Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar

A Scoping Review of Urban Planning Decision Support Tools and Processes That Account for the Health, Environment, and Economic Benefits of Trees and Greenspace

Compelling evidence shows that trees and greenspaces positively impact human well-being and the environment and offer economic benefits. Nevertheless, there exists a knowledge gap regarding the extent to which this evidence is efficiently incorporated into existing urban planning decision-making processes. This scoping review identified the extent to which urban planning decision-making frameworks, models, and tools consider the health, environmental, and economic benefits of trees and greenspace. Out of 28 reviewed studies, 11 (39%) reported on frameworks, models, and tools that take into account the health, environmental, and economic dimensions of trees and greenspace. Additionally, seven studies provided comprehensive coverage of at least one of the three key dimensions. However, none of the decision support frameworks, models, or tools comprehensively integrated all three dimensions, with only two tools (7%) scoring above 50% (five or more out of nine) in terms of comprehensiveness. This review highlights the urgent need to incorporate the true economic and monetary values of the health and environmental benefits of trees and greenspace to inform urban development decision making.

Feedback loops between 3D vegetation structure and ecological functions of animals

Ecosystems function in a series of feedback loops that can change or maintain vegetation structure. Vegetation structure influences the ecological niche space available to animals, shaping many aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. However, most studies concerning three-dimensional vegetation structure and animal ecology consider only a single direction of this relationship. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism. We also show how remote sensing and animal tracking technologies are now available at the global scale to describe feedback loops and their consequences for ecosystem functioning. An improved understanding of how animals interact with vegetation structure in feedback loops is needed to conserve ecosystems that face major disruptions in response to climate and land-use change.

Drawing transformation pathways for making use of joint effects of food and energy production with biodiversity agriphotovoltaics and electrified agricultural machinery

The achievement of the Sustainable Development Goals is being pursued worldwide. While energy production and consumption are to be oriented towards renewable energies, ecologically and socially sustainable agriculture is also a target for science and society. Due to the expansion of renewable energies, agricultural land in particular is the focus of various interest groups, from food production to energy production. In this interdisciplinary study, we show the opportunities and limits of joint synergies from the nexus of food production, energy production, energy consumption, biodiversity protection and social acceptance of renewable energies in a scenario. Biodiversity agriphotovoltaics, i.e. agriphotovoltaics in combination with biodiversity protection measures, such as flower strips, can make a valuable contribution to promoting biotope connectivity in addition to significant energy production. We show this in a GIS-based regional assessment for Lower Saxony in northern Germany. This rough spatial assessment is followed by a modelling of energy production and consumption during the cultivation of a characteristic agricultural field in the loess region of Lower Saxony. Our focus here is on the possibilities of using cable electricity or battery storage for carrying out the cultivation. In an accompanying survey of farmers regarding the use of agriphotovoltaics, we collected and evaluated their prior knowledge, experiences, and attitudes towards this technology. Finally, we show which advantages agriphotovoltaics and electrified agricultural machinery can also have for the sustainable transformation of agriculture and which challenges exist for a truly sustainable use of these technologies.

Rapid, repeatable landscape-scale mapping of tree, hedgerow, and woodland habitats (THaW), using airborne LiDAR and spaceborne SAR data

In the UK, tree, hedgerow, and woodland (THaW) habitats are key havens for biodiversity and support many related ecosystem services. The UK is entering a period of agricultural policy realignment with respect to natural capital and climate change, meaning that now is a critical time to evaluate the distribution, resilience, and dynamics of THaW habitats. The fine-grained nature of habitats like hedgerows necessitates mapping of these features at relatively fine spatial resolution-and freely available public archives of airborne laser scanning (LiDAR) data at <2 m spatial resolution offer a means of doing so within UK settings. The high cost of LiDAR prohibits use for regular monitoring of THaW change, but space-borne sensors such as Sentinel-1 Synthetic Aperture Radar (SAR at ca. 10 m resolution) can potentially meet this need once baseline distributions are established. We address two aims in this manuscript-(1) to rapidly quantify THaW across UK landscapes using LiDAR data and (2) to monitor canopy change intra- and inter-annually using SAR data. We show that workflows applied to airborne LiDAR data can deliver THaW baselines at 2 m resolution, with positional accuracy of >90%. It was also possible to combine LiDAR mapping data and Sentinel-1 SAR data to rapidly track canopy change through time (i.e., every 3 months) using, cloud-based processing via Google Earth Engine. The resultant toolkit is also provided as an open-access web app. The results highlight that whilst nearly 90% of the tallest trees (above 15 m) are captured within the National Forest Inventory (NFI) database only 50% of THaW with a canopy height range of 3-15 m are recorded. Current estimates of tree distribution neglect these finer-grained features (i.e., smaller or less contiguous THaW canopies), which we argue will account for a significant proportion of landscape THaW cover.

