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Woody plant encroachment (WPE) into grasslands has been occurring globally and may be accelerated by climate change in the future. This land cover change is expected to alter the carbon and water cycles, but it remains uncertain how and to what extent the carbon and water cycles may change with WPE into grasslands under current climate. In this study, we examined the difference of vegetation indices (VIs), evapotranspiration (ET), gross primary production (GPP), and solar-induced chlorophyll fluorescence (SIF) during 2000-2010 between grasslands and juniper-encroached grasslands. We also quantitatively assessed the changes of GPP and ET for grasslands with different proportions of juniper encroachment (JWPE). Our results suggested that JWPE increased the GPP, ET, greenness-related VIs, and SIF of grasslands. Mean annual GPP and ET were, respectively, ~55% and ~45% higher when grasslands were completely converted into juniper forests under contemporary climate during 2000-2010. The enhancement of annual GPP and ET for grasslands with JWPE varied over years ranging from about +20% GPP (~+30% for ET) in the wettest year (2007) to about twice as much GPP (~+55% for ET) in the severe drought year (2006) relative to grasslands without encroachment. Additionally, the differences in GPP and ET showed significant seasonal dynamics. During the peak growing season (May-August), GPP and ET for grasslands with JWPE were ~30% and ~40% higher on average. This analysis provided insights into how and to what degree carbon and water cycles were impacted by JWPE, which is vital to understanding how JWPE and ecological succession will affect the regional and global carbon and water budgets in the future.

Knowing the stand age of rubber tree (Hevea brasiliensis) plantations is vitally important for best management practices, estimations of rubber latex yields, and carbon cycle studies (e.g., biomass, carbon pools, and fluxes). However, the stand age (as estimated from the establishment year of rubber plantation) is not available across large regions. In this study, we analyzed Landsat time series images from 1987–2015 and developed algorithms to identify (1) the establishment year of rubber plantations; and (2) the pre-conversion land cover types, such as old rubber plantations, evergreen forests, and cropland. Exposed soil during plantation establishment and linear increases in canopy closure during non-production periods (rubber seedling to mature plantation) were used to identify the establishment year of rubber plantations. Based on the rubber plantation map for 2015 (overall accuracy = 97%), and 1981 Landsat images since 1987, we mapped the establishment year of rubber plantations on Hainan Island (R2 = 0.85/0.99, and RMSE = 2.34/0.54 years at pixel/plantation scale). The results show that: (1) significant conversion of croplands and old rubber plantations to new rubber plantations has occurred substantially in the northwest and northern regions of Hainan Island since 2000, while old rubber plantations were mainly distributed in the southeastern inland strip; (2) the pattern of rubber plantation expansion since 1987 consisted of fragmented plantations from smallholders, and there was no tendency to expand towards a higher altitude and steep slope regions; (3) the largest land source for new rubber plantations since 1988 was old rubber plantations (1.26 × 105 ha), followed by cropland (0.95 × 105 ha), and evergreen forests (0.68 × 105 ha). The resultant algorithms and maps of establishment year and pre-conversion land cover types are likely to be useful in plantation management, and ecological assessments of rubber plantation expansion in China. [ABSTRACT FROM AUTHOR]

