Multi-millennial reconstruction of fire return intervals from a fynbos – Afrotemperate forest ecotone in the Cape Floristic Region, South Africa: Paleoecological implications for present-day management

The Gilé National Park (PNAG for its acronym in Portuguese), located in central Mozambique is one of the most important protected areas in the country. It is one of the last remnants of intact Miombo woodlands, providing critical habitat for endemic biodiversity. Fires are an important ecological factor in Miombo, but changes in fire regimes may compromise the stability of this ecosystem and thus, the conservation value of PNAG. This study assessed fire patterns and mapped fire risk in support of adaptive management in the PNAG. We investigated Miombo fire regime over 23 years (2001 to 2023) in terms of return interval, frequency, temporal distribution, spatial density and intensity, extent, and severity, by using two Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products (MCD14ML active fire; MCD64A1 burned area). Primary risk drivers were established and spatial fire likelihood mapped, using the Random Forest algorithm. Analysis revealed pronounced late dry season burning (August–October) affecting approximately 60% of the PNAG annually, especially in central-northern and eastern landscapes. Remarkably, 88% of the park maintains a 1-to-2-year fire return interval across the entire fire season (May–October) while only 7% maintains return frequencies of 3-to-4-year cycles. The latter is important for maintaining Miombo ecosystem functionality. Medium to medium–high fire severity covered 98% of the total fire extension. Climate-related drivers and hunting activities were identified as key fire initiators, especially in central areas of the park. The findings demonstrate an urgent need for spatially differentiated fire management action through prescribed burning to maintain PNAG’s ecological resilience and conservation value.

Changes in LULC, caused by urbanization and deforestation, can disrupt ecosystem patterns, including climate change. These changes lead to a decrease in the infiltration capacity of the soil, thereby increasing the surface runoff. Understanding LULC change over long periods and impacts is important for mitigating flood risks. This study analyzes LULC changes in the Cikapundung watershed over a 50-year period (1973–2023) and models flood inundation for 2014 and 2023, predict for 2032, which highlight critical knowledge gap this study addresses. The LULC model was conducted using satellite imagery, classified using random forest algorithm. The result shows the study area experienced significant changes, with built-up expanded by about 700% while non-agricultural vegetation declining by around 50%. The LULC model is considered along with DEM and the 2 to 100-year return periods to model the flood inundation, which was processed in HEC-RAS. The flood inundation model shows minimal variation between 2014–2032, with rainfall return period intensity having a greater influence on flood inundations, evidenced by increasing inundation corresponding to longer return intervals. The study is anticipated to inform spatial planning and disaster risk management decisions, as well as aid in adapting to the increasingly apparent effects of climate change.

Over the past 150 years, land-use changes from native ecosystems to row crop corn and soybeans have negatively impacted a variety of ecosystem services across the US Corn Belt, including nutrient attenuation, water storage, and habitat. Restoring floodplains in agriculturally dominated landscapes through United States Department of Agriculture Natural Resource Conservation Service programs (e.g., Emergency Watershed Protection program) could offer disproportionate opportunities to positively enhance ecosystem service benefits, yet identifying and prioritizing opportunities for conservation practices, including floodplain easements, to maximize environmental outcomes and financial resources remain challenging. This research sought to identify, prioritize, and evaluate costs associated with potential floodplain easements across the state of Iowa. Leveraging key geospatial data and criteria, including proportion of field within the 2- and 5-year flood return interval, field boundaries, and land use characteristics, we identified 141,314 floodplain easement opportunities of which 2707 were identified as high-priority locations based on the inundation frequency of the fields, representing a total area of 56,300 ha. To estimate acquisition, direct, and total costs associated with potential easements, we used soil and crop productivity index information, land value data, historic vegetation information, and partial enterprise budgets. Estimated costs to restore only high-priority easement opportunities totaled nearly 84.8 million USD annually. This approach aimed to develop an accessible approach to assist natural resource practitioners and conservation planners in identifying, prioritizing, and estimating costs for potential floodplain easement locations across the state of Iowa and in other regions where data exist.

