Geology topics

Gregory P. Asner

Publications and source records attributed to Gregory P. Asner.

11 recordsLinked to original sources

USGS2023

Linking vocal behaviours to habitat structure to create behavioural landscapes

The recent development of animal-borne sensors coupled with location data can provide insights into how individuals modify their behaviour with respect to specific habitat features. Animals can express a diverse array of behaviours as they navigate heterogenous landscapes, yet few studies have specifically evaluated the interaction of behaviours with habitat characteristics. We used a novel broadcast acoustic transmitter to investigate the interaction between vocal behaviours of an endemic Hawaiian thrush, the ʻōmaʻo, Myadestes obscurus , and habitat features across a naturally fragmented forest landscape. Through the development of behavioural landscape models that link specific vocalizations with space use, we found that the use of different vocalization types (calls, songs, whisper songs) were highly variable across the landscape but were associated with distinct habitat features. The likelihood of calls increased in an open lava matrix between forest patches, while whisper songs were more strongly associated with the dense interior areas of forest fragments. In contrast, the rate of ʻōmaʻo vocalizations overall decreased in the open lava matrix, suggesting that ʻōmaʻo may shift behaviours from territory defence to foraging as they transition through different habitats. Our study revealed context-specific changes in behaviour across ʻōmaʻo home ranges, including courtship, aggression and social interactions between individuals. Combining the use of a novel acoustic tool with automated radiotelemetry allowed us to overcome challenges associated with detection and analysis of variation in behaviour and resource selection across a highly heterogeneous landscape that would have been otherwise difficult to impossible.

Hawaii↗

USGS2022

Empirically validated drought vulnerability mapping in the mixed conifer forests of the Sierra Nevada

Severe droughts are predicted to become more frequent in the future, and the consequences of such droughts on forests can be dramatic, resulting in massive tree mortality, rapid change in forest structure and composition, and substantially increased risk of catastrophic fire. Forest managers have tools at their disposal to try to mitigate these effects but are often faced with limited resources, forcing them to make choices about which parts of the landscape to target for treatment. Such planning can greatly benefit from landscape vulnerability assessments, but many existing vulnerability analyses are unvalidated and not grounded in robust empirical datasets. We combined robust sets of ground-based plot and remote sensing data, collected during the 2012–2016 California drought, to develop rigorously validated tools for assessing forest vulnerability to drought-related canopy tree mortality for the mixed conifer forests of the Sequoia and Kings Canyon national parks and potentially for mixed conifer forests in the Sierra Nevada as a whole. Validation was carried out using a large external dataset. The best models included normalized difference vegetation index (NDVI), elevation, and species identity. Models indicated that tree survival probability decreased with greenness (as measured by NDVI) and elevation, particularly if trees were growing slowly. Overall, models showed good calibration and validation, especially for Abies concolor , which comprise a large majority of the trees in many mixed conifer forests in the Sierra Nevada. Our models tended to overestimate mortality risk for Calocedrus decurrens and underestimate risk for pine species, in the latter case probably due to pine bark beetle outbreak dynamics. Validation results indicated dangers of overfitting, as well as showing that the inclusion of trees already under attack by bark beetles at the time of sampling can give false confidence in model strength, while also biasing predictions. These vulnerability tools should be useful to forest managers trying to assess which parts of their landscape were vulnerable during the 2012–2016 drought, and, with additional validation, may prove useful for ongoing assessments and predictions of future forest vulnerability.

California↗

USGS2021

Ecosystem carbon balance in the Hawaiian Islands under different scenarios of future climate and land use change