Ecological connectivity as a planning tool for the conservation of wildlife in cities

The application of ecological theory in urban planning is becoming more important as land managers focus on increasing biodiversity to improve human welfare in cities. Authorities must decide not only what types of biodiversity-focused infrastructure should be prioritized, but also where new resources should be positioned and existing resources protected or enhanced. Measuring the contribution of green infrastructure to landscape connectivity can maximise the successful return and conservation of urban nature. By using ecological connectivity theory as a planning tool, the effect of different interventions (both positive and negative) on the ease with which wildlife can move across the landscape can be compared. Here we outline an approach to a) quantify ecological connectivity for different urban wildlife species and b) use this to test different urban planning scenarios using QGIS. We demonstrate extensions which improve the application of this method as a planning tool:•Conversion of the effective mesh size value ( m eff ) to a "probability of connectedness" ( P c , for easier interpretation by local government and comparisons between planning scenarios).•An approach for measuring species-specific connectivity, including how to decide what spatial information should be included and which types of species might be most responsive to connectivity planning.•Guidance for using the method to compare different urban planning scenarios.

Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data

Rapid urbanization is causing changes in green spaces and ecological connectivity. So far, urban ecosystem research has mainly focused on using landscape metrics (LM) in two-dimensional (2D) space. Our study proposes three-dimensional (3D) measures of urban forests (UF) and LM calculations using LiDAR technology. First, we estimated the UF volume of Krakow (Poland) and the distribution of vegetation (low, medium, high) using a voxel-based GEOBIA approach based on the ALS LiDAR point cloud, satellite imagery, and aerial orthophotos at specific timestamps: 2006, 2012, 2017. Then, the appropriate landscape metrics were selected (NP, AREA_MN, CONTIG_MN, LPI, PARA_MN, SPLIT, MESH, PD, DIVISION, LSI) to quantify the differences between the 2D- and 3D-derived vegetation structures and detect changes in the urban landscape. The results showed that areas with low vegetation decreased due to the expansion of built-up areas, while areas with medium and high vegetation increased in Krakow between 2006, 2012, and 2017. We have shown that the lack of information on the vertical features of vegetation, i.e., 2D greenery analysis, leads to an overestimation of landscape connectivity. In the 3D vegetation classes, it was observed that low vegetation was the best connected, followed by high vegetation, while medium vegetation was dispersed in the city space. These results are particularly relevant for the urban environment, where the distribution of green space is crucial for the provision of ecosystem services.

Influence of fuel structure derived from terrestrial laser scanning (TLS) on wildfire severity in logged forests

CONTEXT

Logging and wildfire can reduce the height of the forest canopy and the distance to the understorey vegetation below. These conditions may increase the likelihood of high severity wildfire (canopy scorch or consumption), which may explain the greater prevalence of high severity wildfire in some recently logged or burnt forests. However, the effects of these structural characteristics on wildfire severity have not clearly been demonstrated.

OBJECTIVES

We aimed to assess how the structure of forests affected by logging and wildfire influence the probability of high severity wildfire.

METHODS

We used terrestrial laser scanning to measure the connectivity of canopy and understorey vegetation in forests at various stages of recovery after logging and wildfire (approximately 0-80 years since disturbance). These sites were subsequently burnt by mixed severity wildfire during the 2019-20 'Black Summer' fire season in south-eastern Australia. We assessed how these forest structure metrics affected the probability of high severity wildfire.

RESULTS

The probability of high severity fire decreased as the canopy base height increased, and the distance between the canopy base and understorey increased. High severity wildfire was less likely in forests with taller understoreys and greater canopy or understorey cover, but these effects were not considered causal. Fire weather was the strongest driver of wildfire severity, which was also affected by topography.

CONCLUSIONS

These findings demonstrate a link between forest structure characteristics, that are strongly shaped by antecedent logging and fire, and fire severity. They also indicate that vertical fuel structure should be incorporated into assessments of fire risk.

Connectivity assessment and prioritization of urban grasslands as a helpful tool for effective management of urban ecosystem services

Urban grasslands are usually managed as short-cut lawns and have limited biodiversity. Urban grasslands with low-intensity management are species rich and can perform numerous ecosystem services, but they are not accepted by citizens everywhere. Further, increasing and/or maintaining a relatively high level of plant species richness in an urban environment is limited by restricted plant dispersal. In this study, we examined the connectivity of urban grasslands and prioritized the grassland patches with regard to their role in connectivity in an urban landscape. We used high-resolution data from a land use system to map grassland patches in Wrocław city, Silesia, southwest Poland, Central Europe, and applied a graph theory approach to assess their connectivity and prioritization. We next constructed a model for several dispersal distance thresholds (2, 20, 44, 100, and 1000 m), reflecting plants with differing dispersal potential. Our results revealed low connectivity of urban grassland patches, especially for plants with low dispersal ability (2–20 m). The priority of patches was correlated with their area for all dispersal distance thresholds. Most of the large patches important to overall connectivity were located in urban peripheries, while in the city center, connectivity was more restricted and grassland area per capita was the lowest. The presence of a river created a corridor, allowing plants to migrate along watercourse, but it also created a barrier dividing the system. The results suggest that increasing the plant species richness in urban grasslands in the city center requires seed addition.

