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Abstract: Detailed and reliable information about the spatial distribution of species provides critical information for effective conservation planning. In Victoria, Australia, this responsibility is held by the Department of Sustainability and Environment, which maintains and curates a database of site records for species: the Victorian Biodiversity Atlas. But the information is provided in point form, and therefore, it does not provide an adequate view of species distributions for all management purposes. By integrating known occurrences of species with environmental GIS data layers using a machine learning algorithm, random forest, we have built species distribution models for 523 vertebrate fauna species across the whole state, providing predictive ‘maps’ that are available for use in various conservation planning activities. In this paper, we introduce and discuss the methods we developed and implemented for producing these models. Specifically, 26 explanatory variables were used for the modelling; three versions of models were built using different sets of explanatory variables; pseudo-absences were chosen by filtering random points with a profile model; model accuracy was assessed using several measures, especially lift curve-related ones; a threshold was selected for each model to transform continuous result to binary one by maximizing the sum of sensitivity and (pseudo) specificity, which was proved to be valid for presence-only data. [Copyright &y& Elsevier]

Despite growing interest in promoting urban biodiversity conservation, there are few concrete examples of how nature stewardship initiatives can be rapidly scaled, in number and across landscapes. This paper explores the factors that promote or inhibit the proliferation and impact of collaborations between citizens and their local governments that involve residents in municipal biodiversity conservation efforts in their gardens (wildlife gardening). We studied the Gardens for Wildlife Victoria network in Australia, which supports citizen-agency co-development of municipal wildlife gardening programs. In three years the network has expanded from one program to 39 initiatives in various developmental stages in 49% of the local government areas in the state of Victoria. Data are drawn from 21 semi-structured interviews of network participants running or developing programs in 12 municipalities, complemented by a survey of 33 network participants, and participants' evaluation of network workshops. We find that scaling occurs in four different domains of policy, values, locales and participants. Scaling is influenced by six interlinked factors: empowerment of actors; a civil-agency co-design and delivery model; conservation framing; links to and between landscapes and communities; resources – particularly time; and the network's role in promoting innovation and shared learning. Key barriers include short-term, top-down, and monetary agency foci; conservation framed as the principal domain of specialists and professionals; and prioritisation of listed species rather than local species more broadly. We present a framework for considering scaling of biodiversity stewardship and related factors. • Case study shows how biodiversity stewardship collaborations multiply among cities. • Programs are designed to link public and private land stewardship. • Stewardship programs, locales, policies, and values are spread. • Leaders are empowered by belief in impact, meaning, competence, choice. • Enablers are a network, citizen-agency codesign, inclusivity, place-based links. [ABSTRACT FROM AUTHOR]