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Celebrating our achievements

Science New Zealand Awards

Science NZ Award winners

Anne Sutherland, James Shepherd, David Pairman (LUM team); Dan Richards (Early Career Researcher), Stella Belliss (LUM team), Chris Phillips (Individual/Lifetime Achievement)
Missing: Laise Harris, Graeme Curwen, James Ardo, Anne Sutherland, Brent Martin, Christine Martelletti. (LUM team)

At the annual Science New Zealand Awards in Wellington in December 2023, Dr Chris Phillips was awarded an Individual/Lifetime Achievement for his professional expertise in the fields of erosion research and integrated catchment management. Climate-smart landscape researcher Dr Dan Richards was recognised as an Early Career Researcher for his work towards understanding how terrestrial landscapes can support climate adaptation in Aotearoa whilst integrating objectives of climate mitigation, biodiversity conservation, and multiple benefits to people. Our Land Use and Carbon Analysis System (LUCAS) Land Use Mapping (LUM) team received an award for their significant update to LUM 2020 which utilised significant advances in automation, AI and machine learning.

Susan Wiser

Susan Wiser

Susan Wiser

Dr Susan Wiser was the 2023 winner of Te Tohu Taiao – Award for Ecological Excellence –conferred by the New Zealand Ecological Society at its annual conference. This award is presented annually to recognise individuals who have made an outstanding contribution to the study and application of ecological science. Susan has made an impressive contribution to the development of the National Vegetation Database.

Marion Donald

Marion Donald

Marion Donald

Postdoctoral scholar Dr Marion Donald has been awarded a Rutherford Foundation Postdoctoral Fellowship for research titled ‘A trait-based approach for predicting conservation status of Aotearoa New Zealand’s pollinators’ Using ‘trait-based ecology’. Marion’s project focuses on two key pollinator groups in Aotearoa New Zealand – flies and bees. This work will generate new information for data-deficient species and integrate prior data to build Aotearoa-specific models.