The State of Hawai'i passed legislation to be carbon neutral by 2045, a goal that will partly depend on carbon sequestration by terrestrial ecosystems. However, there is considerable uncertainty surrounding the future direction and magnitude of the land carbon sink in the Hawaiian Islands. We used the Land Use and Carbon Scenario Simulator (LUCAS), a spatially explicit stochastic simulation model that integrates landscape change and carbon gain-loss, to assess how projected future changes in climate and land use will influence ecosystem carbon balance in the Hawaiian Islands under all combinations of two radiative forcing scenarios (RCPs 4.5 and 8.5) and two land use scenarios (low and high) over a 90 year timespan from 2010 to 2100. Collectively, terrestrial ecosystems of the Hawaiian Islands acted as a net carbon sink under low radiative forcing (RCP 4.5) for the entire 90 year simulation period, with low land use change further enhancing carbon sink strength. In contrast, Hawaiian terrestrial ecosystems transitioned from a net sink to a net source of CO 2 to the atmosphere under high radiative forcing (RCP 8.5), with high land use accelerating this transition and exacerbating net carbon loss. A sensitivity test of the CO 2 fertilization effect on plant productivity revealed it to be a major source of uncertainty in projections of ecosystem carbon balance, highlighting the need for greater mechanistic understanding of plant productivity responses to rising atmospheric CO 2 . Long-term model projections such as ours that incorporate the interactive effects of land use and climate change on regional ecosystem carbon balance will be critical to evaluating the potential of ecosystem-based climate mitigation strategies.

Hawaii↗

USGS2021

Mapping the vulnerability of giant sequoias after extreme drought in California using remote sensing

Between 2012 and 2016, California suffered one of the most severe droughts on record. During this period Sequoiadendron giganteum (giant sequoias) in the Sequoia and Kings Canyon National Parks (SEKI), California, USA experienced canopy water content (CWC) loss, unprecedented foliage senescence, and, in a few cases, death. We present an assessment of the vulnerability of giant sequoia populations to droughts that is currently lacking and needed for management. We used a temporal trend of remotely sensed CWC obtained between 2015 and 2017, and recently georeferenced giant sequoia crowns to quantify the vulnerability of 7,408 individuals in 10 groves in the northern portion of SEKI. CWC is sensitive to changes in liquid water in tree canopies; therefore, it is a useful metric for quantifying the response of sequoia trees to drought. Temporal trends indicated that 9% of giant sequoias had a significant decline or consistently low CWC, suggesting these trees were likely operating at low photosynthetic capacity and potentially at high risk to drought stress. We also found that 20% of the giant sequoias had an increase or consistently high level of CWC, indicating these trees were at low risk to drought stress. These vulnerability categories were used in a random forest model with a combination of topographic, fire-related, and climate variables to generate high-resolution vulnerability risk maps. These maps show that higher risk is associated with lower elevation and higher climate water deficit. We also found that sequoias at higher elevations but located near meadows had higher vulnerability risk. These results and the vulnerability maps can identify vulnerable sequoias that may be difficult to save or locations of refugia to be protected, and thus may aid forest managers in preparation for future droughts.

California↗

USGS2021

A new remote sensing-based Carbon Sequestration Potential Index (CSPI): A tool to support land carbon management

Integrating remote sensing into assessments of carbon stocks and fluxes has advanced our understanding of how global change affects landscapes and our capacity to support decision making about forest management. However, there remains a lack of detailed and actionable analyses conducted across widely ranging environmental conditions that are appropriate for tactical planning. We used airborne laser scanning data and multi-source satellite imagery to estimate forest aboveground carbon density and gross primary production, and to map forest cover across the main Hawaiian Islands. We used these measures to develop the Carbon Sequestration Potential Index (CSPI), which identifies where the potential for carbon sequestration following afforestation would be highest within a complex landscape of 304 management units. Variation in CSPI was high across islands and between ecosystems, with low values for cool, dry and largely intact forest systems and high values for warm, wet and largely non-forested systems. The CSPI provided a rapid, spatially-explicit and actionable assessment of Hawaiian forest reserves, which can help stewardship agencies contribute to state carbon neutrality goals through climate-smart and science-driven prescriptions that encompass conservation to restoration.