ABSTRACT The increasing frequency of hydrological extremes highlights the need for event‐based approaches to evaluate hydrological model performance and support water resource management. Traditional long‐term continuous simulations often overlook model behavior during critical flood and drought periods, limiting their operational value. To address this gap, we developed a coupled SEED–CSES framework for large‐sample, event‐based benchmarking. SEED identifies flood and drought events using the Log‐Pearson Type III (LP3) distribution for multiple return intervals (2, 5, 10, 25, 50, and 100 years), while CSES evaluates model skill. We demonstrate the framework by assessing the extreme‐event prediction performance of the National Water Model (NWM) v3.0 at more than 7000 USGS NWIS stations, including over 600 CAMELS basins. Across the CONUS domain, NWM 3.0 shows higher skill for flood events (median KGE ≈0.20) than for drought events (median KGE ≈−0.78). Wetter eastern, southeastern, and northwestern regions perform better (median KGE ≈0.387), while arid western and southwestern regions show low performance (median KGE ≈−0.447), illustrating how event‐based benchmarking reveals hydrological behaviors masked in long‐term evaluations. The integrated SEED–CSES framework provides a standardized and automated platform for hydrological model assessment, supporting improved flood forecasting, drought monitoring, and climate resilience.

Human fire use is a key activity and process in many landscapes and ecosystems around the world, varying spatiotemporally depending on social, economic, and ecological factors. Recently, initiatives have begun to synthesise data on global fire use from across multiple disciplines and disparate sources into coherent databases. Here, we draw on information from one of these databases, the Livelihood Fire Database, which collates data on fire use practices worldwide from case studies in the literature. We examine data from 345 case study locations spanning 69 countries regarding return interval, area burned, and seasonality of anthropogenic fires set to meet small-scale rural livelihood objectives and/or for cultural reasons. We distinguish patterns in the spatiotemporal nature of fires associated with different fire-use purposes, such as clearing vegetation for agriculture, maintaining pasture for livestock, promoting certain plant species for gathering, or driving game when hunting. For many fire uses, especially those related to hunting, gathering, human wellbeing, and social signalling, there are very limited quantitative data available, but it is possible to draw qualitative insights from case studies. Case studies demonstrate that environmental and social conditions drive variation in fire use for the same purpose, reiterating that assumptions of uniform drivers of anthropogenic fire may be misleading. Nonetheless where quantitative data are available, we find some correspondence between the spatiotemporal nature of fires and fire-use purpose, suggesting that distinguishing between different fire-use purposes may be useful to understand and to better model their likely timing, size, and frequency relative to climate and other drivers. We recommend examples where the diagnosis of these broad relationships between fire-use purpose and fire properties could enable improved representation of anthropogenic fire in global land surface models, and aid interpretation of remote sensing data. Many of the smaller fires now being revealed in global burned area data by new fine-scale remote sensing products are likely human-set; continued collection, collation, and analyses of case study data on human fire use globally will be essential to help interpret this improved detection of small fires, and to ensure appropriate representation of the underlying drivers of human activity when modelling fire regimes.

Human fire use is a key activity and process in many landscapes and ecosystems around the world, varying spatiotemporally depending on social, economic, and ecological factors. Recently, initiatives have begun to synthesise data on global fire use from across multiple disciplines and disparate sources into coherent databases. Here, we draw on information from one of these databases, the Livelihood Fire Database, which collates data on fire use practices worldwide from case studies in the literature. We examine data from 345 case study locations spanning 69 countries regarding return interval, area burned, and seasonality of anthropogenic fires set to meet small-scale rural livelihood objectives and/or for cultural reasons. We distinguish patterns in the spatiotemporal nature of fires associated with different fire-use purposes, such as clearing vegetation for agriculture, maintaining pasture for livestock, promoting certain plant species for gathering, or driving game when hunting. For many fire uses, especially those related to hunting, gathering, human wellbeing, and social signalling, there are very limited quantitative data available, but it is possible to draw qualitative insights from case studies. Case studies demonstrate that environmental and social conditions drive variation in fire use for the same purpose, reiterating that assumptions of uniform drivers of anthropogenic fire may be misleading. Nonetheless where quantitative data are available, we find some correspondence between the spatiotemporal nature of fires and fire-use purpose, suggesting that distinguishing between different fire-use purposes may be useful to understand and to better model their likely timing, size, and frequency relative to climate and other drivers. We recommend examples where the diagnosis of these broad relationships between fire-use purpose and fire properties could enable improved representation of anthropogenic fire in global land surface models, and aid interpretation of remote sensing data. Many of the smaller fires now being revealed in global burned area data by new fine-scale remote sensing products are likely human-set; continued collection, collation, and analyses of case study data on human fire use globally will be essential to help interpret this improved detection of small fires, and to ensure appropriate representation of the underlying drivers of human activity when modelling fire regimes.

