The reliability of airborne light detection and ranging (LiDAR) for delineating individual trees and estimating aboveground biomass (AGB) has been proven in a diverse range of ecosystems, but can be difficult and costly to commission. Point clouds derived from structure from motion (SfM) matching techniques obtained from unmanned aerial systems (UAS) could be a feasible low-cost alternative to airborne LiDAR scanning for canopy parameter retrieval. This study assesses the extent to which SfM three-dimensional (3D) point clouds—obtained from a light-weight mini-UAS quadcopter with an inexpensive consumer action GoPro camera—can efficiently and effectively detect individual trees, measure tree heights, and provide AGB estimates in Australian tropical savannas. Two well-established canopy maxima and watershed segmentation tree detection algorithms were tested on canopy height models (CHM) derived from SfM imagery. The influence of CHM spatial resolution on tree detection accuracy was analysed, and the results were validated against existing high-resolution airborne LiDAR data. We found that the canopy maxima and watershed segmentation routines produced similar tree detection rates (~70%) for dominant and co-dominant trees, but yielded low detection rates (<35%) for suppressed and small trees due to poor representativeness in point clouds and overstory occlusion. Although airborne LiDAR provides higher tree detection rates and more accurate estimates of tree heights, we found SfM image matching to be an adequate low-cost alternative for the detection of dominant and co-dominant tree stands.

Despite the intact appearance of relatively unmodified north Australian savannas, mounting evidence indicates that contemporary fire regimes characterised by frequent, extensive and severe late dry season wildfires are having deleterious effects on a range of regional water, soil erosion, biodiversity conservation and greenhouse gas (GHG) emissions values. For the high rainfall (>1000 mm year–1) savannas (426 000 km2), we assessed the spatial effects of contemporary fire regimes within the context of ecosystem response models and three plausible alternative fire management scenarios on ecosystem attributes. Over the 2008–12 assessment period, mean annual fire frequency (0.53) comprised mostly late dry season fires. Although spatially variable, contemporary fire regimes resulted in substantial GHG emissions, hill slope erosion and suspended sediment transport, a slight decline in carbon biomass and slight positive effects on fire-vulnerable vegetation. Based on available climate change models and strategic fire management practice, we show that, relative to business-as-usual, improved fire management involving strategic prescribed burning results in substantial benefits to most ecosystem attributes, including under enhanced climate change conditions, whereas in the absence of improved fire management, climate change results in substantially worse outcomes.

Tropical savannas are characterized by high primary productivity and high fire frequency, such that much of the carbon captured by vegetation is rapidly returned to the atmosphere. Hence, there have been suggestions that management‐driven reductions in savanna fire frequency and/or severity could significantly reduce greenhouse gas emissions and sequester carbon in tree biomass. However, a key knowledge gap is the extent to which savanna tree biomass will respond to modest shifts in fire regimes due to plausible, large‐scale management interventions. Here, we: (1) characterize relationships between the frequency and severity of fires and key demographic rates of savanna trees, based on long‐term observations in vegetation monitoring plots across northern Australia; (2) use these relationships to develop a process‐explicit demographic model describing the effects of fire on savanna tree populations; and (3) use the demographic model to address the question: to what extent is it feasible, through the strategic application of prescribed burning, to increase tree biomass in Australian tropical savannas? Our long‐term tree monitoring dataset included observations of 12,344 tagged trees in 236 plots, monitored for between 3 and 24 years. Analysis of this dataset showed that frequent high‐severity fires significantly reduced savanna tree recruitment, survival, and growth. Our demographic model suggested that: (1) despite the negative effects of frequent high‐severity fires on demographic rates, savanna tree biomass appears to be suppressed by only a relatively small amount by contemporary fire regimes, characterized by a mix of low‐ to high‐severity fires; and (2) plausible, management‐driven reductions in the frequency of high‐severity fires are likely to lead to increases in tree biomass of about 11.0 t DM ha⁻¹ (95% CI: −1.2–20.8) over a century. Accounting for this increase in carbon storage could generate significant carbon credits, worth, on average, three times those generated annually by current greenhouse gas (methane and nitrous oxide) abatement projects, and has the potential to significantly increase the economic viability of fire/carbon projects, thereby promoting ecologically sustainable management of tropical savannas in Australia and elsewhere. This growing industry has the potential to bring much‐needed economic activity to savanna landscapes, without compromising important natural and cultural values.

Landscape fires are substantial sources of (greenhouse) gases and aerosols. Fires in savanna landscapes represent more than half of global fire carbon emissions. Quantifying emissions from fires relies on accurate burned area, fuel load and burning efficiency data. Of these, fuel load remains the source of the largest uncertainty. In this study, we used high spatial resolution images from an Unmanned Aircraft System (UAS) mounted multispectral camera, in combination with meteorological data from the ERA-5 land dataset, to model instantaneous pre-fire above-ground biomass. We constrained our model with ground measurements taken in two locations in savanna-dominated regions in Southern Africa, one low-rainfall region (660 mm year${}^{-1}$) in the North-West District (Ngamiland), Botswana, and one high-rainfall region (940 mm year${}^{-1}$) in Niassa Province (northern Mozambique). We found that for fine surface fuel classes (live grass and dead plant litter), the model was able to reproduce measured Above-Ground Biomass (AGB) (R${}^2$ of 0.91 and 0.77 for live grass and total fine fuel, respectively) across both low and high rainfall areas. The model was less successful in representing other classes, e.g., woody debris, but in the regions considered, these are less relevant to biomass burning and make smaller contributions to total AGB.

Northern Australia is prone to recurring severe natural hazards, especially frequent cyclones, flooding, and extensive wildfires. The region is sparsely populated (≪ 0.5 persons km⁻²), with Indigenous (Aboriginal) residents comprising 14% of the population, and typically the majority in remote regions. Despite national policy committed to addressing emergency management (EM) in vulnerable Indigenous communities, implementation remains unfunded. We synthesise participatory intercultural research conducted over seven years exploring core challenges, opportunities and potential solutions towards developing effective EM partnerships. Similar EM engagement and empowerment issues face First Nations and local communities in many international settings. In search of solutions, we explore developing effective partnership arrangements between EM agencies and culturally diverse Indigenous communities. Observing that government already provides substantial investment in cultural and natural resource management programmes conducted by over 150 Indigenous Ranger Groups (IRGs) nationally, we demonstrate that expansion of IRG roles to incorporate EM community engagement and service delivery can provide multiple cost-effective community and business development benefits for many remote communities.