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At least 1,225 records · Page 68Linked to original sources

USGS2017

Prediction of forest canopy and surface fuels from Lidar and satellite time series data in a bark beetle-affected forest

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and surface fuels from light detection and ranging (lidar) and Landsat time series explanatory variables via random forest (RF) modeling across a coniferous montane forest in Colorado, USA, which was affected by mountain pine beetles ( Dendroctonus ponderosae Hopkins) approximately six years prior. We examined relationships between mapped fuels and the severity of tree mortality with correlation tests. RF models explained 59%, 48%, 35%, and 70% of the variation in available canopy fuel, canopy bulk density, canopy base height, and canopy height, respectively (percent root-mean-square error (%RMSE) = 12–54%). Surface fuels were predicted less accurately, with models explaining 24%, 28%, 32%, and 30% of the variation in litter and duff, 1 to 100-h, 1000-h, and total surface fuels, respectively (%RMSE = 37–98%). Fuel metrics were negatively correlated with the severity of tree mortality, except canopy base height, which increased with greater tree mortality. Our results showed how bark beetle-caused tree mortality significantly reduced canopy fuels in our study area. We demonstrated that lidar and Landsat time series data contain substantial information about canopy and surface fuels and can be used for large-scale efforts to monitor and map fuel loads for fire behavior modeling at a landscape scale.

Colorado↗

USGS2019

Surface fire to Crown Fire: Fire history in the Taos Valley watersheds, New Mexico, USA

Tree-ring fire scars, tree ages, historical photographs, and historical surveys indicate that, for centuries, fire played different ecological roles across gradients of elevation, forest, and fire regimes in the Taos Valley Watersheds. Historical fire regimes collapsed across the three watersheds by 1899, leaving all sites without fire for at least 119 years. Historical photographs and quaking aspen (Populus tremuloides Michx.) ages indicate that a high-severity fire historically burned at multiple high-elevation subalpine plots in today’s Village of Taos Ski Valley, with large high-severity patches (>640 ha). Low-severity, frequent (9–29-year median interval) surface fires burned on the south aspects in nearby lower elevation dry conifer forests in all watersheds. Fires were associated with drought during the fire year. Widespread fires commonly burned synchronously in multiple watersheds during more severe drought years, preceded by wet years, including fire in all three watersheds in 1664, 1715, and 1842. In contrast, recent local “large” wildfires have only burned within single watersheds and may not be considered large in a historical context. Management to promote repeated low-severity fires and the associated open stand structures is within the historical range of variability in the dry conifer forests of these watersheds. In the high-elevation, subalpine forests, different management approaches are needed, which balance ecological and socioeconomic values while providing public safety.

New Mexico↗

USGS2019

Prototype downscaling algorithm for MODIS Satellite 1 km daytime active fire detections

This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as compared to the non-burning neighborhood components. Active fire presence probability class for each of the 500 m pixels within the 1 km footprint is assigned by locally adaptive contextual tests against its surrounding neighborhood pixels. Accuracy is assessed using gas flares and wildfires in conjunction with available high-resolution imagery. Proof of concept results using MODIS observations over two sites show that under clear sky conditions, over 84% of the 500 m locations that had active fires were correctly assigned to high to medium probabilities, and correspondingly low to poor probabilities were assigned to locations with no visible flaming fronts. Factors limiting the algorithm performance include fire size/temperature distributions, cloud and smoke obscuration, sensor point spread functions, and geolocation errors. Despite these limitations, the resulting finer spatial scale of active fire detections will not only help first responders and managers to locate actively burning fire fronts more precisely but will also be useful for the fire science community.