What Types of Greenspaces Are Associated with Depression in Urban and Rural Older Adults? A Multilevel Cross-Sectional Study from JAGES

Depression in older adults is a public health challenge. We aimed to clarify the relationship between depression in older adults and three types of neighborhood greenspaces: trees, grasslands, and fields. We utilized data from the Japan Gerontological Evaluation Study (JAGES) performed in 2016. Multilevel logistic regression analysis was used for non-stratified and stratified analyses for the urban–rural regions. The target population comprised 126,878 older adults (age ≥ 65 years) who responded to the depression questions and were living in 881 neighborhoods in Japan. Depression was diagnosed based on a Geriatric Depression Scale score ≥5, and 20.4% of the study population had depression. In the pre-stratification analysis, areas with more greenspaces revealed lower odds of depression (odds ratio (OR) 0.95, 95% confidence interval (CI) 0.85–0.95). In urban areas, more trees correlated with lower odds of depression (OR 0.94, 95% CI 0.89–1.00). In rural areas, moderate amounts of grassland were associated with lower odds of depression compared to areas with fewer grasslands (OR 0.91, 95% CI 0.83–1.00). We found that urban areas with higher tree density and rural areas with moderate amounts of grassland were associated with lower odds of depression.

A Method for Tree Detection Based on Similarity with Geometric Shapes of 3D Geospatial Data

This paper presents an approach to detecting patterns in a three-dimensional context, emphasizing the role played by the local geometry of the surface model. The core of the associated algorithm is represented by the cosine similarity computed to sub-matrices of regularly gridded digital surface/canopy models. We developed an accompanying software instrument compatible with a GIS environment which allows, as inputs, locations in the surface/canopy model based on field data, pre-defined geometric shapes, or their combination. We exemplified the approach for a study case dealing with the locations of scattered trees and shrubs previously identified in the field in two study sites. We found that the variation in the pairwise similarities between the trees is better explained by the computation of slopes. Furthermore, we considered a pre-defined shape, the Mexican Hat wavelet. Its geometry is controlled by a single number, for which we found ranges of best fit between the shapes and the actual trees. Finally, a suitable combination of parameters made it possible to determine the potential locations of scattered trees. The accuracy of detection was equal to 77.9% and 89.5% in the two study sites considered. Moreover, a visual check based on orthophotomaps confirmed the reliability of the outcomes.

The ‘GartenApp’: Assessing and Communicating the Ecological Potential of Private Gardens

Private gardens make up large parts of urban green space. In contrast to public green spaces, planning and management is usually uncoordinated and independent of municipal planning and management strategies. Therefore, the potential for private gardens to provide ecosystem services and habitat and to function as corridors for wildlife is not fully utilized. In order to improve public knowledge on gardens, as well as provide individual gardeners with information on what they can contribute to enhance ecosystem services provision, we developed a GIS-based web application for the city of Braunschweig (Germany): the ‘GartenApp’ (garden app). Users of the app have to outline their garden on a web map and provide information on biodiversity related features and management practices. Finally, they are asked about observations of well recognizable species in their gardens. As an output, the gardeners are provided with an estimate of the ecosystem services their garden provides, with an evaluation of the biodiversity friendliness, customized advice on improving ecosystem services provision, and results from connectivity models that show gardeners the role of their garden in the green network of the city. In this paper, we describe the app architecture and show the first results from its application. We finish with a discussion on the potential of GIS-based web applications for urban sustainability, planning and conservation.

Beyond Assuming Co-Benefits in Nature-Based Solutions: A Human-Centered Approach to Optimize Social and Ecological Outcomes for Advancing Sustainable Urban Planning

Urbanization deletes and degrades natural ecosystems, threatens biodiversity, and alienates people from the experience of nature. Nature-based solutions (NbS) that are inspired and supported by nature have the potential to deliver multifunctional environmental and social benefits to address these challenges in urban areas under context-specific conditions. NbS implementation often relies on a one-size-fits-all approach, although interventions that maximize one benefit (e.g., biodiversity conservation) may have no influence on, or even negatively affect, others (e.g., social justice). Furthermore, the current pathways from NbS to various benefits do not rely on a deep understanding of the underlying processes, prohibiting the identification of optimal solutions that maximize synergies across pathways. We present a comprehensive socio-ecological framework that addresses these issues by recognizing that cities are human-dominated environments that are foremost built and maintained to support humans. Our framework demonstrates how we can use experiments and niche species models to understand and predict where species will be and where people will be healthy and happy in a comparable manner. This knowledge can then be integrated into decision support tools that use optimization algorithms to understand trade-offs, identify synergies, and provide planners with the tools needed to tailor context-specific NbS to yield greener, more resilient cities with happier people and reduced inequality.