Hawaii↗

USGS2018

Landscape-scale variation in canopy water content of giant sequoias during drought

Recent drought (2012–2016) caused unprecedented foliage dieback in giant sequoias ( Sequoiadendron giganteum ), a species endemic to the western slope of the southern Sierra Nevada in central California. As part of an effort to understand and map sequoia response to droughts, we studied the patterns of remotely sensed canopy water content (CWC), both within and among sequoia groves in two successive years during the drought period (2015 and 2016). Our aims were: (1) to quantify giant sequoia responses to severe drought stress at a landscape scale using CWC as an indicator of crown foliage status, and (2) to estimate the effect of environmental correlates that mediate CWC change within and among giant sequoia groves. We utilized airborne high fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) data from the Carnegie Airborne Observatory to assess giant sequoia foliage status during 2015 and 2016 of the 2012–2016 droughts. A series of statistical models were generated to classify giant sequoias and to map their location in Sequoia and Kings Canyon National Parks (SEKI) and vicinity. We explored the environmental correlates and the spatial patterns of CWC change at the landscape scale. The mapped CWC was highly variable throughout the landscape during the two observation years, and proved to be most closely related to geological substrates, topography, and site-specific water balance. While there was an overall net gain in sequoia CWC between 2015 and 2016, certain locations (lower elevations, steeper slopes, areas more distant from surface water sources, and areas with greater climate water deficit) showed CWC losses. In addition, we found greater CWC loss in shorter sequoias and those growing in areas with lower sequoia stem densities. Our results suggest that CWC change indicates sequoia response to droughts across landscapes. Long-term monitoring of giant sequoia CWC will likely be useful for modeling and predicting their population-level response to future climate change.

California↗

USGS2018

Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought

California experienced severe drought from 2012 to 2016, and there were visible changes in the forest canopy throughout the State. In 2014, unprecedented foliage dieback was recorded in giant sequoia ( Sequoiadendron giganteum ) trees in Sequoia National Park, in the southern California Sierra Nevada mountains. Although visible changes in sequoia canopies can be recorded, biochemical and physiological responses to drought stress in giant sequoia canopies are not well understood. Ground-based measurements provide insight into the mechanisms of drought responses in trees, but are often limited to few individuals, especially in trees of tall stature such as giant sequoia. Recent studies demonstrate that remotely measured forest canopy water content (CWC) is a general indicator of canopy response to drought, but the underpinning leaf- to canopy-level causes of observed variation in CWC remain poorly understood. We combined field and airborne remote sensing measurements taken in 2015 and 2016 to assess the biophysical responses of giant sequoias to drought. In 49 study trees, CWC was related to leaf water potential, but not to the other foliar traits, suggesting that changes in CWC were made at whole-canopy rather than leaf scales. We found a non-random, spatially varying pattern in mapped CWC, with lower CWC values at lower elevation and along the outer edges of the groves. This pattern was also observed in empirical measurements of foliage dieback from the ground, and in mapped CWC across multiple sequoia groves in this region, supporting the hypothesis that drought stress is expressed in canopy-level changes in giant sequoias. The fact that we can clearly detect a relationship between CWC and foliage dieback, even without taking into account prior variability or new leaf growth, strongly suggests that remotely sensed CWC, and changes in CWC, are a useful measure of water stress in giant sequoia, and valuable for assessing and managing these iconic forests in drought.

California↗

USGS2018

Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section

Hotter droughts are becoming more common as climate change progresses, and they may already have caused instances of forest dieback on all forested continents. Learning from hotter droughts, including where on the landscape forests are more or less vulnerable to these events, is critical to help resource managers proactively prepare for the future. As part of our Leaf to Landscape Project, we measured the response of giant sequoia, the world’s largest tree species, to the extreme 2012–2016 hotter drought in California. The project integrated leaf-level physiology measurements, crown-level foliage dieback surveys, and remotely sensed canopy water content (CWC) to shed light on mechanisms and spatial patterns in drought response. Here we summarize initial findings, present a conceptual model of drought response, and discuss management implications; details are presented in the other four articles of the special section on Giant Sequoias and Drought. Giant sequoias exhibited both leaf- and canopy-level responses that were effective in protecting whole-tree hydraulic integrity for the vast majority of individual sequoias. Very few giant sequoias died during the drought compared to other mixed conifer tree species; however, the magnitude of sequoia drought response varied across the landscape. This variability was partially explained by local site characteristics, including variables related to site water balance . We found that low CWC is an indicator of recent foliage dieback, which occurs when stress levels are high enough that leaf-level adjustments alone are insufficient for giant sequoias to maintain hydraulic integrity. CWC or change in CWC may be useful indicators of drought stress that reveal patterns of vulnerability to future hotter droughts. Future work will measure recovery from the drought and strengthen our ability to interpret CWC maps. Our ultimate goal is to produce giant sequoia vulnerability maps to help target management actions, such as reducing other stressors, increasing resistance to hotter drought through prescribed fire or mechanical thinning, and planting sequoias in projected future suitable habitat, which may occur outside current grove distributions. We suggest that managers compare different types of vulnerability assessments and combine vulnerability maps with other sources of information to inform decisions.

