NESP RL Project 4.6 - Managing and monitoring for improved biodiversity outcomes using state-and-transition models
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"text": "Agricultural landscapes in Australia have historically been places of ecological decline. Habitat loss and fragmentation from land clearing, overgrazing by livestock and feral herbivores, inappropriate fire regimes and weed invasion in remnant vegetation are among the factors that pose challenges for conservation in these landscapes. Yet agricultural landscapes retain important conservation values, and new incentives for nature-positive outcomes will provide opportunities for changes in farm management that improve biodiversity outcomes.\n\nThis project is developing state-and-transition models, interactive maps and practical decision-support tools to help land managers understand how ecosystems change and identify actions that can maintain or improve their condition.\n\nThe research brings together two complementary areas:\n\ninvestigating how changes to grazing and fertiliser management can improve biodiversity in working agricultural landscapes without compromising farm production or profitability\nsafeguarding Mallee birds and their habitats in the Murray Darling Depression.\n\n**Limestone Coast state-and-transition models**\n\nState-and-transition models of the agricultural zone: flooding red gum woodland, lowland resprouting woodland and sedgelands.\n\n**Mallee Woodlands state-and-transition models**\n\nState and transition models for Mallee Woodlands of the Murray Darling Depression of south-east Australia.\n\n**Understanding how ecosystems change**\n\nState-and-transition models describe the different condition states in which an ecosystem can occur and the processes that move it from one condition state to another.\n\nFor example, an ecosystem may transition from a relatively intact state to a modified or highly modified state because of grazing, clearing, weeds, changed fire regimes or altered hydrology. Management actions such as controlling grazing, restoring vegetation, managing fire or improving hydrological conditions may support recovery.\n\nBy bringing this information together, the models can help land managers:\n* recognise ecosystem condition\n* understand the pressures driving change\n* identify possible degradation and recovery pathways\n* compare management options\n* plan monitoring, restoration and conservation activities.\n\n**Improving biodiversity in working agricultural landscapes**\n\nThe project is investigating how changes to fertiliser and grazing management may help agricultural ecosystems transition to higher biodiversity condition states.\n\nResearch is taking place across approximately 10–12 farms in each of three regions:\n* Tasmanian Midlands\n* Western Victorian Volcanic Plains\n* Limestone Coast.\n\nThe research compares paddocks with different histories of fertiliser use and grazing management. It measures ecosystem condition and biodiversity indicators, including plants, selected invertebrate groups, bats, birds and soils.\n\nThe findings will be used to update and validate regionally specific state-and-transition models and develop:\n* a monitoring framework for assessing ecosystem condition in production areas\n* practical advice for landholders seeking to improve biodiversity and landscape resilience\n* stronger evidence for sustainability reporting, natural-capital accounting and emerging nature markets.\n\n**How the research supports conservation action**\n\nThe project’s models, reports and interactive maps will help land managers and decision-makers understand how management affects biodiversity and ecosystem condition.\n\nThe research can support:\n* Mallee bird habitat management\n* grazing, fire and vegetation management planning\n* restoration planning\n* biodiversity and natural-capital monitoring on farms\n* assessment of changes to farming practices\n* biodiversity incentives, nature markets and sustainability reporting.\nBy linking management actions with ecological outcomes, the project will support better conservation and sustainable agriculture decisions.",
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