Effects of post fire ecology on plant species and abundance in Southern Californian Semi-Arid Shrublands

Chaparral strands are considered to be fire- adapted due to diverse recovery mechanisms used by chaparral plant species during secondary succession. The mixture of seeds used in the mulch for the hydroseeded site may be a combination of species native to California but not specific to the CSUSM site. Ultimately the natural emergence of native plants may be affected by hydroseeding, which can result in a decline of native plant diversity. Changes in fire frequency and/or intensity may also occur. Hydroseeding affects initial post- fire recovery of native chaparral vegetation, due to species exclusivity of seed-mixes. It was hypothesized that species diversity and abundance as well as plant cover would be higher in the area treated with hydroseed. 8 individual plots per treatment of unburned and burned, naturally regenerating and hydroseeded, stands at CSUSM. Topsoil (0-10 cm) was collected on February 1, 2019 from 24 randomly located plots (n = 8 plots/site). Woody shrubs (green shrubs) were measured for canopy area and species identification. Identified species included Adenostoma fasiciculatum, Acmispon glaber, Ceanothus tomentosus, Mimulus aurantiacus, Malosma laurina, and Salvia mellifera. The hydroseeded stand had the most diversity among plant species while the unburned stand had the least. Hydroseeded stands have more diversity due to the seed mixture of mulch that was used to initiate restoration on the CSUSM site. There was a significant difference across four major plant species. The mixture of seeds used in the mulch for the hydroseeded site may be a combination of species native to California but not specific to the CSUSM site. Ultimately the natural emergence of native plants may be affected by hydroseeding, which can result in a decline of native plant diversity. Changes in fire frequency and/or intensity may also occur

Temporal and spatial differences of methane flux at arctic tundra in Alaska

High latitude ecosystems were thought to enhance CH_4 emission in relation to the current arctic warming. However, we have little information about this potential feedback mechanisms on climate change, thus, model parameterization is insufficient and the observational data are required. We observed CH_4 flux at several types of tundra in Alaska over the growing seasons since 1995. From these observed data, we examined current CH_4 emission and its controlling factors on Alaskan tundra. Then we discussed about spatial and temporal differences in CH_4 flux. Daily trend of half hourly CH_4 flux had little relation with soil temperature, but the seasonal trend of daily flux changed with soil or water temperature. Cumulative CH_4 fluxes during the growing seasons were 8.1gCH_4m^(-2) on wet sedge tundra at Happy Valley in 1995, 3.3gCH_4m^(-2) on non-acidic moist tundra in 1996, and 3.58-8.24gCH_4m^(-2) on wet sedge tundra at Barrow between 1999-2003. Non-acidic tundra had low CH_4 emission with low CO_2 accumulation. There was large spatial difference in CH_4 flux caused by tundra type, and the large temporal difference at the wet sedge tundra reflected yearly weather variability

Ecological research in the Large Scale Biosphere Atmosphere Experiment in Amazonia: A discussion of early results

The Large-scale Biosphere–Atmosphere Experiment in Amazonia (LBA) is a multinational, interdisciplinary research program led by Brazil. Ecological studies in LBA focus on how tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in the Amazon region. Early results from ecological studies within LBA emphasize the variability within the vast Amazon region and the profound effects that land-use and land-cover changes are having on that landscape. The predominant land cover of the Amazon region is evergreen forest; nonetheless, LBA studies have observed strong seasonal patterns in gross primary production, ecosystem respiration, and net ecosystem exchange, as well as phenology and tree growth. The seasonal patterns vary spatially and interannually and evidence suggests that these patterns are driven not only by variations in weather but also by innate biological rhythms of the forest species. Rapid rates of deforestation have marked the forests of the Amazon region over the past three decades. Evidence from ground-based surveys and remote sensing show that substantial areas of forest are being degraded by logging activities and through the collapse of forest edges. Because forest edges and logged forests are susceptible to fire, positive feedback cycles of forest degradation may be initiated by land-use-change events. LBA studies indicate that cleared lands in the Amazon, once released from cultivation or pasture usage, regenerate biomass rapidly. However, the pace of biomass accumulation is dependent upon past land use and the depletion of nutrients by unsustainable land-management practices. The challenge for ongoing research within LBA is to integrate the recognition of diverse patterns and processes into general models for prediction of regional ecosystem function

