Honoring the legacy of a conservation champion: Bob Pressey (1953–2023)
Bibliographic record
Abstract
On 5 July 2023, we lost a champion for conservation—Professor Robert (Bob) Pressey. His passion was a simple one—make a difference for biodiversity conservation. He fought fiercely for evidence- and outcomes-based conservation. Bob discovered (some might say invented) conservation planning in the late 1980s and quickly became one of the premier scientists in this field (Pressey, 2002). In the 1990s and early 2000s, he defined, applied, and continuously improved the framework of systematic conservation planning, providing the foundations and scientific methods used today to identify conservation priorities (Margules & Pressey, 2000; Pressey, 1994a; Pressey & Bottrill, 2008; Pressey & Cowling, 2001; Pressey et al., 1996). Through this work, he made significant contributions to establishing representative protected area networks in Australia (Ferrier et al., 2000; Pressey, 1994a), South Africa (Cowling & Pressey, 2003; Pressey et al., 2003), South Pacific (Mills et al., 2011), and beyond. His significant contributions to conservation science and practice are shown through his staunch support of and generous donations of time to the Society for Conservation Biology and other nongovernmental organizations and societies. In 2001, he received the Society for Conservation Biology's Edward T. LaRoe III Award for translating principles of conservation biology into real-world conservation. Further recognition of his contributions to conservation includes the Eureka Prize for Biodiversity Research in 2002, the New South Wales Premier's Award in 2004, the Australian Ecology Research Award in 2008, service as a governor of the World Wildlife Fund (WWF) in 2006, and election to the Australian Academy of Science in 2010 and to the Royal Society in 2022. In his academic career, when he felt his work in designing and implementing protected areas had not achieved the level of protection of biodiversity he sought, he shifted focus. He demonstrated that reserves are biased toward sites less threatened by extractive and commercial activities, which limits their effectiveness. He referred to this bias as “residual reservation.” In the last decade of his career, his attention was drawn to understanding the causes and consequences of residual reservation (Pressey et al., 2021). By understanding these and proposing solutions, he hoped conservation scientists and practitioners would be better equipped to argue for more effective protection in the future. In my youthful naivety and arrogance, I believed that scientific insights would quickly change the way conservation was done and make it more effective. I have since discovered that the path to effectiveness is longer, more winding, and bumpier than initially perceived, with many confusing detours. I get up most mornings willing to give it another go. La lutte continue. For those of us who knew and worked with Bob, he was a friend and mentor, a respected and inspiring colleague, a natural storyteller (Das, 2012; Pressey, 1994b), and the ultimate source for bad jokes and 1970s surf videos. Bob's never-ending love of the environment, dedication to his work, pursuit of irreproachable and robust science, and grit permeate his published works and continue to inspire us. Vale Bob, la lutte will continue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".