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10/25/11 Australian case study: the Greater Blue Mountains World Heritage Area THINK.CHANGE.DO Dr Daniel Ramp Senior Lecturer School of the Environment Australian case study Climate trends in Australia - Rainfall 1 10/25/11 Australian case study Climate trends in Australia - Topography • 99% of the Australian con2nent < 1000 m • Limited scope for al2tudinal migra2on as climate zones shi< Australian case study Climate trends in Australia - Fire • Vegeta2on in all but we@est areas very fire‐prone • 5% of land surface burnt each year (up to 50% in north) • Future fire regimes effected by: – Temperature – Rainfall – Fuel loads (CO2) • Very difficult to predict 2 10/25/11 Australian case study Issues of scale Australian case study World Heritage site listings • Cultural • Australian Convict Sites (2010) • Royal Exhibition Building and Carlton Gardens (2004) • Sydney Opera House (2007) • Natural • Australian Fossil Mammal Sites (Riversleigh / Naracoorte) (1994) • Fraser Island (1992) • Gondwana Rainforests of Australia (1986) • Great Barrier Reef (1981) • Greater Blue Mountains Area (2000) • Heard and McDonald Islands (1997) • Lord Howe Island Group (1982) • Macquarie Island (1997) • Ningaloo Coast (2011) • Purnululu National Park (2003) • Shark Bay, Western Australia (1991) • Wet Tropics of Queensland (1988) • Mixed • Kakadu National Park (1981) • Tasmanian Wilderness (1982) • Uluru-Kata Tjuta National Park (1987) • Willandra Lakes Region (1981) 3 10/25/11 Park management framework Where do we want to be? Experience Did we achieve what we planned and should we change? Management Objec2ves Management and Evalua2on Park Policy How to translate into departmental ac2on? Outcomes What did we do and what services or products were produced? What did we achieve? Outputs How to get there? How do we go about it? Research Context Planning Inputs What do we need? Management Processes Australian case study Hierarchical adaptive management Vision Objec2ves Biodiversity objec2ves Thresholds of poten2al concern Indicators and modelling 4 10/25/11 Ecological condi2on Australian case study Measurement indicators and management intervention Upper and lower thresholds (TPCs) Time Management interven2on 2007‐2009 Managing for ecosystem change in the Greater Blue Mountains World Heritage Area ARC LP0774833 5 10/25/11 What is the GBMWHA? GBMWHA 1.03 million hectares Land tenure What do we 8 protected areas Where is it? have? Na2ve 2tle Reserves subject to claims What do Co‐management What are the strategy plan ecosystems unknowns? require? Adjacent land use Perimeter approximately 5,000 km What impact What can Freehold, protected do threats areas and Crown managers do? have? reserves ARC LP0774833 Greater Blue Mountains World Heritage Area Contrasting values Bequest, inspira2on, spirituality Biodiversity Geodiversity Scenic and aesthe2c Research and educa2on Water catchment GBMWHA Values Social and economic Indigenous values Historic values Wilderness Recrea2on and tourism 6 10/25/11 Greater Blue Mountains World Heritage Area Contrasting threatening processes • Invasive species – Over 40 plants – 15 animals • Fire – Days with high fire risk – Increase in frequency and size (without management) • Urban expansion • Pollu2on • Fragmenta2on/habitat loss Greater Blue Mountains World Heritage Area Climate trends for the GBMWHA Parameter Projec*ons to 2050 Source Temperature • Increase in mean min and max temperature by 1 – 3oC DECCW 2009 (A2) CSIRO 2007 • Increase in number of hot days over 35oC • More hot days/nights and fewer cold days/night, CSIRO 2007 o including fewer frost days below 0 C Rainfall • No change in autumn • 10 – 20% decrease in winter rainfall. Slightly drier winter due to higher temperatures and increased evapora2on DECCW 2009 • 5 – 10% increase in spring rainfall. Slightly drier spring due to higher temperatures and increased evapora2on • 20 – 50% increase in summer rainfall. We@er summer Evapotranspira*on • Increase across region CSIRO 2007 Bushfire • Risk likely to increase across region CSIRO 2007 Sea level rise • Increase 40 cm by 2050 and 90 cm by 2100, rela2ve to DECCW 2009 1990 sea level Atmospheric CO2 • Increase IPCC 2007 7 10/25/11 Greater Blue Mountains World Heritage Area Project themes Future scenarios Sta2s2cal modelling Species distribu2ons Endemism Dispersal Fire regimes Climate change Hotspots Representa2on Efficacy Land acquisi2on Data collec2on Reserve design Diversity Invasive species Decision making Surrogacy Survey efficiency ARC LP0774833 Adap2ve management Park