Surface albedo and temperature models for surface energy balance fluxes and evapotranspiration using SEBAL and Landsat 8 over Cerrado-Pantanal, Brazil

The determination of the surface energy balance fluxes (SEBFs) and evapotranspiration (ET) is fundamental in environmental studies involving the effects of land use change on the water requirement of crops. SEBFs and ET have been estimated by remote sensing techniques, but with the operation of new sensors, some variables need to be parameterized to improve their accuracy. Thus, the objective of this study is to evaluate the performance of algorithms used to calculate surface albedo and surface temperature on the estimation of SEBFs and ET in the Cerrado-Pantanal transition region of Mato Grosso, Brazil. Surface reflectance images of the Operational Land Imager (OLI) and brightness temperature (Tb) of the Thermal Infrared Sensor (TIRS) of the Landsat 8, and surface reflectance images of the MODIS MOD09A1 product from 2013 to 2016 were combined to estimate SEBF and ET by the surface energy balance algorithm for land (SEBAL), which were validated with measurements from two flux towers. The surface temperature (Ts) was recovered by different models from the Tb and by parameters calculated in the atmospheric correction parameter calculator (ATMCORR). A model of surface albedo (asup) with surface reflectance OLI Landsat 8 developed in this study performed better than the conventional model (acon) SEBFs and ET in the Cerrado-Pantanal transition region estimated with asup combined with Ts and Tb performed better than estimates with acon. Among all the evaluated combinations, SEBAL performed better when combining asup with the model developed in this study and the surface temperature recovered by the Barsi model (Tsbarsi ). This demonstrates the importance of an asup model based on surface reflectance and atmospheric surface temperature correction in estimating SEBFs and ET by SEBAL

MODELLING GROSS PRIMARY PRODUCTION OF TROPICAL FOREST BY REMOTE SENSING

The application of remote sensing has provided an opportunity to improve the estimation of gross primary production (GPP) on a regional scale. Several models to estimate GPP of homogeneous ecosystems, such as agricultural areas, entirely based on remote sensing data exist, but models to describe more heterogeneous areas are less common. Thus, the aim of the study was to evaluate the GPP estimated by different remote sensing methods in an Amazon-Cerrado transition forest in Mato Grosso, using MODIS spectral data. Two models, known as the temperature and greenness model (TG) and the vegetation index (VI) model, were used to estimate seasonal and interannual variations in GPP. Our results indicated that the TG and VI models were incapable of reproducing the seasonal variation in GPP, because the lack of correlation between vegetation indices and the GPP measured from tower-based eddy covariance (GPPEC). Furthermore, the time series of the enhanced vegetation index (EVI) was delayed by 2 months with GPPEC. The results presented in this paper highlight some of the complexities in validating satellite products. Further study over a variety of Brazilian forests is needed to quantitatively assess the TG and VI and other methods to improve their accuracy

Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems

© 2017 by the author. Arctic tundra ecosystems are a major source of methane (CH 4 ), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH 4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100-1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH 4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH 4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH 4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales

Mecanismos de Controle da Variação Sazonal da Transpiração de uma Floresta de Transição Amazônia Cerrado

No presente trabalho foi estudada a variação sazonal datranspiração, de uma floresta tropical, e sua dependência com fatoresbióticos e abióticos. Utilizaram-se dados do projeto Experimento de GrandeEscala da Biosfera-Atmosfera na Amazônia (LBA), coletados floresta detransição Amazônia-cerrado, norte de Mato Grosso. Os valores máximosda condutividade de superfície (Cs), foram observados no período úmido(0,17 m s-1), e os mínimos (0,011 s m-1) no período de transição úmidoseco.A condutância aerodinâmica (Ca) máxima foi 0,052 m s-1 no períodoúmido e 0,068 m s-1 no período seco. A análise horária do fator dedesacoplamento sugere que a evapotranspiração, durante a manhã, tem ummaior controle realizado pela disponibilidade de energia, quando comparadoao período menos chuvoso. Durante a tarde verifica-se que o dossel dafloresta progressivamente tende a estar mais acoplado à atmosfera, para osperíodos estudados, demonstrando maior controle superficial natranspiração