Prescribed burning is widely practiced for fuels reduction and restoring ecosystems historically maintained by fire. The Pine Barrens in southern New Jersey (USA) is an ecosystem shaped by frequent fire. Although late-winter prescribed burning has been applied to New Jersey Pine Barrens (NJPB) forests for decades, the long-term ecological consequences remain uncertain. A prescribed fire experiment was started in 2015 to evaluate effects of fire return interval on NJPB forests. For this investigation, monitoring plots were classified into five groups based on burn frequency, or number of burns over 9 years, ranging from 1 to 8 burns. Burn frequency did not explain significant ( p < 0.05) variation in stand-level attributes (stem density, basal area, etc.) in the first decade. Tree-level survival was significantly and positively correlated with stem diameter (DBH), but unaffected by fire frequency. No recruitment of new stems was observed under any burn frequency. Collectively, the early findings of this experiment indicate that the dual objectives of fuels reduction and minimizing overstory damage can be achieved under a range of fire frequencies (or return intervals) in these fire-adapted oak–pine woodlands. Research addressing effects of prescribed fire on the understory layer and tree regeneration in NJPB oak–pine woodlands is warranted.

BackgroundClimate change is expected to alter fire return intervals in cold and wet forests in the northwestern United States. This coupled with an expected rise in prescribed fires to restore healthy forests, disproportionately increases risk to saplings of tree species adapted to colder and wetter environments that have low fire resistance. To assess this potential impact, we evaluated the impacts of increasing fire intensity on Picea engelmannii and Thuja plicata sapling physiology, morphology, and mortality. This was achieved using established pyro-ecophysiology experiments where saplings were subjected to controlled surface fires across a range of fire intensities and post-fire growth, physiology and mortality were assessed up to 7 months post-fire.ResultsIn this study we demonstrate that the probability of mortality in the saplings of these two conifer species displays a sigmoidal increase with increasing fire intensity. At fire radiative energy dosage levels < 0.6 MJ m−2, the observed mortality in both species was lower than predicted by existing crown scorch-based models due to their limited sensitivity at small diameters. Prior to sapling death, chlorophyll fluorescence transiently recovers before a rapid decline, though the timing varies by species and fire intensity dosage. A new general sapling mortality model derived from 7 conifer species is presented.ConclusionsOur results provide predictive tools that managers could use to make informed decisions on the potential impacts of fires on conifer saplings growing in cold and wet environments. Results from both species suggest that chlorophyll fluorescence temporal trends could serve as a potential early warning indicator of fire-induced tree mortality, however, future work should explore whether similar responses are observable using remote sensing data from solar-induced chlorophyll fluorescence and assess potential mechanisms underlying this signal. The general sapling mortality model presented in this paper appears to provide an improved method of predicting conifer sapling mortality over existing approaches, however, research is needed to develop coefficients to adjust the model with tree age and environmental factors. Further studies could also explore whether phenotypic plasticity is driving observed tree responses to fire from plants grown from similar environments.Supplementary InformationThe online version contains supplementary material available at 10.1186/s42408-025-00443-7.

