Wildlife‐habitat models are an important tool in wildlife management today, and by far the majority of these predict aspects of species distribution (abundance or presence) as a proxy measure of habitat quality. Unfortunately, few are tested on independent data., and of those that are, few show useful predictive skill. We demonstrate that six critical assumptions underlie distribution based wildlife‐habitat models, all of which must be valid for the model to predict habitat quality. We outline these assumptions in a meta‐model, and discuss methods for their validation. Even where all six assumptions show a high level of validity, there is still a strong likelihood that the model will not predict habitat quality. However, the meta‐model does suggest habitat quality can be predicted more accurately if distributional data are ignored, and variables more indicative of habitat quality are modelled instead.

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This paper documents the development and use of the VegMachine.net land cover monitoring tool. From 2002 to 2015, VegMachine® software was used by government agencies, natural resource management (NRM) groups and individual pastoralists in northern Australia to assess and benchmark vegetation cover levels. In 2016 the VegMachine.net website was launched to build a wider user base and assure service continuity. Users can now graph historical (1990–) cover on one or more user defined areas of interest (AOI), produce comprehensive paddock-by-paddock property monitoring reports, and view a range of land cover raster images through the website map panel. In its first 32 months of operation 913 users logged 1604 sessions on the website and more than 1000 of the website’s most comprehensive monitoring reports were distributed to users. Levels of use varied; 26% of users (n = 237) have used the website more than once, and within this group a smaller set of regular users (n = 36) have used the site more than five times, in many cases to provide analyses to multiple clients. We outline four case studies that document the significant impact VegMachine.net has had on users including graziers, government agencies, NRM groups and researchers. We also discuss some possible paths forward that could widen the user base and improve retention of first time users.

Producer reliance on drought subsidies instead of proactive planning and timely destocking in low rainfall years has prompted Queensland government investment in promoting business and drought resilience. GrazingFutures (AU$6 million budget, 2016-2022) is an extension project focussed on enhancing business management skills of extensive livestock producers in western Queensland, Australia. The region's rangelands are in productivity decline, span 1 million km 2 and are managed by graziers operating more than 2400 livestock businesses (beef, sheep and goats). The Queensland Department of Agriculture and Fisheries delivers GrazingFutures as a component of the Drought and Climate Adaptation Program, in partnership with regional natural resource management groups and other public and private organisations. Project delivery emphasised upskilling multi-agency staff and livestock producers to promote practice change within three whole of business themes: (1) grazing land management; (2) animal production; and (3) peoplebusiness. Three independent surveys (2018, 2019, 2020) indicated positive practice change was occurring in grazing businesses as a consequence of the project. Graziers instigated management changes even under major environmental challenges including extended drought (2013-2020), an extreme flood event in 2019 and the COVID-19 pandemic in 2020. This paper details the rationale, progress against the objectives, challenges and future direction of the GrazingFutures extension project.