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NASA NTRS2020

Costa Rica & Panama Ecological Forecasting II: Identifying Current and Future Areas of Environmental Concern in La Amistad International Park to Inform Resource Management

Seven percent of all scientifically known life forms lie within the 202,230 square miles of Central America, making this area ecologically unique and increasing the need for environmental management. The Mesoamerican Biological Corridor forms a conservation partnership throughout Central America to establish a forested corridor of over 600 protected areas. Although conservation programs exist, deforestation still afflicts the area, putting strain on these diverse ecosystems. La Amistad International Park in southern Costa Rica and northern Panama in particular faces conflicting land use changes. Expanding agricultural development and urbanization, combined with concern over indigenous land rights, have raised questions about the implementation of sustainability goals and communication strategies within the region. To help address these issues, the NASA DEVELOP Costa Rica & Panama Ecological Forecasting II team continued a partnership with the Ministry of Environment and Energy in Costa Rica and the National Environmental Authority in Panama. The team created a Land Use Conflict Identification Strategy (LUCIS) model based on land cover maps for 2019 and 2029 that were created in term I using imagery from Landsat 8 Operational Land Imager (OLI). With partner input, the team applied weights to different objectives and combined suitability maps to identify areas of potential biodiversity conflict. Additionally, the team created a Short-term Forest Change (SFTC) Tool using Terra Moderate Resolution Imaging Spectroradiometer, Landsat 8 OLI, and Sentinel-2 Multispectral Instrument to help the partners identify areas of immediate, major forest changes. The LUCIS model indicated higher agricultural growth when compared to the ecological category.

Ecological Forecasting↗
NASA NTRSDate not supplied

Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested Sites

Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).

Edward Ayres↗
NASA NTRS1999

Northern Forest Ecosystem Dynamics Using Coupled Models and Remote Sensing

Forest ecosystem dynamics modeling, remote sensing data analysis, and a geographical information system (GIS) were used together to determine the possible growth and development of a northern forest in Maine, USA. Field measurements and airborne synthetic aperture radar (SAR) data were used to produce maps of forest cover type and above ground biomass. These forest attribute maps, along with a conventional soils map, were used to identify the initial conditions for forest ecosystem model simulations. Using this information along with ecosystem model results enabled the development of predictive maps of forest development. The results obtained were consistent with observed forest conditions and expected successional trajectories. The study demonstrated that ecosystem models might be used in a spatial context when parameterized and used with georeferenced data sets.

Ranson, K. J.↗
NASA NTRS2022

Megafires in a Warming World: What Wildfire Risk Factors Led to California’s Largest Recorded Wildfire

Massive wildfires and extreme fire behavior are becoming more frequent across the westernUnited States, creating a need to better understand how megafire behavior will evolve in our warmingworld. Here, the fire spread model Prometheus is used to simulate the initial explosive growth ofthe 2020 August Complex, which occurred in northern California (CA) mixed conifer forests. Hightemperatures, low relative humidity, and daytime southerly winds were all highly correlated withextreme rates of modeled spread. Fine fuels reached very dry levels, which accelerated simulationgrowth and heightened fire heat release (HR). Model sensitivity tests indicate that fire growth andHR are most sensitive to aridity and fuel moisture content. Despite the impressive early observedgrowth of the fire, shifting the simulation ignition to a very dry September 2020 heatwave predicted a>50% increase in growth and HR, as well as increased nighttime fire activity. Detailed model analysesof how extreme fire behavior develops can help fire personnel prepare for problematic ignitions.

Kevin Varga↗
NASA NTRS2019

Role of forest regrowth in global carbon sink dynamics

Although the existence of a large carbon sink in terrestrial ecosystems is well-established, the drivers of this sink remain uncertain. It has been suggested that perturbations to forest demography caused by past land-use change, management, and natural disturbances may be causing a large component of current carbon uptake. Here we use a global compilation of forest age observations, combined with a terrestrial biosphere model with explicit modeling of forest regrowth, to partition the global forest carbon sink between old-growth and regrowth stands over the period 1981–2010. For 2001–2010 we find a carbon sink of 0.85 (0.66–0.96) Pg/year located in intact old-growth forest, primarily in the moist tropics and boreal Siberia, and 1.30 (1.03–1.96) Pg/year located in stands regrowing after past disturbance. Approaching half of the sink in regrowth stands would have occurred from demographic changes alone, in the absence of other environmental changes. These age-constrained results show consistency with those simulated using an ensemble of demographically-enabled terrestrial biosphere models following an independent reconstruction of historical land use and management. We estimate that forests will accumulate an additional 69 (44–131) Pg C in live biomass from changes in demography alone if natural disturbances, wood harvest, and reforestation continue at rates comparable to those during 1981–2010. Our results confirm that it is not possible to understand the current global terrestrial carbon sink without accounting for the sizeable sink due to forest demography. They also imply that a large portion of the current terrestrial carbon sink is strictly transient in nature.