Abstract We created the first annually resolved records of historical fire occurrence coupled with precise estimates of tree establishment for the northern half of the west slope of the Oregon Cascades, a region that is home to some of the most productive forests on earth. Our reconstructions at 36 randomly located sites document exceptional diversity in historical fire disturbance and successional dynamics. Most stands where we collected data appear to have initiated following stand‐replacing fire between 200 and 750 years ago, although many sites exhibited evidence of moderate‐severity fire that created multi‐aged stands. More than two‐thirds of sites experienced multiple non‐stand‐replacing fires following stand initiation. A spatial generalized linear mixed model demonstrated that historical fire occurrence was negatively associated with average snow disappearance day and time since last fire and positively associated with drought. Significant variability in the number of fires, length of fire return intervals, and sample depth across sites made calculation of informative mean fire return intervals (MFRIs) difficult. Site‐level annual probability of fire from our mixed model ranged from 0.039 to 0.003, equivalent to MFRIs of 26–389 years. We used fire and tree establishment records to infer the general location of several large historical fire events that likely burned as much or more area as the &gt;50,000 ha fires that burned across our study region in 2020. We also identified periods of extensive burning and subsequent tree establishment that occurred across seven centuries within six large river drainages that made up our study region. Although tree establishment occurred for up to a century following stand‐replacing fire at some sites, we show that these apparent long periods of establishment were relatively short pulses of regeneration separated by reburns. This study demonstrates that many highly productive Douglas‐fir‐dominated stands in western Oregon are significantly departed from historical fire disturbance regimes. Management that emphasizes rapid re‐establishment of closed canopy forest conditions following fire and development of old‐growth forest conditions in the absence of fire may fail to provide for the unique and highly valued ecosystem services associated with these forests.

Abstract Background Mapping surface and ground fuels is key to supporting wildland fire research and management. Fuel loading, structure, distribution, and continuity, along with other factors, strongly influence fire spread and consumption. It is, therefore, essential to understand drivers of fuel accumulation such as the aboveground tree inputs from abscission, dispersion, decomposition, disturbances, and management practices (e.g., prescribed fire), particularly in fire-dependent forest ecosystems such as longleaf flatwoods savannas of the southeastern US. In 2022, we collected and measured litter load, duff load, and duff depth before and after prescribed burning in 72 field plots at pine flatwoods at Osceola National Forest, in northern Florida, where a long-term experiment on fire return intervals (FRI; 1, 2, 4 years and unburned controls) has been running since 1958. We assessed how FRI, proximity to trees, wind direction, and structural attributes such as stand basal area and density influenced the distribution and accumulation of litter and duff. Results Overall, litter and duff were highly variable across FRI and before and after prescribed fire. Litter load, duff load, and duff depth all increased with longer FRIs and higher basal area. Consistent prescribed fire significantly increased duff bulk density—defined as the ratio of duff load to duff depth—compared to the long-unburned plots. Proximity to the tree bole was a significant factor explaining duff distribution within unburned plots, while both duff and litter were evenly distributed across the four cardinal directions. Conclusions The FRI of the prescribed burning drove the inter-stand-level accumulation of duff and litter while aboveground tree biomass influenced intra-stand distribution. Consistent prescribed fire resulted in more compacted duff layers, an effect that warrants consideration in carbon assessment in fire-maintained forest ecosystems. This study advances our understanding of litter and duff accumulation dynamics in southern pine flatwoods under frequent prescribed fire management; however, comparison with data from other study sites is essential to corroborate these trends.

Abstract Understanding and predicting bankfull stage is essential for geomorphic analysis, hydraulic modelling and river corridor management, especially regarding floods and connectivity. This study evaluates traditional geomorphic and hydrologic methods and introduces a machine learning (ML) approach to predict bankfull stage along the upper Apalachicola River, Florida, United States. First, we integrated LiDAR point cloud data with a 2010 hydrographic survey through a triangular irregular network (TIN) following coordinate transformation, producing a 1.5‐m resolution digital elevation model (DEM) that captures riverbed elevation. After extracting cross‐sections, we applied two geomorphic methods, Width‐to‐Depth Ratio (WDR) and Hydraulic Mean Depth (HMD), and three (1.1‐, 1.5‐, 2.0‐year) hydrologic return intervals to 344 cross‐sections to determine bankfull stage and assessed their agreement with visual and field‐verified bankfull elevations. A refined HMD method using shape ratio (Rs) and slope inflection corrections improved geomorphic estimates in 131 cross‐sections. Bankfull estimates based on return intervals exhibited substantially lower reliability relative to geomorphic methods, with associated confidence levels falling below 70%. This reduced performance is attributable to stage‐based spatial averaging and limited sensitivity to local topographic variability. By contrast, the geomorphic methods (WDR and HMD) achieved confidence levels exceeding 95%, underscoring their stronger agreement and robustness. To improve accuracy, we developed ML models: Random Forest (RF), Gradient Boosting (GB) and Ensemble model trained on cross‐sectional elevation profiles and engineered features such as cross‐sectional area, top width, maximum depth, symmetry, etc. The GB model outperformed all others ( R 2 = 0.94, MSE = 0.21), with feature importance analysis revealing that elevation at the top bank as well as channel area, top width and maximum depth dominated predictions. While this study advances the integration of ML into fluvial systems and provides a replicable framework for large rivers with limited hydrologic data, we recommend that multiple ML models be evaluated across individual reaches to account for the unique geomorphic and hydraulic characteristics of each river reach.