• Optimum air temperature of photosynthesis from GPP EC agree well with those from MODIS EVI. • Optimum air temperature of photosynthesis from GPP EC and MODIS EVI differed substantially from those that are currently used in satellite-based models. • Use of optimum air temperature of photosynthesis from site-year specific or biome-specific approaches can affects global GPP estimates substantially. Gross primary productivity (GPP) of vegetation is affected by air temperature. Biogeochemical models use the optimum air temperature (T opt) parameter, which comes from biome-specific look-up tables (T opt − b − LT). Many studies have shown that plants have the capacity to adapt to changes in environmental conditions over time, which suggests that the static T opt − b − LT parameters in the biogeochemical models may poorly represent actual T opt and induce uncertainty in GPP estimates. Here, we estimated biome-specific, site-year-specific, and site-specific optimum air temperature using GPP data from eddy covariance (EC) flux tower sites (GPP EC) (T opt − b − EC , T opt − sy − EC , T opt − s − EC), the Enhanced Vegetation Index (EVI) from MODIS images (T opt − b − EVI , T opt − sy − EVI , T opt − s − EVI), and mean daytime air temperature (T DT). We evaluated the consistency among the four T opt parameters (T opt − b , T opt − sy , T opt − s and T opt − b − LT), and assessed how they affect satellite-based GPP estimates. We find that T opt parameters from MODIS EVI agree well with those from GPP EC , which indicates that EVI can be used as a variable to estimate T opt at individual pixels over large spatial domains. T opt − b , T opt − sy , and T opt − s differed significantly from T opt − b − LT. GPP estimates using T opt − b and T opt − sy were more consistent with GPP EC than when using T opt − b − LT for all the land cover types. Our use of T opt − sy substantially improved 8-day and annual GPP estimates across biomess (from 1% to 34%), especially for cropland, grassland, and open shrubland. Our simple calculation shows that global GPP estimates differ by up to 10 Pg C/yr when using our suggested T opt − sy − EVI instead of using the static T opt − b − LT. Our new approach on estimating T opt has the potential to improve estimates of GPP from satellite-based models, which could lead to better understanding of carbon-climate interactions. [ABSTRACT FROM AUTHOR]

• Divergent albedo responses to greenness in alpine (TP) and temperate (IM) grasslands. • Sensitivity of albedo to greenness was highest in early growing season. • Albedo-greenness relationship changed from negative to positive in growing season in TP. Changes in Earth's albedo due to vegetation dynamics, snow cover, and land cover change have attracted much attention. However, the effects of vegetation dynamics on albedo have not been comprehensively documented according to its spatial (regional), temporal (within growing season), and spectral (visible, near-infrared, and shortwave) characteristics. This study examined the effects of vegetation greenness on albedo from 2000 to 2014 in China's grasslands, which have considerable intra- and inter-annual variations, using remote sensing-based albedo and two-band Enhanced Vegetation Index (EVI2) data. Generally, we found an insignificant negative correlation between the shortwave (SW) albedo and EVI2 for grasslands in China. However, the visible (VIS) albedo was more sensitive to changes in vegetation greenness than near-infrared (NIR) albedo in China's grasslands. The relationship between the NIR albedo and EVI2 was more complicated, especially in the Tibetan Plateau (TP), where the correlation was negative in the early growing season and positive in the late growing season; while the correlation between the NIR albedo and EVI2 was always negative in main part of Inner Mongolia (IM). The different albedo-EVI2 relationships in IM and TP may be related to differences in soil albedos. The higher sensitivity of the SW albedo to vegetation greenness change in IM, the stronger effect on land surface radiation budget. Our finding about vegetation-induced changes in albedo differ in space, time and spectral bands is expected to contribute to the improvement of land surface models. [ABSTRACT FROM AUTHOR]

Over the past few decades, wide encroachment of eastern redcedar ( Juniperus virginiana ) and Ashe juniper ( Juniperus ashei ) into the prairies of the U.S. Great Plains has affected wildlife habitats, forage and livestock production, and biogeochemical cycles. This study investigates the spatio-temporal dynamics of juniper forest encroachment into tallgrass prairies by generating juniper forest encroachment maps from 1984 to 2010 at 30 m spatial resolution. A pixel and phenology-based mapping algorithm was used to produce the time series maps of juniper forest encroachment using a combination of Phased Array type L-band Synthetic Aperture Radar (PALSAR) mosaic data from 2010 and Landsat 5 and 7 data (10,871 images from 1984 to 2010). We analyzed the resultant maps to understand the dynamics of juniper forest encroachment at state and county spatial scales and examined juniper occurrence by geographic region and soil type. The juniper forest maps were generated over five multi-year periods: the late 1980s (1984–1989), early 1990s (1990–1994), late 1990s (1995–1999), early 2000s (2000–2004), and late 2000s (2005–2010). We also produced a map of time since stand detection of juniper forests in 2010. Our major findings include: (1) juniper forests have expanded linearly in time at an annual rate of ~ 40 km 2 /year since 1984; (2) juniper forests had notable spatial clusters in its expansion process; (3) ~ 65% of juniper forests in 2010 were < 15 years after stands have been detected; and (4) juniper forests in 2010 were mainly distributed in sandy and loamy soils with relatively low available water storage in the top soils. This study demonstrates the potential of combining a cloud computing platform (Google Earth Engine), time series optical images (Landsat), and microwave images to document the spatial-temporal dynamics of juniper forest encroachment into prairies since the 1980s at the regional scale. The results can be used to study the causes, consequences, and potential future distribution of juniper encroachment, which are relevant to the sustainable management of prairie ecosystems. [ABSTRACT FROM AUTHOR]