management Risk minimisa2on Weeds ‐ Lantana Carnivore interac2ons Collaborators Greater Blue Mountains World Heritage Area Collaborators • Chief inves2gators – – – – – – – – – • Dr Daniel Ramp (BEES, UNSW) Prof. Richard Kingsford (BEES, UNSW) Dr Shawn Laffan (BEES, UNSW) Dr David Warton (Maths, UNSW) A/Prof. John Merson (IES, UNSW) Prof. Ross Bradstock (UoW) A/Prof. Robert Mulley (UWS) Dr Tony Auld (DECCW) Dr Rosalie Chapple (BMWHI) Partners – NSW Office of Environment and Heritage – NSW Department of Primary Industries – Hawkesbury‐Nepean CMA – Blue Mountains City Council – Blue Mountains World Heritage Ins2tute • Research staff – – – – – • Daniel Ramp (Research Fellow) Evan Webster (Research Assistant) Erin Roger (Research Assistant) Tom Colley (Research Assistant) Kun Zhang (Post‐doc) Research students – – – – – – – – – Fiona Thomson (PhD) Gilad Bino (PhD) Jack Pascoe (PhD) Alex Gold (PhD) Ian Renner (PhD) Alex Gold (MPhil) James Mar2n (MEM) Melissa Head (Hons) Leah Shepherd (Hons) ARC LP0774833 8 10/25/11 Greater Blue Mountains World Heritage Area Research examples on climate change 1. Endangered ecological communi2es – Upland swamps 2. Individual species and community composi2on – Plants in the family Myrtaceae 3. Vulnerability within sites – Microrefugia 4. Reserve adequacy – Communi2es of species 5. Risk to ecosystem services – Catchment water yield Greater Blue Mountains World Heritage Area 1. Upland swamps • Prominent on steep valley sides, where water exits the ground between sandstone and claystone rock layers • Extent varies due to changes in rainfall/evapora2on • Porous sandstone layered with impermeable ironstone and shale belts • Water flows through sandstone, but the hard ironstone forces it to the surface 9 10/25/11 How might conditions change in the future? Which swamps are likely to be susceptible? How can mitigation strategies be optimised? 1. Upland swamps Climate change and upland swamps Higher summer rainfall Rainfall Drier in winter and spring Drier ground Geomorphology Physical features Hydrology Biota Weed source Erosion Soil organisms affected Less infiltra2on Some plants ok Temperature Al2tude range 500 – 950 m Lower eleva2ons first Geomorphology important Fauna impacted More frequent Fire More intense No more than once every 12 years Peatland burning Erosion Lower water table 10 10/25/11 1. Upland swamps Benefits of modelling • Predic2on – A model can iden2fy unknown areas where a habitat may occur • Explana2on – A model can help to explain why a habitat exists where it does (i.e. how it responds to the environment) • Projec2on – A model can incorporate different climate scenarios to predict where a habitat may thrive in the future 1. Upland swamps Niche modelling Upland swamp Niche envelope m Te all inf Ra / re tu ra pe Look for a sta2s2cal rela2onship between where upland swamps exist and environmental and clima2c variables – their niche Model suggests where condi2ons for swamps may change Provides a mechanism for assessing risk to swamp communi2es 11 10/25/11 Number of swamps within suitable niche 1. Upland swamps Swamps at risk 1600 1400 1469 1469 1398 1469 1368 1278 1211 1200 1288 35% at risk 956 1000 800 2000 600 2030 2050 400 200 0 B1 A1B A1FI IPCC Scenario 1. Upland swamps Web visualisation of simulations 12 10/25/11 2. Individual species Family Myrtaceae – Key Outstanding Value • Contains the Eucalypts: Eucalyptus, Corymbia, Angophora (127 species) • 29 genera, 293 species • Trees or shrubs • Most diverse family in the region 2. Individual species Endemism • Many species have very narrow clima2c and geographic ranges – 53% eucalypt species clima2c ranges <3oC – 25% span <1oC 13 10/25/11 Species distribu2on modelling 2. Individual species Species distributions 2050 medium emission scenario (A1B) * 5% reduction in annual rainfall * 1.5 degree rise in minimum temperature * 2 degree rise in maximum temperature Angophora bakeri Angophora costata 2. Individual species Climate change Current condi2ons 268 species suitability models 200,000,000 data points Computer array 2030 medium emission scenario (A1B) 2 % reduc2on in annual rainfall 1 degree rise in minimum temperature 0.6 degree rise in maximum temperature 2050 medium emission scenario (A1B) 5 % reduc2on in annual rainfall 1.5 degree rise in minimum temperature 2 degree rise in maximum temperature 14 10/25/11 3. Microrefugia Biodiversity corridors • Biodiversity corridors – large spa2al areas of con2guous habitat, or core areas – connected by habitat linkages to meet their natural ecological and behavioural requirements • Design – can be con2nuous