Fire↗

USGS2021

Broad-scale surface and atmospheric conditions during large fires in south-central Chile

The unprecedented size of the 2017 wildfires that burned nearly 600,000 hectares of central Chile highlight a need to better understand the climatic conditions under which large fires develop. Here we evaluate synoptic atmospheric conditions at the surface and free troposphere associated with anomalously high (active) versus low (inactive) months of area burned in south-central Chile (ca. 32–41° S) from the Chilean Forest Service (CONAF) record of area burned from 1984–2018. Active fire months are correlated with warm surface temperatures, dry conditions, and the presence of a circumpolar assemblage of high-pressure systems located ca. 40°–60° S. Additionally, warm surface temperatures associated with active fire months are linked to reduced strength of cool, onshore westerly winds and an increase in warm, downslope Andean Cordillera easterly winds. Episodic warm downslope winds and easterly wind anomalies superimposed on long-term warming and drying trends will continue to create conditions that promote large fires in south-central Chile. Identifying the mechanisms responsible for easterly wind anomalies and determining whether this trend is strengthening due to synoptic-scale climatic changes such as the poleward shift in Southern Hemisphere westerly winds will be critical for anticipating future large fire activity in south-central Chile.

Fire↗

USGS2021

Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)

Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine learning algorithm specifically for burned area in wetlands, and applied the algorithm to the Sentinel-2 archive (2016–2019) across the Southeastern US (>290,000 km 2 ). Combining Landsat-8 imagery with Sentinel-2 increased the annual clear-sky observation count from 17 to 46 in 2016 and from 16 to 78 in 2019. When validated with WorldView imagery, the Sentinel-2 burned area had a 29% and 30% omission and commission rates of error for burned area, respectively, compared to the US Geological Survey Landsat-8 Burned Area Product (L8 BA), which had a 47% and 8% omission and commission rate of error, respectively. The Sentinel-2 algorithm and the L8 BA mapped burned area within 78% and 60% of wetland fire perimeters ( n = 555) compiled from state and federal agencies, respectively. This analysis demonstrated the potential of Sentinel-2 to support efforts to track the burned area, especially across challenging ecosystem types, such as wetlands.

Florida, Montana, Oregon↗

USGS2016

Climate change and future fire regimes: Examples from California

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.

Geoscience Canada↗

USGS2021

Understanding grass invasion, fire severity, and Acacia koa regeneration for forest restoration in Hawaiʻi Volcanoes National Park

With invasive grasses increasing wildfire occurrence worldwide, a better understanding of the relationships between native plants, fire, and invasive grass is needed to help restoration plans facilitate ecosystem resilience. Invasive grasses are particularly problematic for altering fire regimes in the tropics, yet in Hawaiʻi, restoration sites are often planted with monocultures of the native tree Acacia koa, which can promote grass growth via nitrogen fixation. This, combined with the difficulty of estimating pre-fire grass cover under thick canopies, complicates attempts to restore Hawaiian ecosystems. We studied the 2018 Keauhou Ranch Fire in Hawaiʻi to investigate three questions: (1) at what level of precision can pre-fire grass cover be accurately estimated from oblique aerial photos? (2) how are post-fire A. koa regeneration densities affected by fire severity? and (3) how are post-fire A. koa regeneration densities affected by pre-fire grass cover and its interaction with fire severity? We collected burn severity and post-fire regeneration data from 30 transects stratified across mid-elevation woodland, montane woodland, and montane shrubland communities. We evaluated visual estimates of pre-fire grass cover from oblique aerial imagery with quantitative in situ data from 60 unburned transects of the same cover types. Pre-fire estimates of grass cover categories were 67% accurate in montane woodland ( n = 9) and 100% accurate in montane shrubland ( n = 11), but only 20% accurate in mid-elevation woodland ( n = 10). In montane woodlands with low pre-fire tree densities, A. koa regeneration densities were higher with increased fire severity, but this trend reversed when pre-fire tree densities were high. We detected no effect of pre-fire grass cover, nor its interaction with fire severity, on A. koa regeneration density. This indicates that restoration through the planting of A. koa may be successful in promoting fire-resilient A. koa forest, although there are potential issues to consider regarding the effects that A. koa ’s grass promotion may have on other species within the ecosystem.

