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Built environment practitioners currently seek options and opportunities to respond to the biodiversity emergency. Biodiversity Inclusive Design (BID) is an approach to design that seeks to foster functional ecological systems, enable species’ persistence within the built environment and (re) connect people with nature. BID can support designers’ quest toward biodiversity positivity. However, design projects that prioritise biodiversity are sparse and are limited to ad hoc initiatives by individual champions rather than being standard practice. Frameworks providing a structured design process to achieve biodiversity positivity already exist, but they can be difficult to find, compare and navigate. Responding to calls to further develop the concept of Biodiversity Inclusive Design, we systematically analyse 15 design frameworks compatible with BID. We explore how existing design frameworks position biodiversity as a client. For each framework, we uncover the underlying rules, ideas, beliefs, design principles and proposed structure of the design process. Through a thematic analysis, we identify re-emerging concepts and themes underpinning BID. Nested within complementary design frameworks, we conclude by positioning BID as a set of parallel processes that specifically explore biodiversitys’ perspectives (needs, preferences) and how they interact with the socio-ecological system to give a voice to biodiversity within the planning and design process. Our paper formalises BID as a practice and identifies three core dimensions of design action and nine design principles.

Laboratory tools for diagnosing taeniosis/cysticercosis in non-endemic countries are available; however, there is little data on their performance. To provide information on the sensitivity, specificity, and reproducibility of these tools, inter-laboratory studies were organized within the EU COST-Action CYSTINET (TD1302). Two serological and one coprological Ring Trials (RTs) were organized to test a panel of human-derived sera and stool samples using assays routinely conducted by the participating laboratories to detect Taenia spp. infections. Four Western blots (WBs) and five ELISAs were used by nine laboratories for cysticercosis diagnosis. In the first serological RT, the overall sensitivity was 67.6% (95% CI, 59.1–75.4), whereas specificity was 97% (95% CI, 89.8–99.6). WBs recorded the best accuracy. A second serological RT was organized, to assess the three tests most frequently used during the first RT. Two out of six laboratories performed all the three tests. The overall sensitivity and specificity were 52.8% (95% CI, 42.8–62.7) and 98.1% (95% CI, 93.2–99.7), respectively. Laboratory performance strongly affected test results. Twelve laboratories participated in the coprological RT using conventional microscopy and six laboratories used molecular assays. Traditional diagnosis by microscopy yielded better results than molecular diagnosis. This may have been influenced by the lack of standardization of molecular tests across participating laboratories.

Estimation of urban tree canopy parameters plays a crucial role in urban forest management. Unmanned aerial vehicles (UAV) have been widely used for many applications particularly forestry mapping. UAV-derived images, captured by an onboard camera, provide a means to produce 3D point clouds using photogrammetric mapping. Similarly, small UAV mounted light detection and ranging (LiDAR) sensors can also provide very dense 3D point clouds. While point clouds derived from both photogrammetric and LiDAR sensors can allow the accurate estimation of critical tree canopy parameters, so far a comparison of both techniques is missing. Point clouds derived from these sources vary according to differences in data collection and processing, a detailed comparison of point clouds in terms of accuracy and completeness, in relation to tree canopy parameters using point clouds is necessary. In this research, point clouds produced by UAV-photogrammetry and -LiDAR over an urban park along with the estimated tree canopy parameters are compared, and results are presented. The results show that UAV-photogrammetry and -LiDAR point clouds are highly correlated with R2 of 99.54% and the estimated tree canopy parameters are correlated with R2 of higher than 95%.

This paper presents the outcomes from a joint research project that aims to develop a smartphone application/online platform to model the most thermally comfortable active transport route to a planned destination using heat information and tree shading (Shadeway). Here, we provide a summary of our systematic review of academic literature and applications from the Google Play and Apple App Store, to identify current knowledge about personal adaptation strategies when navigating travel in cities during high temperatures. The review identifies that there is a lack of attention regarding the use of smartphone applications to address urban thermal comfort for active transport by government and private industry. We then present the initial results of original research from three community focus groups and an online survey that elicited participants’ opinions about Shadeways in the City of Greater Bendigo (CoGB), Australia. The results clearly show the need for better management of Shadeways in CoGB. For example, 52.3% of the routes traveled by participants suffer from either no or poor levels of shading, and 53 of the shaded areas were located along routes that also experience heavy traffic, which can have an adverse effect on perceptions and actual safety. It is expected that this study will contribute to improve understanding of the methods used to identify adaptation strategies to increasingly extreme temperatures.

Urban trees deliver many ecological services to the urban environment, including reduced runoff generation in storms. Trees intercept rainfall and store part of the water on leaves and branches, reducing the volume and velocity of water that reaches the soil. Moreover, trees modify the spatial distribution of rainwater under the canopy. However, measuring interception parameters is a complex task because it depends on many factors, including environmental conditions (rainfall intensity, wind speed, etc.) and tree characteristics (plant surface area, leaf and branch inclination angle, etc.). In the few last decades, remotely sensed data have been tested for retrieving tree metrics, but the use of this derived data for predicting interception parameters are still being developed. In this study, we measured the minimum water storage capacity (Cmin) and throughfall under the canopies of 12 trees belonging to three different species. All trees had their plant surface metrics calculated: plant surface area (PSA), plant area index (PAI), and plant area density (PAD). Trees were scanned with a mobile terrestrial laser scan (TLS) to obtain their individual canopy point clouds. Point clouds were used to calculate canopy metrics (canopy projected area and volume) and TLS-derived surface metrics. Measured surface metrics were then correlated to derived TLS metrics, and the relationship between TLS data and interception parameters was tested. Additionally, TLS data was used in analyses of throughfall distribution on a sub-canopy scale. The significant correlation between the directly measured surface area and TLS-derived metrics validates the use of the remotely sensed data for predicting plant area metrics. Moreover, TLS-derived metrics showed a significant correlation with a water storage capacity parameter (Cmin). The present study supports the use of TLS data as a tool for measuring tree metrics and ecosystem services such as Cmin; however, more studies to understand how to apply remotely sensed data into ecological analyses in the urban environment must be encouraged.