ABSTRACTObjectiveTo evaluate the effect of multidisciplinary tracheostomy team (MDT) interventions on emergency department utilization in pediatric patients with tracheostomy.MethodsThis retrospective cohort study analyzed a prospective registry of 364 children who underwent tracheostomy from 2015 to 2023 at a single tertiary pediatric center. The study period encompassed pre‐intervention, post‐intervention pre‐COVID, COVID‐19, and post‐COVID recovery phases. Primary outcomes were time to ED visits and ED visit frequency, analyzed using parametric survival analysis and mixed‐effects negative binomial regression.ResultsAmong 364 patients (mean age 3.5 ± 5.4 years; 53% male), MDT implementation was associated with a 50% reduction in ED visit rates (incidence rate ratio 0.50, 95% CI: 0.43–0.57, p < 0.001) during the post‐intervention, pre‐COVID period. Benefits sustained through COVID (65% reduction) and post‐COVID recovery (91% reduction). Time to first ED visit increased significantly across post‐intervention periods (post‐intervention, pre‐COVID: time ratio 1.22, 95% CI: 1.12–1.32, p < 0.001; post‐COVID recovery: time ratio 1.25, 95% CI: 1.11–1.40, p < 0.001). During median follow‐up of 2.8 years, 1056 of 1842 total encounters (57%) involved ED visits. Respiratory conditions accounted for 34% of ED visits. Hispanic ethnicity (time ratio 0.88, p = 0.003) and respiratory‐related visits (time ratio 0.78, p < 0.001) were associated with shorter return intervals but did not affect overall visit frequency.ConclusionMDTs were associated with sustained 50% reductions in pediatric ED utilization, with reductions continuing through the COVID‐19 pandemic.Levels of Evidence3.

Introduction Many plant species have evolved to persist in fire-prone regions under specific fire regimes. Seeds have developed mechanisms, including the breaking of physical seed dormancy by fire-related heat shock, that synchronize germination and seedling emergence with post-fire conditions conducive to successful recruitment. Seeds with physical dormancy can have their dormancy released by high soil temperatures during fire, with documented thermal thresholds varying widely from 60°C to 150°C. Generally, these thresholds are believed to be highly phylogenetically conserved, but how ecosystems shape seed thermal thresholds within widespread, geographically diverse genera is unknown. In this study, we sought to understand how soil heating under different fire regimes, seed traits, and climate variables all shape pyro-thermal niche metrics, dormancy-break, and mortality of Acacia seeds. Methods Using 35 Acacia species from across 12 vegetation types in Australia, we explored the relationship between seed pyro-thermal niche characteristics and fire return interval (FRI), fuel type (as a proxy for soil heating), mean annual temperature, and total annual precipitation. Results Pyro-thermal niche metrics showed a hump-shaped relationship with both the minimum recommended FRI and fuel type, highlighting the role fire plays in shaping seed thermal thresholds. Climate variables showed no discernible relationship with pyro-thermal niche metrics. Discussion These results suggest that the mechanisms that shape the distribution of different seed dormancy classes are different from those that shape variation in pyro-thermal niche metrics. Understanding the processes driving plant population dynamics in fire-prone regions is essential for ecological understanding under a changing climate.

