Nomenclature Wagner et al. (1999) for all native Hawaiian species; USDA ARS-GRIN (www.ars-grin.gov/ npgs/) for Megathyrsus maximus.Abstract Questions: How does potential fire behaviour differ in grass-invaded nonnative forests vs open grasslands? How has land cover changed from 1950-2011 along two grassland/forest ecotones in Hawaii with repeated fires? Location: Non-native forest with invasive grass understory and invasive grassland (Megathyrsus maximus) ecosystems on Oahu, Hawaii, USA.Methods: We quantified fuel load and moisture in non-native forest and grassland (Megathyrsus maximus) plots (n = 6) at Makua Military Reservation and Schofield Barracks, and used these field data to model potential fire behaviour using the BehavePlus fire modelling program. Actual rate and extent of landcover change were quantified for both areas from 1950-2011 with historical aerial imagery.Results: Live and dead fuel moisture content and fine fuel loads did not differ between forests and grasslands. However, mean surface fuel height was 31% lower in forests (72 cm) than grasslands (105 cm; P < 0.02), which drove large differences in predicted fire behaviour. Rates of fire spread were 3-5 times higher in grasslands (5.0-36.3 mÁmin À1 ) than forests (0-10.5 mÁmin À1 ; P < 0.001), and flame lengths were 2-3 times higher in grasslands (2.8-10.0 m) than forests (0-4.3 m; P < 0.01). Between 1950 and 2011, invasive grassland cover increased at both Makua (320 ha) and Schofield (745 ha) at rates of 2.62 and 1.83 haÁyr À1 , respectively, with more rapid rates of conversion before active fire management practices were implemented in the early 1990s.Conclusions: These results support accepted paradigms for the tropics, and demonstrate that type conversion associated with non-native grass invasion and subsequent fire has occurred on landscape scales in Hawaii. Once forests are converted to grassland there is a significant increase in fire intensity, which likely provides the positive feedback to continued grassland dominance in the absence of active fire management.
The synergistic impacts of non-native grass invasion and frequent human-derived wildfires threaten endangered species, native ecosystems and developed land throughout the tropics. Fire behaviour models assist in fire prevention and management, but current models do not accurately predict fire in tropical ecosystems. Specifically, current models poorly predict fuel moisture, a key driver of fire behaviour. To address this limitation, we developed empirical models to predict fuel moisture in non-native tropical grasslands dominated by Megathyrsus maximus in Hawaii from Terra Moderate-Resolution Imaging Spectroradiometer (MODIS)-based vegetation indices. Best-performing MODIS-based predictive models for live fuel moisture included the two-band Enhanced Vegetation Index (EVI2) and Normalized Difference Vegetation Index (NDVI). Live fuel moisture models had modest (R2=0.46) predictive relationships, and outperformed the commonly used National Fire Danger Rating System (R2=0.37) and the Keetch–Byram Drought Index (R2=0.06). Dead fuel moisture was also best predicted by a model including EVI2 and NDVI, but predictive capacity was low (R2=0.19). Site-specific models improved model fit for live fuel moisture (R2=0.61), but limited extrapolation. Better predictions of fuel moisture will improve fire management in tropical ecosystems dominated by this widespread and problematic non-native grass.
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