Índice de Área Foliar em Floresta de Transição Amazonia Cerrado em Diferentes Métodos de Estimativa

The Leaf Area Index (LAI) is a vegetation biophysical variableused for various primary production models across scales and global modelsof climate, hydrology, biogeochemistry and ecology. This paper comparesthree estimates of LAI by at transitional forest Amazon Cerrado. LAI isestimated on field measurements where were utilized light canopytransmittance through the Beer-Lambert equation, remotely sensedModerate Resolution Imaging Spectroradiometer (MODIS) monthly LAIproduct and hemispherical photographs. LAI based on field observationsfor Beer-Lambert equation presented seasonality, obtaining an annual meanvalue of 3.21 to 3.74 m2 m-2 in 2001 to 2003. LAI through MODIS sensorLAI product presented value of 5.25 a 5.54 m2 m-2 in 2001 to 2003. LAIbased on hemispherical photographs presented value of 3.05±0.52 to4.12±0.56 m2 m-2 in Jun/2004 to May/2005 (Silva, 2006). The MODISproduct did not presented significant correlation with others methods. TheMODIS LAI product for transitional forest and tropical forest tropicalcould be important for studies of canopy dynamics and need to be validatedto be used reliable in coupling biosphere atmosphere models.O Índice de Área Foliar (IAF) é uma importante variável biofísicada vegetação usada em vários modelos de produção primária através de escalase modelos globais de clima, hidrologia, biogeoquímica e ecologia. Esseartigo compara três estimativas de IAF na floresta de transição AmazôniaCerrado. O IAF é estimado por observações de campo da transmitância deluz e equação de Lambert-Beer, por sensoriamento remoto utilizando oproduto mensal IAF do sensor remoto Moderate Resolution ImagingSpectroradiometer (MODIS) e por fotografias hemisféricas. O IAF estimadopor Lambert-Beer apresentou sazonalidade e uma média anual variandode 3,21 a 3,74 m2m-2 para os anos de 2001 a 2003. A média de IAFestimada pelo produto MODIS variou de 5,25 a 5,54 m2m-2 para os anos de2001 a 2003. A média de IAF estimada por fotografias hemisféricas varioude 3,05±0,52 a 4,12±0,56 m2m-2 para o período de Jun/2004 a Mai/2005(Silva, 2006). O IAF obtido pelo produto MODIS não apresentou correlaçãosignificativa com o IAF estimado pela lei de Lambert-Beer e por fotografiashemisféricas. O produto IAF do sensor MODIS para floresta detransição e florestas tropicais pode ser importante para estudos de dinâmicade dossel e precisa ser validado para ser utilizado com segurança emmodelos de acoplamento biosfera-atmosfera.Palavras-chave: transmitância da luz no dossel, área foliar, sensoriamentoremoto, floresta tropical

Methane fluxes during the initiation of a large-scale water table manipulation experiment in the Alaskan Arctic tundra

Much of the 191.8 Pg C in the upper 1 m of Arctic soil of Arctic soil organic mater is, or is at risk of, being released to the atmosphere as CO2 and/or CH4. Global warming will further alter the rate of emission of these gases to the atmosphere. Here we quantify the effect of major environmental variables affected by global climate change on CH4 fluxes in the Alaskan Arctic. Soil temperature best predicts CH4 fluxes and explained 89% of the variability in CH4 emissions. Water table depth has a nonlinear impact on CH4 efflux. Increasing water table height above the surface retards CH4 efflux. Decreasing water table depth below the surface has a minor effect on CH4 release once an aerobic layer is formed at the surface. In contrast with several other studies, we found that CH4 emissions are not driven by net ecosystem exchange (NEE) and are not limited by labile carbon supply