Abstract Background Little is known about the fire history of the Atlantic cypress swamps, which are found along the coast of the United States from Maine to Florida. By utilizing historical records from journals and newspapers, we have documented the fire history of the Delmarva Peninsula’s Great Cypress Swamp. In the late eighteenth century, this swamp was estimated to cover nearly 50,000 acres (20,234 ha). Results Between 1782 and 1941, the Great Cypress Swamp experienced 18 documented fires. The fire season in the swamp lasted from May to November, with the highest number of fires—one-third—occurring in July. The mean fire return interval (MFRI) was 5.33 years. Generally, both the Palmer Drought Severity Index (PDSI) and newspaper reports indicated that fires were more likely to occur during times of drought. Notably, the 1930 fire, which lasted from August to October, occurred under severe drought conditions. Conclusions Over time, the Great Cypress Swamp has undergone significant human alteration due to timber harvesting for shingle production and ditching and drainage efforts associated with agricultural expansion. The removal of the canopy, as well as drainage, likely intensified the effects of droughts by drying out the peat and increasing the risk of fire. In most cases, the exact cause of the fires remains unknown, but they were most likely of anthropogenic origin, such as careless smoking and the burning of dry peat to access buried logs.

Abstract Background Prescribed fire is an essential tool employed by natural resource managers to serve ecological and fuel treatment objectives of fire management. However, limited operational resources, environmental conditions, and competing goals result in a finite number of burn days, which need to be allocated toward maximizing the overall benefits attainable with fire management. Burn prioritization models must balance multiple management objectives at landscape scales, often providing coarse resolution information. We developed a decision-support framework and a burn prioritization model for wetlands and wildland-urban interfaces using high-resolution mapping in Everglades National Park (Florida, USA). The model included criteria relevant to the conservation of plant communities, the protection of endangered faunal species, the ability to safely contain fires and minimize emissions harmful to the public, the protection of cultural, archeological, and recreational resources, and the control of invasive plant species. A geographic information system was used to integrate the multiple factors affecting fire management into a single spatially and temporally explicit management model, which provided a quantitative computations-alternative to decision making that is usually based on qualitative assessments. Results Our model outputs were 50-m resolution grid maps showing burn prioritization scores for each pixel. During the 50 years of simulated burn unit prioritization used for model evaluation, the mean burned surface corresponded to 256 ± 160 km2 y−1, which is 12% of the total area within Everglades National Park eligible for prescribed fires. Mean predicted fire return intervals (FRIs) varied among ecosystem types: marshes (9.9 ± 1.7 years), prairies (7.3 ± 1.9 years), and pine rocklands (4.0 ± 0.7 years). Mean predicted FRIs also varied among the critical habitats for species of special concern: Ammodramus maritimus mirabilis (7.4 ± 1.5 years), Anaea troglodyta floridalis and Strymon acis bartrami butterflies (3.9 ± 0.2 years), and Eumops floridanus (6.5 ± 2.9 years). While mean predicted fire return intervals accurately fit conservation objectives, baseline fire return intervals, calculated using the last 20 years of data, did not. Fire intensity and patchiness potential indices were estimated to further support fire management. Conclusions By performing finer-scale spatial computations, our burn prioritization model can support diverse fire regimes across large wetland landscape such as Everglades National Park. Our model integrates spatial variability in ecosystem types and habitats of endangered species, while satisfying the need to contain fires and protect cultural heritage and infrastructure. Burn prioritization models can allow the achievement of target fire return intervals for higher-priority conservation objectives, while also considering finer-scale fire characteristics, such as patchiness, seasonality, intensity, and severity. Decision-support frameworks and higher-resolution models are needed for managing landscape-scale complexity of fires given rapid environmental changes.

ABSTRACTThe 2020 Cameron Peak wildfire burned part of the Poudre River catchment in Colorado, USA. The river flows through a high‐gradient canyon before entering a lower‐gradient transition zone with modified channel morphology and flow regime. Widespread post‐fire erosion introduced fine sediment (&lt; 2 mm) to the river, causing sediment deposition and a major fish kill. Fine sediment deposition in the transition zone partially blocked or filled fish habitat in channel margin backwaters and side channels and filled interstices in fish‐spawning habitat along the cobble‐boulder bed channel. During summer 2023, we quantified fine sediment retention at 18 sites along the river by measuring fine sediment volumes and embeddedness. Our objectives were to (i) evaluate whether reach‐scale geomorphic attributes or river distance downstream from the sediment source correlate more strongly with reach‐scale fine sediment volume and embeddedness and (ii) use 2D hydraulic modeling and incipient motion equations to estimate the discharge necessary to mobilize the channel bed and remove excess fine sediment. Reach location (canyon vs. transition zone) best explained the volume of fine sediment and embeddedness, although the reach‐scale variables of gradient and cross‐sectional area were significant predictors of fine sediment retention. Hydraulic modeling indicated that a 2‐year return interval flow mobilizes a substantial portion of the bed at the canyon site, whereas bed mobilization requires a 5‐ to 10‐year flow at the transition zone sites. Management to mitigate post‐fire sedimentation and stressors to fishes may need to emphasize changes in river corridor geometry where consumptive water use limits flushing flows.