strips of land or 'stepping stones' that are patches of suitable habitat – providing func2onal linkages between core protected areas s2mula2ng or allowing species migra2on between areas Great Eastern Ranges Ini2a2ve • A response to mi2gate the impacts of climate change, and other threats • It will strengthen conserva2on management and connec2vity of natural lands along the great eastern ranges conserva2on corridor 15 10/25/11 3. Microrefugia Refugia = resilience • Nature of biodiversity is dynamic • Protect loca2ons that are important for ongoing ecological and evolu2onary processes • Refugia are loca2ons that have stable and unusual climates with intrinsic conserva2on value because they – buffer species from climate variability and therefore enhance the ability of species to persist when the climate is unsuitable elsewhere – foster gene2c isola2on that can enhance evolu2onary processes; and – enhance the diversity of environmental condi2ons and thus increase the poten2al for higher biodiversity A novel approach to quantify and locate microrefugia using topoclimate, climate stability, and isolation from the matrix – Global Change Biology 3. Microrefugia Macrorefugia Macrorefugia 16 10/25/11 3. Microrefugia How to map microrefugia • To iden2fy the poten2al loca2on of microrefugia need to quan2fy areas that: – have the lowest or highest temperatures when assessed using fine‐scale topoclima2c grids – have rela2vely stable climates; and – are dis2nctly different from the climate in the surrounding area 3. Microrefugia Fine scale topoclimate information ! 17 10/25/11 3. Microrefugia Wollemi region microrefugia 95th percen*le of maximum temperature gradient 5th percen*le of minimum temperature gradient ! ! 3. Microrefugia Prioritisation and adequacy • Refugia could be included in adequacy assessments • Alloca2on of resources for ac2ons need to be op2mised – Tools to priori2se values spa2ally are very useful in decision making – Have the capacity to be turned into simple end‐ user products – Can incorporate trigger points 18 10/25/11 Macrorefugia 4. Community responses to climate change Community aggregations Incorporating climate refugia for faunal assemblages in assessments of protected area adequacy – Journal of Biogeography Macrorefugia 4. Community responses to climate change Community responses 19 10/25/11 Macrorefugia 4. Community responses to climate change Climate relationships among communities Macrorefugia 4. Community responses to climate change Stability in communities 20 10/25/11 Site selec2on across NSW targe2ng 10% representa2on of 11 mammal assemblages within a protected area network. Colour shading represents levels of irreplaceability idenitfied by the Marxan so<ware for each of four scenarios: (a) current condi2ons building upon exis2ng protected area network; (b) current condi2ons without exis2ng network; (c) projected condi2ons for 2050 building upon exis2ng network; and (d) projected condi2ons for 2050 without the exis2ng network. Black polygons represent the exis2ng protected area network. Macrorefugia 4. Community responses to climate change Representation of communities effected by change scenarios 21 10/25/11 Australian Case Study What have we learned? • Science can inform policy within sites – Can priori2se mi2ga2on/adapta2on strategies to areas of most risk/benefit – Can op2mise configura2on of protected areas and priori2se land acquisi2on for specific threats – Need to consider range of outstanding values • Problems of uptake and knowledge transfer s2ll exist – Conflic2ng values in mul2‐tenured sites – Language barriers between managers and scien2sts – Long term collabora2ons lacking 22 10/25/11 3. Reserve Efficacy Endemism • Endemism in the Myrtaceae – To compare regional and na2onal representa2on of plant species in the family Myrtaceae – To assess spa2al representa2on of plant species in the Myrtaceae within a 100 km buffer of the WHA • How it was derived – Compared regional representa2on to na2onal ranges • Species range – 10 km cells • Species weight – Sum of the number of cells in the GBMWHA it occurs in, divided by the range • Weighted endemism – Sum of the species weights • Corrected weighted endemism – Weighted endemism divided by the number of species 3. Reserve Efficacy Corrected weighted endemism 1 1 20% of Myrtaceae species are range‐restricted to 0.9 the GBMWHA 0.8 The GBMWHA represents, on average, 20% of the range of a species that occurs within it 0.7 0.6 1 0.5 0.4 0.3 0.2 0.1 1 1 5 1 18 10 2 5 91 1 3 5 1 1 1 9 8 1 1 2 1 2 0 23 10/25/11 3. Reserve Efficacy Spatially-explicit endemism 24