Lisa M. Ellsworth

Abstract Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform ( https://rangelands.app/ ), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

Abstract Questions How does a highly degraded H awaiian tropical dry lowland ecosystem dominated by the non‐native invasive M egathyrsus maximus (guinea grass) respond to different restoration treatments (three native species outplanting treatments; four native broadcast seed treatments)? What effect do restoration treatments have on invasive and native species groundcover, biomass and physiological activity, and volumetric soil water content? Location Waianae K ai F orest R eserve, I sland of O ahu, H awaii, USA . Methods The invasive grass M . maximus was suppressed by initial mowing and pre‐ and post‐planting herbicide applications. Native species were added in three outplant and four broadcast seed treatments in a complete randomized block design. Native species and M . maximus growth and ecophysiology, and volumetric soil water content were quantified for 8 mo following treatment establishment. Results Native species outplant survival ranged from 38% to 67%. Cover of M . maximus was significantly reduced in all outplant treatments compared with control and treated control (mowing and herbicide without native species additions), but did not differ across outplant treatments. Of the native species, D odonaea viscosa biomass was higher than C ordia subcordata , while other native species did not differ. Maximum photosynthetic rates ( A max ) did not differ across species in J uly. However, in A ugust (drier period), M . maximus exhibited lower A max than all native species except T . populnea , indicating adaptive dormancy during drought. Broadcast seeding with native species was not an effective restoration treatment, as field germination ranged from 0.5% to 2.3%. Conclusions Ecological restoration of highly invaded H awaiian tropical dry lowland ecosystems can be mediated through aggressive invasive species suppression and native species outplanting. Recommendations for restoration include initial removal of invasive grasses, adaptive suppression of grasses post‐outplanting, and utilization of diverse native species assemblages that are ecophysiologically adapted to local conditions and competitive with M . maximus .

Abstract Recent policy has focused on prevention of wildfire in the sagebrush steppe in an effort to protect habitat for the greater sage grouse ( Centrocercus urophasianus ). Historically, fire return intervals in Wyoming big sagebrush ( Artemisia tridentata ssp. wyomingensis ) ecosystems were 50–100 yr or more, but invasive species, climate change, and a legacy of intensive grazing practices have led to degraded rangeland condition, altered fire regimes and fire effects, and declines in sagebrush cover. Little is known about the long‐term impacts of fire in this ecosystem in areas where grazing pressure has been removed, few invasive species exist, and fire return intervals are maintained. In this study, we quantified vegetation composition prior to prescribed burning, 1 year following fire, and 17 years after fire in a native‐dominated Wyoming big sagebrush ecosystem at Hart Mountain National Antelope Refuge, Oregon, United States. Seventeen years following fire, the ecosystem was dominated by native herbaceous vegetation, with 8.3% cover of broad‐leaved forbs and bunchgrasses in the understory, compared to just 3.8% cover of native herbaceous vegetation in unburned controls. Invasive annual grass cover ranged from 0.2% to 8.4% across all treatments and years ( P = 0.56). One year following fire, the distance from a randomly located point and the nearest mature sagebrush was 16.6 m, but by 17 years after the fire, that distance had decreased to 2.5 m. Seventeen years after fires, shrub cover was 0.4–4% in burned plots compared to 13–24% in unburned controls. Collectively, these data demonstrate that good condition ungrazed Wyoming big sagebrush plant communities exhibited resilience following fire and maintained a native‐dominated mosaic of shrubs, bunchgrasses, and forbs. Further, unburned control plots were dominated by woody vegetation and exhibited losses in herbaceous understory, possibly indicating that they are outside of their natural fire return interval. Our results illustrate that management of all habitat components, including natural disturbance and a mosaic of successional stages, is important for persistent resilience and that suppression of all fires in the sagebrush steppe may create long‐term losses of heterogeneity in good condition Wyoming big sagebrush ecosystems.

Abstract Questions How does potential fire behaviour differ in grass‐invaded non‐native 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 land‐cover 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 m·min −1 ) than forests (0–10.5 m·min −1 ; 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 ha · yr −1 , 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.