
Abstract: Land-use change has progressed rapidly throughout the Indonesian archipelago and is now intruding into western New Guinea (Tanah Papua), one of the world’s last wilderness areas with extensive tracts of pristine and highly erse tropical rainforests. Tanah Papua has reached a crossroads between accelerating environmental degradation and sustainable development policies entailing landscape-scale conservation targets, pledged in the Manokwari Declaration. We assessed the representation of ecoregions and elevational zones within Tanah Papua’s protected area network to identify its shortcomings at broad spatial scales. Lowland ecoregions are less protected than mountainous regions, with half of the western and southern lowlands designated for land-use concessions. Under the direct threat from land-use change, the political motivation in Tanah Papua toward conservation- and culture-centered land management provides a window of opportunity for scientifically guided, proactive conservation planning that integrates sustainable development for the benefit of Indigenous communities.
No related grants have been discovered for Benjamin Wagner.