Designing cities for everyday nature.

The motivations for incorporating nature into the design of cities have never been more compelling. Creating experiences with nature that occur every day (everyday nature) in cities could help reverse the fate of many threatened species and connect people with nature and living cultural traditions. However, this requires more than just urban greening; it involves ensuring daily doses of nature in a way that also supports nonhuman organisms. A major shift in the way nature is conceived of and is made part of the design of cities is required. Principles include reconsidering nature as a development opportunity rather than a constraint and eliminating offsetting of biodiversity site values. Processes include using biodiversity-sensitive design frameworks and establishing meaningful professional engagement among ecologists, planners, and designers. Challenges include design obstacles, conflicts between nature and people (e.g., safety, disease, and noise) that require careful management, and socioeconomic and political considerations (e.g., Global North vs. Global South). Research to interrogate the multiple benefits of nature in cities can complement experimental interventions, ultimately supporting better urban design and creating much more resiliently built environments for people and nature.

Diseño de ciudades para la naturaleza cotidiana Resumen Los motivos para incorporar a la naturaleza dentro del diseño urbano jamás habían sido tan convincentes. La creación en las ciudades de experiencias con la naturaleza que ocurren a diario (naturaleza cotidiana) podría ayudar a cambiar el destino de muchas especies amenazadas y conectar a las personas con la naturaleza y las tradiciones culturales vivientes. Lo anterior requiere más que reverdecimiento urbano ya que involucra dosis diarias de naturaleza de manera que también mantengan a los organismos no humanos. Se necesita de un cambio mayor en la manera en la que se concibe a la naturaleza y cómo se le hace parte del diseño urbano. Los principios incluyen reconsiderar a la naturaleza como una oportunidad de desarrollo en lugar de una limitación y eliminar la compensación del valor de los sitios de biodiversidad. Los procesos incluyen el uso de marcos de diseños sensibles con la biodiversidad y el establecimiento de una participación profesional significativa entre los ecologistas, los planeadores y los diseñadores. Los retos incluyen los obstáculos del diseño, conflictos entre la naturaleza y las personas (seguridad, enfermedades y ruido) que requieren de un manejo cuidadoso y consideraciones políticas (Norte Global versus Sur Global). La investigación para interrogar los múltiples beneficios de la naturaleza en las ciudades puede complementar a las intervenciones, a la larga respaldando un mejor diseño urbano y creando ambientes para las personas y la naturaleza construidos con mayor resiliencia.

Consistent patterns of vehicle collision risk for six mammal species.

The occurrence and rate of wildlife-vehicle collisions are related to both anthropocentric and environmental variables, however, few studies compare collision risks for multiple species within a model framework that is adaptable and transferable. Our research compares collision risk for multiple species across a large geographic area using a conceptually simple risk framework. We used six species of native terrestrial mammal often involved with wildlife-vehicle collisions in south-east Australia. We related collisions reported to a wildlife organisation to the co-occurrence of each species and a threatening process (presence and movement of road vehicles). For each species, we constructed statistical models from wildlife atlas data to predict occurrence across geographic space. Traffic volume and speed on road segments (also modelled) characterised the magnitude of threatening processes. The species occurrence models made plausible spatial predictions. Each model reduced the unexplained variation in patterns and distributions of species between 29.5% (black wallaby) and 34.3% (koala). The collision models reduced the unexplained variation in collision event data between 7.4% (koala) and 19.4% (common ringtail possum) with predictor variables correlating similarly with collision risk across species. Road authorities and environmental managers need simple and flexible tools to inform projects. Our model framework is useful for directing mitigation efforts (e.g. on road effects or species presence), predicting risk across differing spatial and temporal scales and target species, inferring patterns of threat, and identifying areas warranting additional data collection, analysis, and study.

A simple framework for a complex problem? Predicting wildlife-vehicle collisions.

Collisions of vehicles with wildlife kill and injure animals and are also a risk to vehicle occupants, but preventing these collisions is challenging. Surveys to identify problem areas are expensive and logistically difficult. Computer modeling has identified correlates of collisions, yet these can be difficult for managers to interpret in a way that will help them reduce collision risk. We introduce a novel method to predict collision risk by modeling hazard (presence and movement of vehicles) and exposure (animal presence) across geographic space. To estimate the hazard, we predict relative traffic volume and speed along road segments across southeastern Australia using regression models based on human demographic variables. We model exposure by predicting suitable habitat for our case study species (Eastern Grey Kangaroo Macropus giganteus) based on existing fauna survey records and geographic and climatic variables. Records of reported kangaroo-vehicle collisions are used to investigate how these factors collectively contribute to collision risk. The species occurrence (exposure) model generated plausible predictions across the study area, reducing the null deviance by 30.4%. The vehicle (hazard) models explained 54.7% variance in the traffic volume data and 58.7% in the traffic speed data. Using these as predictors of collision risk explained 23.7% of the deviance in incidence of collisions. Discrimination ability of the model was good when predicting to an independent dataset. The research demonstrates that collision risks can be modeled across geographic space with a conceptual analytical framework using existing sources of data, reducing the need for expensive or time-consuming field data collection. The framework is novel because it disentangles natural and anthropogenic effects on the likelihood of wildlife-vehicle collisions by representing hazard and exposure with separate, tunable submodels.