Hawaii↗

USGS2022

Spatial estimates of soil moisture for understanding ecological potential and risk: a case study for arid and semi-arid ecosystems

Soil temperature and moisture (soil-climate) affect plant growth and microbial metabolism, providing a mechanistic link between climate and growing conditions. However, spatially explicit soil-climate estimates that can inform management and research are lacking. We developed a framework to estimate spatiotemporal-varying soil moisture (monthly, annual, and seasonal) and temperature-moisture regimes as gridded surfaces by enhancing the Newhall simulation model. Importantly, our approach allows for the substitution of data and parameters, such as climate, snowmelt, soil properties, alternative potential evapotranspiration equations and air-soil temperature offsets. We applied the model across the western United States using monthly climate averages (1981–2010). The resulting data are intended to help improve conservation and habitat management, including but not limited to increasing the understanding of vegetation patterns (restoration effectiveness), the spread of invasive species and wildfire risk. The demonstrated modeled results had significant correlations with vegetation patterns—for example, soil moisture variables predicted sagebrush (R 2 = 0.51), annual herbaceous plant cover (R 2 = 0.687), exposed soil (R 2 = 0.656) and fire occurrence (R 2 = 0.343). Using our framework, we have the flexibility to assess dynamic climate conditions (historical, contemporary or projected) that could improve the knowledge of changing spatiotemporal biotic patterns and be applied to other geographic regions.

Land↗

USGS2020

Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data

Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.

Alaska↗

USGS2022

Multi-species inference of exotic annual and native perennial grasses in rangelands of the western United States using Harmonized Landsat and Sentinel-2 data

The invasion of exotic annual grass (EAG), e.g., cheatgrass ( Bromus tectorum ) and medusahead ( Taeniatherum caput-medusae ), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass ( Poa secunda )). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers.

western United States↗

USGS2014

Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR

Vegetation structure, including forest canopy height, is an important input variable to fire behavior modeling systems for simulating wildfire behavior. As such, forest canopy height is one of a nationwide suite of products generated by the LANDFIRE program. In the past, LANDFIRE has relied on a combination of field observations and Landsat imagery to develop existing vegetation structure products. The paucity of field data in the remote Alaskan forests has led to a very simple forest canopy height classification for the original LANDFIRE forest height map. To better meet the needs of data users and refine the map legend, LANDFIRE incorporated ICESat Geoscience Laser Altimeter System (GLAS) data into the updating process when developing the LANDFIRE 2010 product. The high latitude of this region enabled dense coverage of discrete GLAS samples, from which forest height was calculated. Different methods for deriving height from the GLAS waveform data were applied, including an attempt to correct for slope. These methods were then evaluated and integrated into the final map according to predefined criteria. The resulting map of forest canopy height includes more height classes than the original map, thereby better depicting the heterogeneity of the landscape, and provides seamless data for fire behavior analysts and other users of LANDFIRE data.

Alaska↗

USGS2016

Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California

To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.

California↗

USGS2022

A century of drought in Hawai‘i: Geospatial analysis and synthesis across hydrological, ecological, and socioeconomic scales

Drought is a prominent feature of Hawaiʻi’s climate. However, it has been over 30 years since the last comprehensive meteorological drought analysis, and recent drying trends have emphasized the need to better understand drought dynamics and multi-sector effects in Hawaiʻi. Here, we provide a comprehensive synthesis of past drought effects in Hawaiʻi that we integrate with geospatial analysis of drought characteristics using a newly developed 100-year (1920–2019) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: Meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration and magnitude have increased significantly, consistent with trends found in other Pacific Islands. We found that most droughts were associated with El Niño events, and the two worst droughts of the past century were multi-year events occurring in 1998–2002 and 2007–2014. The former event was most severe on the islands of O’ahu and Kaua’i while the latter event was most severe on Hawaiʻi Island. Within islands, we found different spatial patterns depending on leeward versus windward contrasts. Droughts have resulted in over $80 million in agricultural relief since 1996 and have increased wildfire risk, especially during El Niño years. In addition to providing the historical context needed to better understand future drought projections and to develop effective policies and management strategies to protect natural, cultural, hydrological, and agricultural resources, this work provides a framework for conducting drought analyses in other tropical island systems, especially those with a complex topography and strong climatic gradients.