Woody plant encroachment of eastern redcedar ( Juniperus virginiana L., hereafter referred to as “red cedar” ) into native grasslands in the U.S. Southern Great Plains has significantly affected the production of forage and livestock, wildlife habitats, as well as water, carbon, nutrient and biogeochemical cycles. However, time series of red cedar maps are still not available to document the continuously spatio-temporal dynamics of red cedar encroachment across landscape, watershed and regional scales. In this study, we developed a pixel and phenology-based mapping algorithm, and used it to analyze PALSAR mosaic data in 2010 and all the available Landsat 5/7 data during 1984–2010 with the Google Earth Engine (GEE) platform. This pilot study analyzed 4233 images covering > 10 counties in the central region of Oklahoma, and generated red cedar forest maps for 2010 and five historical time periods: the late 1980s (1984–1989), early 1990s (1990–1994), late 1990s (1995–1999), early 2000s (2000–2004), and late 2000s (2005–2010). The resultant maps for 2010, the late 2000s, early 2000s, and late 1990s were evaluated using validation samples collected from Google Earth's high-resolution images and geo-referenced field photos. The overall (producer and user) accuracy of these maps ranged from 88% to 96% (88%–93%, and 96%–99%). The resultant maps clearly illustrated an increase in red cedar encroachment within the study area at an annual rate of ~ 8% during 1984–2010. These maps can be used to support additional studies on the driving factors and consequences of red cedar encroachment. This study also demonstrated the potential to trace the historical encroachment of red cedar into grasslands using time series Landsat images and PALSAR data. [ABSTRACT FROM AUTHOR]

• Percentage maps of juniper forest encroachment at 1 km are generated during 2000–2015. • Climate variable changes are examined at regional scale by pairwise analysis models. • We quantified climate variable changes with each percentage increase of woody cover. • Roles of hydroclimates are assessed on climate impacts of juniper woody encroachment. Woody plant encroachment (WPE) into grasslands has been exacerbated by climate change and human activities. WPE may affect local climate by altering the exchange of mass and energy between the land surface and the atmosphere. The lack of studies on the effects of WPE on local climate hinders our understanding of the interactions between changes in regional vegetation cover and climate. Here, we analyzed the differences of land surface temperature (ΔLST), albedo (ΔAlbedo) and evapotranspiration (ΔET) between juniper-woody-encroached grasslands and adjacent pure grasslands using 16-years of remote sensing data. Our results showed that juniper woody plant encroachment (JWPE) into the semi-arid and sub-humid grasslands reduced daytime LST and albedo, but increased nighttime LST and ET from an annual scale analysis. With each one percent increase in juniper cover, annual mean daytime ΔLST decreased ~0.026 °C, nighttime ΔLST increased ~0.01 °C, daily ΔLST decreased ~0.008 °C, Δalbedo decreased ~0.053%, and ΔET increased ~1.31 mm/year. Furthermore, it is suggested that the impacts of JWPE on LST and ET were stronger in dry years than in normal and pluvial years, and that no significant variations in albedo were found among the different hydrological conditions. These results provide insights into applying satellite-based techniques to understand the feedbacks between woody vegetation dynamics and local climate change. [ABSTRACT FROM AUTHOR]