forest↗
NASA NTRS2012

Retrieval of Vertical LAI Profiles Over Tropical Rain Forests using Waveform Lidar at La Selva, Costa Rica

This study explores the potential of waveform lidar in mapping the vertical and spatial distributions of leaf area index (LAI) over the tropical rain forest of La Selva Biological Station in Costa Rica. Vertical profiles of LAI were derived at 0.3 m height intervals from the Laser Vegetation Imaging Sensor (LVIS) data using the Geometric Optical and Radiative Transfer (GORT) model. Cumulative LAI profiles obtained from LVIS were validated with data from 55 ground to canopy vertical transects using a modular field tower to destructively sample all vegetation. Our results showed moderate agreement between lidar and field derived LAI (r2=0.42, RMSE=1.91, bias=−0.32), which further improved when differences between lidar and tower footprint scales (r2=0.50, RMSE=1.79, bias=0.27) and distance of field tower from lidar footprint center (r2=0.63, RMSE=1.36, bias=0.0) were accounted for. Next, we mapped the spatial distribution of total LAI across the landscape and analyzed LAI variations over different land cover types. Mean values of total LAI were 1.74, 5.20, 5.41 and 5.62 over open pasture, secondary forests, regeneration forests after selective-logging and old-growth forests respectively. Lastly, we evaluated the sensitivities of our LAI retrieval model to variations in canopy/ground reflectance ratio and to waveform noise such as induced by topographic slopes. We found for both, that the effects were not significant for moderate LAI values (about 4). However model derivations of LAI might be inaccurate in areas of high-slope and high LAI (about 8) if ground return energies are low. This research suggests that large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the high LAI levels in tropical rain forests and may be a useful tool for understanding the light transmittance within these canopies.

Tang, Hao↗
NASA NTRS1984

Modeling long-term changes in forested landscapes and their relation to the Earth's energy balance

The dynamics of the forested parts of the Earth's surface on time scales from decades to centuries are discussed. A set of computer models developed at Oak Ridge National Laboratory and elsewhere are applied as tools. These models simulate a landscape by duplicating the dynamics of growth, death and birth of each tree living on a 0.10 ha element of the landscape. This spatial unit is generally referred to as a gap in the case of the forest models. The models were tested against and applied to a diverse array of forests and appear to provide a reasonable representation for investigating forest-cover dynamics. Because of the climate linkage, one important test is the reconstruction of paleo-landscapes. Detailed reconstructions of changes in vegetation in response to changes in climate are crucial to understanding the association of the Earth's vegetation and climate and the response of the vegetation to climate change.

Shugart, H. H.↗
NASA NTRSDate not supplied

Haiti Agriculture II: Evaluating the Success of Reforestation Practices in Haiti

The Caribbean country of Haiti has an extensive history of deforestation and environmental degradation stemming from French colonization. Over the past 33 years, the Haiti Reforestation Partnership (HRP) and their partners, Comprehensive Development Program (CODEP), have planted approximately 15.52 million trees. However, these efforts lacked scientific guidance to ensure successful forest stand survival. The NASA DEVELOP team partnered with the HRP to create a habitat suitability model (HSM) by using PlanetScope and Sentinel-2 Multispectral Instrument (MSI) imagery. The team also incorporated Landsat 8 and 9 OLI surface temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar, and ancillary datasets to analyze areas suitable for future reforestation efforts. The habitat model suggested locations with higher forest stand survival based on topography, soil health, climate, and feasibility to access suggested locations. We confirmed the HSM through a cross-analyzation of high enhanced vegetation index (EVI) values. Areas with lower EVI values and higher suitability based on the HSM were suggested for future planting as they lack well-established forest stands but have optimal conditions for growth. Through the creation of the HSM, the team provided the HRP with static maps of high suitability, a 3D printed elevation model, and a guidebook for animators. Additionally, the team provided a structured video highlighting the HRP’s efforts. Effective reforestation and better forest stand survival would help to achieve the goal of securing community food security. This would also serve as a guide to expand planting efforts into other locations and communities.

Kelli Roberts↗
NASA NTRS1977

The value of volume and growth measurements in timber sales management of the National Forests

This paper summarizes work performed in the estimation of gross social value of timber volume and growth rate information used in making regional harvest decisions in the National Forest System. A model was developed to permit parametric analysis. The problem is formulated as one of finding optimal inventory holding patterns. Public timber management differs from other inventory holding problems in that the inventory, itself, generates value over time in providing recreational, aesthetic and environmental goods. 'Nontimber' demand estimates are inferred from past Forest Service harvest and sales levels. The solution requires a description of the harvest rates which maintain the optimum inventory level. Gross benefits of the Landsat systems are estimated by comparison with Forest Service information gathering models. Gross annual benefits are estimated to be $5.9 million for the MSS system and $7.2 million for the TM system.