Hawaii↗

USGS2019

Discovery of the yellow-bellied marmot (Marmota flaviventris) in the Jemez Mountains, New Mexico: Examining competing hypotheses for range extension

The yellow-bellied marmot ( Marmota flaviventris ) reaches the southern edge of its geographic range in New Mexico, where it is known from the San Juan and Sangre de Cristo Mountains. We provide a synopsis of the geographic range of M. flaviventris in New Mexico and report 5 recent records from the Jemez Mountains, Los Alamos and Sandoval Counties. Of the 5 records from the Jemez Mountains, 3 were obtained at high-elevation sites (>2690 m) during routine fieldwork and while conducting surveys for the American pika ( Ochotona princeps ), and 2 were from a residential area at relatively low elevation (2204 m) on a finger-mesa in Los Alamos. We evaluate 3 hypotheses for the provenance of the new records and conclude that M. flaviventris has maintained a relictual occurrence in the Jemez Mountains, but that the recent detections were due to (1) increased mammalogy fieldwork at high elevations, digital camera technology, and social media that allowed mammalogists to become aware of observations, and (2) possibly altered behavior by marmots due to impacts of recent widespread wildfire. Because small, isolated populations of marmots are vulnerable to extinction, research is needed to assess the status and trend of marmots in the Jemez Mountains, as well as in adjacent mountain ranges in New Mexico, with emphasis on identifying conservation threats and prospects for long-term persistence in the state.

New Mexico↗

USGS2007

Effects of exotic grasses on soil seed banks in Southeastern Arizona grasslands

At the Appleton-Whittell Research Ranch, an ungrazed grassland preserve in southeastern Arizona, soil seed banks were sampled in June, August, and October 2002 and June 2003. Wildfire had previously burned 90% of the research ranch in May 2002. Seed density and species richness in burned native grassland (2 plots) were compared to those in burned exotic grassland (2 plots). Averaged over 4 sample dates, seed densities were as follows: burned native grassland, 591 ± 243.1 seeds ·m −2 and 784 ± 334.9 seeds ·m −2 ; burned exotic grassland, 501 ± 198.9 seeds ·m −2 and 196 ± 123.8 seeds ·m −2 . Species richness in the seed bank, also averaged over 4 sample dates, was as follows: burned native grassland, 16.3 ± 1.7 species ·m −2 and 19.5 ± 1.0 species ·m −2 ; burned exotic grassland, 12.0 ± 3.4 species ·m −2 and 11.06 ± 2.5 species ·m −2 . The seed bank of burned exotic grassland contained significantly fewer seeds and species than that of burned native grassland. In addition, the seed bank in burned exotic grassland comprised mainly exotic grasses, whereas annual and perennial herbs, most of them native, dominated the seed bank of burned native grassland. Of the 50 species detected in soil samples, only 20 had a persistent seed bank, and only 1 of these was a native perennial bunchgrass. The preponderance of transient species means that eradication of exotic grasses must be followed by reseeding of native grasses and herbs, perhaps repeatedly, if native grassland is to replace exotic grassland.

Arizona↗

USGS2025

A review of the effects of climate change on visitor use in US public lands and waters