California↗

USGS2017

What mediates tree mortality during drought in the southern Sierra Nevada?

Severe drought has the potential to cause selective mortality within a forest, thereby inducing shifts in forest species composition. The southern Sierra Nevada foothills and mountains of California have experienced extensive forest dieback due to drought stress and insect outbreak. We used high-fidelity imaging spectroscopy (HiFIS) and light detection and ranging (LiDAR) from the Carnegie Airborne Observatory (CAO) to estimate the effect of forest dieback on species composition in response to drought stress in Sequoia National Park. Our aims were: (1) to quantify site-specific conditions that mediate tree mortality along an elevation gradient in the southern Sierra Nevada Mountains; (2) to assess where mortality events have a greater probability of occurring; and (3) to estimate which tree species have a greater likelihood of mortality along the elevation gradient. A series of statistical models were generated to classify species composition and identify tree mortality, and the influences of different environmental factors were spatially quantified and analyzed to assess where mortality events have a greater likelihood of occurring. A higher probability of mortality was observed in the lower portion of the elevation gradient, on southwest and west-facing slopes, in areas with shallow soils, on shallower slopes, and at greater distances from water. All of these factors are related to site water balance throughout the landscape. Our results also suggest that mortality is species-specific along the elevation gradient, mainly affecting Pinus ponderosa and Pinus lambertiana at lower elevations. Selective mortality within the forest may drive long-term shifts in community composition along the elevation gradient.

Sierra Nevada↗

USGS2011

LiDAR: Providing structure

Since the days of MacArthur, three-dimensional (3-D) structural information on the environment has fundamentally transformed scientific understanding of ecological phenomena (MacArthur and MacArthur 1961). Early data on ecosystem structure were painstakingly laborious to collect. However, as reviewed and reported in recent volumes of Frontiers(eg Vierling et al. 2008; Asner et al.2011), advances in light detection and ranging (LiDAR) remote-sensing technology provide quantitative and repeatable measurements of 3-D ecosystem structure that enable novel ecological insights at scales ranging from the plot, to the landscape, to the globe. Indeed, annual publication of studies using LiDAR to interpret ecological phenomena increased 17-fold during the past decade, with over 180 new studies appearing in 2010 (ISI Web of Science search conducted on 23 Mar 2011: [{lidar AND ecol*} OR {lidar AND fores*} OR {lidar AND plant*}]).

Frontiers in Ecology and the Environment↗

USGS2009

Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies

For two decades, remotely sensed data from imaging spectrometers have been used to estimate non-pigment biochemical constituents of vegetation, including water, nitrogen, cellulose, and lignin. This interest has been motivated by the important role that these substances play in physiological processes such as photosynthesis, their relationships with ecosystem processes such as litter decomposition and nutrient cycling, and their use in identifying key plant species and functional groups. This paper reviews three areas of research to improve the application of imaging spectrometers to quantify non-pigment biochemical constituents of plants. First, we examine recent empirical and modeling studies that have advanced our understanding of leaf and canopy reflectance spectra in relation to plant biochemistry. Next, we present recent examples of how spectroscopic remote sensing methods are applied to characterize vegetation canopies, communities and ecosystems. Third, we highlight the latest developments in using imaging spectrometer data to quantify net primary production (NPP) over large geographic areas. Finally, we discuss the major challenges in quantifying non-pigment biochemical constituents of plant canopies from remotely sensed spectra.

Remote Sensing of Environment↗