Lietzke, K. R.↗
NASA NTRS2012

Carbon Consequences of Forest Disturbance and Recovery Across the Conterminous United States

Forests of North America are thought to constitute a significant long term sink for atmospheric carbon. The United States Forest Service Forest Inventory and Analysis (FIA) program has developed a large data base of stock changes derived from consecutive estimates of growing stock volume in the US. These data reveal a large and relatively stable increase in forest carbon stocks over the last two decades or more. The mechanisms underlying this national increase in forest stocks may include recovery of forests from past disturbances, net increases in forest area, and growth enhancement driven by climate or fertilization by CO2 and Nitrogen. Here we estimate the forest recovery component of the observed stock changes using FIA data on the age structure of US forests and carbon stocks as a function of age. The latter are used to parameterize forest disturbance and recovery processes in a carbon cycle model. We then apply resulting disturbance/recovery dynamics to landscapes and regions based on the forest age distributions. The analysis centers on 28 representative climate settings spread about forested regions of the conterminous US. We estimate carbon fluxes for each region and propagate uncertainties in calibration data through to the predicted fluxes. The largest recovery-driven carbon sinks are found in the South central, Pacific Northwest, and Pacific Southwest regions, with spatially averaged net ecosystem productivity (NEP) of about 100 g C / square m / a driven by forest age structure. Carbon sinks from recovery in the Northeast and Northern Lake States remain moderate to large owing to the legacy of historical clearing and relatively low modern disturbance rates from harvest and fire. At the continental scale, we find a conterminous U.S. forest NEP of only 0.16 Pg C/a from age structure in 2005, or only 0.047 Pg C/a of forest stock change after accounting for fire emissions and harvest transfers. Recent estimates of NEP derived from inventory stock change, harvest, and fire data show twice the NEP sink we derive from forest age distributions. We discuss possible reasons for the discrepancies including modeling errors and the possibility of climate and/or fertilization (CO2 or N) growth enhancements.

Williams, Christopher A.↗
NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗
NASA NTRS2015

Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery

Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.

Neigh, Christopher S. R.↗
NASA NTRS1987

Boreal forests and atmosphere - Biosphere exchange of carbon dioxide

Two approaches to investigating the role of boreal forests in the global carbon cycle are presented. First, a tracer support model which incorporates the normalized-difference vegetation index obtained from advanced, very high resolution radiometer radiances was used to simulate the annual cycle of CO2 in the atmosphere. Results indicate that the seasonal growth of the combined boreal forests of North America and Eurasia accounts for about 50 percent of the mean seasonal CO2 amplitude recorded at Pt. Barrow, Alaska and about 30 percent of the more globally representative CO2 signal at Mauna Loa, Hawaii. Second, tree-ring width data from four boreal treeline sites in northern Canada were positively correlated with Pt. Barrow CO2 drawdown for the period 1971-1982. These results suggest that large-scale changes in the growth of boreal forests may be contributing to the observed increasing trend in CO2 amplitude. They further suggest that tree-ring data may be applicable as indices for CO2 uptake and remote sensing estimates of photosynthetic activity.

D'Arrigo, Rosanne↗
NASA NTRS2011

Changes in the Carbon Cycle of Amazon Ecosystems During the 2010 Drought

Satellite remote sensing was combined with the NASA-CASA carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production (NPP) in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO2 uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon River basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO2 to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to forests outside the main river floodplains.

Potter, Christophera↗
NASA NTRS1981

Remote sensing aided procedure for conifer growth modeling in the northeastern Sierra Nevada

The objective of this study was to use remotely-sensed data with ground-acquired data for preparing inputs to a mathematical model for generation of a potential conifer growth map of a wildland area. The study area, jointly selected by the resource managers of the U.S. Forest Service at the Plumas National Forest and researchers, covers approximately 500 sq km in the northeastern scrapment of Sierra Nevada. The approach involved a computerized databank based on both remotely-sensed and ground-acquired data. The remotely-sensed data included Landsat Multispectral Scanner (MSS) data, NOAA-5 Very High Resolution Radiometer (VHRR) data and U-2 Color infrared photography. The ground data included U.S. Geological Survey (USGS) topographic maps, Defense Mapping Agency (DMA)/USGS digital terrain data, soil maps, and vegetation data. The results included a series of maps for the final product as well as the intermediate products. The intermediate products were potential evapotranspiration, aspect, and soil plant available water.

Smith, H. G.↗
NASA NTRS2007

Climate-Induced Boreal Forest Change: Predictions versus Current Observations

For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

Soja, Amber J.↗
NASA NTRS2013

Characterization of ASTER GDEM Elevation Data over Vegetated Area Compared with Lidar Data

Current researches based on areal or spaceborne stereo images with very high resolutions (less than 1 meter) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is a state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 meters) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that accurate co-registration between ASTER GDEM and the National Elevation Dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-seconds and further improved to 0.6 if only homogenous vegetated areas were considered.

vegetation canopy↗