Climate change is affecting recreational visitor use in U.S. public lands and waters, causing changes to visitation levels, timing of trips, activity participation, and visitor safety. This report reviews the literature on how climate change is influencing visitor use in the United States and how visitor use may be affected in the future. Our goal is to provide the current state of the literature for managers of public lands and waters and provide foundational information for the development of a climate change vulnerability assessment methodology for visitor use within the National Park Service (that may be applicable to other federal lands and waters). Specifically, we investigate how seven different climate change factors may affect visitor use on public lands and waters. These factors consist of increasing temperatures; flooding, drought, and increased variability of precipitation; decreasing snowpack and earlier spring runoff; wildfires, smoke, and air quality; coastal hazards: hurricanes and sea level rise; harmful algal blooms (HABs); and zoonotic and vector-borne disease. The current research indicates that these factors are already affecting visitors to public lands and waters and continued effects in the future are likely as the climate warms. Additionally, we summarize existing research on how visitors to U.S. public lands and waters are adapting to climate change. Throughout the review, we note where there are substantial gaps in the literature and more research would help managers respond to the effects of climate change on visitor use.

Science Report↗

USGS2012

Short seed longevity, variable germination conditions, and infrequent establishment events provide a narrow window for Yucca brevifolia (Agavaceae) recruitment

PREMISE OF THE STUDY: The future of long-lived stand-forming desert plants such as Yucca brevifolia (Joshua tree) has come into question in light of climate variation and landscape-scale disturbances such as wildfire. Understanding plant establishment dynamics is important for mitigating the impacts of disturbances and promoting revegetation. • METHODS: We placed Y. brevifolia seeds in shallow caches and manipulated granivore access, nurse shrub effects, and the season of cache placement to determine conditions for seed germination and seedling establishment. • KEY RESULTS: Greatest seedling emergence occurred during spring and summer, when increased soil moisture was accompanied by warm soil temperatures. Late winter-spring emergence for cached seeds was enhanced beneath shrub canopies, but seedling survival declined beneath shrubs as temperatures increased in spring. Germinability of seed remaining in the soil was reduced from 50-68% after 12 mo residence time in soil and declined to <3% after 40 mo. Following dispersal from parent plants, seeds are either removed by granivores or lose germinability, imposing substantial losses of potential germinants. • CONCLUSIONS: Specific germination and establishment requirements impose stringent limits on recruitment rates for Y. brevifolia. Coupled with infrequent seed availability, the return rates to prefire densities and demographic structure may require decades to centuries, especially in light of potential changes to regional desert climate in combination with the potential for fire recurrence. Demographic patterns are predicted to vary spatially in response to environmental variability that limits recruitment and may already be apparent among extant populations.

American Journal of Botany↗

USGS2015

Direct and indirect effects of environmental variability on growth and survivorship of pre-reproductive Joshua trees, Yucca brevifolia Engelm (Agavaceae)

• Premise of study: Accurate demographic information about long-lived plant species is important for understanding responses to large-scale disturbances, including climate change. It is challenging to obtain these data from desert perennial plants because seedling establishment is exceptionally rare, and estimates of survival are lacking for their vulnerable early stages. Desert wildfires, urbanization, and climate change influence the persistence of the long-lived Yucca brevifolia . Quantitative demographic attributes are crucial for understanding how populations will respond to disturbances and where populations will recede or advance under future climate scenarios. • Methods: We measured survival in a cohort of 53 pre-reproductive Y. brevifolia at Yucca Flat, Nevada, USA, for 22 yr and recorded their growth, nurse-plant relationships, and herbivory. • Key results: Herbivory by black-tailed jackrabbits ( Lepus californicus ) caused severe losses of plants during the first and second years (45% and 31%, respectively). Surviving plants experienced <2.5% annual mortality. Survival for the population was 19% over 22 yr. Plants <25 cm in height had lower life expectancy. Average growth rate (± SD) for plants that survived to the last census was 3.12 ± 1.96 cm yr −1 , and growth rates were positively associated with precipitation. Thirty-year-old Y. brevifolia had not yet reproduced. • Conclusions: A rare establishment event for Y. brevifolia during 1983–1984, triggered by above-average summer rainfall, provided a unique opportunity to track early survival and growth. Infrequent but acute episodes of herbivory during drought influenced demography for decades. Variability in survival among young Y. brevifolia indicates that size-dependent demographic variables will improve forecasts for this long-lived desert species under predicted regional climate change.

Nevada↗