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Climate Change File High-resolution forest modeling in the cloud Leveraging the ASC to simulate individual tree growth across interior Alaska RCP 8.5 − Site 1103 75 Species ) 1 - a ALNUsinu h C ALNUtenu s e BETUkena n n o BETUneoa t ( 50 s LARIlari s a m PICEglau o i B PICEmari d n POPUbals u o r POPUtrem g e v 25 POPUtric o b A SALIscou 0 2000 2050 2100 2150 2200 Year Adrianna Foster, NASA Postdoctoral Fellow ABoVE Science Cloud Webinar Friday, April 20, 2018 Uncertainty in future vegetation trajectories in Alaska Greening vs. browning? Increasing fires frequency and severity? Changing permafrost? Insects? Uncertainty in future vegetation trajectories in Alaska Species- and tree-level interactions are important Fire Soils VS Ecological modeling Individual-based gap models fir spruce pine aspen Shugart 1998 Gap models use equations to simulate tree growth and response to external forces Precipitation Sunlight and temperature Disturbances Soil nutrients Soil moisture Individual tree growth annual diameter increment growth Individual tree growth annual diameter increment growth Individual tree growth Calculate optimal DBH increment growth given optimal conditions annual diameter increment growth Reduce growth based on resource availability and species tolerances Individual plots simulate gap dynamics Average of hundreds of plots produces landscape-scale output biomass (tonnes C ha-1) basal area (m2 ha-1) size structure (stems size class-1 ha-1) Application of UVAFME in interior AK Yukon River Basin – Interior AK Final products from project: 2km wall-to-wall gridded simulations across YRB ~131,000 sites Initial testing in Tanana Valley University of Virginia Forest Model Enhanced Fortran program that simulates forest growth at individual point locations 25 modules ~157,000 lines of code Initially – FAREAST (Yan & Shugart 2005) Developed for boreal Eurasia Out of similar gap-models: JABOWA, FORET, etc. 2014 – FAREAST became UVAFME (Shuman et al. 2015) Updated to Fortran 90, object-oriented, flexible structure Has since been applied within US Rocky Mountains, eastern US, Russia, Canada, and interior AK Required input data For each site/point-location: • mean monthly minimum & maximum temperature, monthly precipitation, mean monthly cloudiness • standard deviations of above climate variables • AK study: ClimateNA for temperature & precipitation; CRU for monthly cloudiness • site & soil characteristics (e.g. latitude, longitude, slope, aspect, drainage conditions, FRI, etc.) • AK study: NCSC database, SSURGO, ALFRESCO maps of fire probability • rangelist: species presence/absence • AK study: range maps from Little 1971 & Viereck & Little 2007 Wang et al. 2016 Harris et al. 2014 Hugelius et al. 2013 Mann et al. 2014 Required input data Other input data • Species input file: species-level characteristics (e.g. average maximum DBH, height, age; drought tolerance, nutrient tolerance, etc.) (Burns & Honkala 1990; Viereck & Little 2007) @ @ *, § *, § *, § Species Common Name Maximum Maximum Maximum s g DDmin DDopt DDmax *, § Age (years) DBH (cm) Height (m) *, §, ¶ *, §, ¶ Betula kenaica Kenai birch 140 30 24 1.66 1.469 300 2000 3619 Betula neoalaskana Alaskan paper 140 76 30 0.6 1.887 280 1158 2036 birch Larix laricina Tamarack 335 33 24 1.49 0.617 280 1986 3692 Picea glauca White spruce 200 76 34 0.9 1.473 280 1096 1911 Picea mariana Black spruce 250 30 27 1.87 0.918 220 1079 1911 Populus balsamifera Balsam popular 200 75 25 0.67 1.107 401 1550 2700 Populus tremuloides Quaking aspen 150 75 30 0.81 1.747 320 1371 2461 Populus trichocarpa Black 200 180 38 0.43 1.67 347 2268 4176 cottonwood Application of UVAFME in interior AK Yukon River Basin – Interior AK High number of sites requires a big(ish)- data approach to parameterization QGIS and R scripts to reduce workflow tedium and increase reproducibility Example – climate change file Convert stacks of monthly Geotiffs of climate projections to the appropriate UVAFME climate change file Example – climate change file Convert stacks of monthly Geotiffs of climate projections to the appropriate UVAFME climate change file Create difference rasters Map to point locations Put into correct format for UVAFME Optimization of this code and distribution across nodes on ASC: ~18 day run time to 30 minute run time How to run individual sites Running UVAFME ./UVAFME.exe file_list.txt file_list.txt: specifies input and output directory locations Testing: Interactive mode – command line Generally use above101-104 nodes Each site: 20-60 seconds depending on output data requirement GUI Development If command line interfaces terrify you... UVAFME Code Updates Fairbanks, AK Updates