Fire is a fundamental force that shapes ecosystems by influencing vegetation composition, succession, and structural diversity. Fire regimes, defined by fire frequency, intensity, and seasonality, vary across ecosystems and are critical in fire-dependent landscapes. In the Florida Everglades, fire is a key driver of ecological dynamics, interacting with hydrology and the structure of vegetation. This study defines contemporary fire regimes by describing fire patterns from 1978 to 2023, utilizing fire perimeter data from Everglades National Park and Big Cypress National Preserve. Our findings reveal a highly variable annual burned area with a strong increasing trend. Prescribed fires were the foundation of trends in fire activity, as wildfires remained stable over the study period. Across the Everglades, fire return intervals differed between ecosystems, with upland ecosystems experiencing more frequent fires than wetland ecosystems. Our findings highlight the role of fire management in shaping modern fire regimes and underscore the importance of prescribed burns in maintaining ecosystem function and resilience in the Everglades.

Abstract This study uses 25 CMIP6 global climate model simulations, bias‐corrected and dynamically downscaled to 9 km, to examine regional changes in extreme precipitation, and predictive uncertainty, in the western United States under global warming levels (GWL) of 2°C and 3°C. This resolution is needed to capture orographic precipitation enhancement. Most models agree on significant increases in both the Rx1day and R99p indices. The largest increases in extreme precipitation are anticipated in California, both in an absolute sense, with Rx1day increases up to ∼10 mm/day, and in a relative sense, with up to a doubling of R99p in the more arid parts of the state for GWL 3°C. The most significant reductions in return intervals of extreme precipitation events are anticipated in the Rocky Mountain region. For instance, 50‐year Rx1day events become 3 to 4 times more frequent under GWL 2°C and 6 to 8 times more frequent under GWL 3°C.

Abstract Background Catastrophic wildfire has escalated across the globe in recent decades with devastating consequences for human communities and native ecosystems. Global change processes, including climate warming and land use practices, are altering fuels, fire risk, and ecosystem recovery. Managing ecosystems to reduce fire risk and prevent conversion to undesirable alternative states requires knowledge of the ecological conditions of ecosystems, trajectories of change, and drivers of those changes. We developed an approach for evaluating ongoing changes in climate and vegetation and using that information to determine appropriate fuels and other vegetation management strategies for southwest US dryland shrubland and woodland landscapes. We illustrated the approach at a management appropriate scale—a USDA Forest Service Wildfire Crisis Strategy landscape. Results We developed an understanding of ecological types, current climatic regimes, ecological resilience to disturbance, and resistance to invasive annual grass (R&amp;R). We then evaluated changes in plant functional type cover, historical fires, and R&amp;R using long-term data. In unburned areas, changes in plant functional type cover included decreases in perennial forbs and grasses but increases in annual forbs and grasses, shrubs, and especially pinyon and juniper trees. In burned areas, tree cover was reduced and both perennial forb and grass and annual forb and grass cover increased. Most ecological types had moderate wildfire risk based on modeled annual burn probabilities and large areas burned since 1998 (16% of study area). These types were likely burning within expected fire return intervals, but areas burned during a single event may have exceeded historical extents and post-fire outcomes had changed. Transitions to warmer temperature regimes occurred between 1980–1999 and 2000–2019 resulting in an 11% decrease in R&amp;R with the greatest impacts in cooler and moister ecological types. Conclusions We showed that climate warming in southwest drylands has been associated with concurrent changes in vegetation and fuels and decreases in R&amp;R. We provide an approach that allows managers to quantify the ongoing changes at management appropriate scales. We suggest climate smart management strategies to help direct ecosystems into conditions that can decrease fire risk, increase resistance to plant invasions, and reduce vulnerability to climate change.