to UVAFME • Simulation of permafrost depth based on: • soil moisture & depth litter quality • climate organic layer depth • topographic effects depth of thaw • vegetation cover • Update of litter and nutrient modules: • genus- and cohort-specific decay Crown scorch (%) • Incorporation of fuels tracking and consumption • fire intensity & fuels consumption based on aridity and fuel amount Code updates based on Bonan (1989); Bonan et al. (1990); Pastor & Post (1985); Schumacher et al. (2006); Keane et al. (2011) Dry, south-facing Moist, north-facing slope: slope: Low biomass, black spruce High biomass, mixed/white spruce birch white spruce black spruce aspen black spruce Simulations at inventory sites Cooperative Forest Inventory Data (CAFI) (Malone et al. 2009) 77 sites in Yukon River Basin mostly mixed white spruce & deciduous some black spruce Gilles Creek Sites* 30 sites in Tanana Valley both black spruce and white spruce sites *Gilles Creek inventory from B. Rogers, WHRC Site type: WS Inventory Modeled 60 ) 1 - a h C s e n n Species o t 40 ( Site type: BS Site type: WS Betula neoalaskana s s a Inventory Modeled Picea glauca Inventory Modeled m o i Picea mariana B d Populus tremuloides n u o r 20 g ) ) e 1 1 v - - 60 o a a b h h A C C s 20 s e e n n n Species n Species o 0 o t t ( ( Betula neoalaskana 40 Betula neoalaskana s s s s a Picea glaucaa UVAFME updates improved agreement with inventoryPicea glauca data m m o o i Picea mari iana Picea mariana B B d 10 Populusd tremuloides Populus tremuloides n n u Blacku Spruce20 Sites: n = 22 o o r r g g e e v v o o b b A A 0 0 a a a s a a a s a a a s a a a s n c n e n c n e n c n e n c n e a u a d a u a d i i i i a u ia id a u ia id k la r o k la r o k a r k a r s l s l l lo l lo g a g a s g a s g a la u la u a u a u a m a m l m l m a m a m a a m a a m e a e a e e o c e o c e o a e o a e e i e r e i e r c e r c e r t t e i t e i t n P ic n P ic c c s s n P i s n P i s a P u a P u P P l l l l la lu la lu u u tu tu u u u u p p t p t p e o e o e e B B o o P P B P B P White Spruce Sites: n = 8 CAFI Modeled 60 ) 1 - a h Species C s Betula kenaica e 40 n n Betula neoalaskana o t ( Larix laricina s s a Picea glauca m o i Picea mariana B d Populus balsamifera n u 20 o Populus tremuloides r g e total v o b A 0 UVAFME updates improved agreement with inventory data l l a a a a a a s a a a a a a s a a r r c n n c n e t c n n c n e t i i i i e e a u a f d o a u a f d o a c i i i t a c i i i t i i k a r k a r n r l o n r l o s l s l a m a m e a g e a g l u l u a a a a k l k l m m a s a s a x l m a x l m i i a e a e l a l a o r a e o r a e c r c r u i e u i e e a b t e a b t t t c c L L n P i n P i e s s e s s P P B a u u B a u u l l l l l l u u u u u u t t p p p p e e o o o o B B P P P P Species Average biomass across allCAFI sites n = 77 Apply UVAFME across the Tanana Valley Climate change analyses across Tanana Gridded, wall-to-wall runs 2 km resolution ~ 35,000 sites Running multiple sites Sitelist file Allows user to specify IDs of sites to run in one simulation UVAFME will run each site in succession (sites are independent and do not interact) Distribute sites across available nodes ~50 second run * 35,000 sites =1,750,000 seconds = 29,167 minutes = 487 hours = 20 days (!!!) Across 10 nodes & 4 cores each ~ 0.5 days SLURM script for batch runs SLURM allows you to check runtime of all jobs Error files for diagnosing issues UVAFME output site_log.txt file tells me which sites have been finished Climate change: RCP 8.5 Scenario 2006 – 2100 climate change + 100 years ‘stabilization’ MAT Change: ~ +6ºC Precipitation Change: ~ +170 mm Year 2100 Year 2200 Suggests overall increase in biomass with increasing precipitation and temperatures, with pockets of biomass loss Shift towards white spruce and expansion of aspen RCP 4.5 − Site 1196 RCP 4.5 − Site 1196 60 Species ) 1 60 - a ALNUsinu h C SpeciesALNUtenu ) RCP 8.5 − Site 1103 1 s - e a BBETUkALNUsinetulaena kuenaica n h n o C BETUneoaALNUtenu t 40 Betula neoalaskana ( s e s LARIlarBETUkenai n Larix laricina s climate change n a o BETUneoa t m 40 PPICEglauicea glauca ( o 75 i s B SpeciesLARIlari ) PICEmari s Picea mariana 1 a - d a ALNUsinu n m POPUbalsPICEglau h u Populus balsamifera o i o C ALNUtenu r B PICEmari POPUtrem s g Populus tremuloides e d e 20 BETUkena n n v POPUbals n POPUtric u o o o b BETUneoa t r ( A POPUtrem g 50 SALIscou s LARIlari e 20 s v a POPUtric o m PICEglau b birch o i A SALIscou B PICEmari d n POPUbals u o 0 r POPUtrem g e white spruce v 25 POPUtric o b 2000 2050 2100 2150 2200 0 A Year aspen SALIscou 2000 2050 2100 2150 2200 Year 0 2000 2050 2100 2150 2200 Year RCP4.5 − Picea mariana 0 .
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