Josh M. Gray

Bio: Josh M. Gray is an academic researcher from North Carolina State University. The author has contributed to research in topics: Land cover & Phenology. The author has an hindex of 18, co-authored 32 publications receiving 2399 citations. Previous affiliations of Josh M. Gray include Boston University & Beijing Normal University.

Net carbon uptake has increased through warming-induced changes in temperate forest phenology

Abstract: The timing of life-history events has a strong impact on ecosystems. Now, analysis of the phenology of temperate forests in the eastern US indicates that in the case of an earlier spring and a later autumn, carbon uptake (photosynthesis) increases considerably more than carbon release (respiration).

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery.

Abstract: Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the "greenness rising" and end of the "greenness falling" stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery

Abstract: Plant phenology regulates ecosystem services at local and global scales and is a sensitive indicator of global change. Estimates of phenophase transition dates, such as the start of spring or end of fall, can be derived from sensor- based time series, but must be interpreted in terms of bio- logically relevant events. We use the PhenoCam archive of digital repeat photography to implement a consistent proto- col for visual assessment of canopy phenology at 13 temper- ate deciduous forest sites throughout eastern North America, and to perform digital image analysis for time-series-based estimation of phenophase transition dates. We then compare these results to remote sensing metrics of phenophase tran- sition dates derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Reso- lution Radiometer (AVHRR) sensors. We present a new type of curve fit that uses a generalized sigmoid function to es- timate phenology dates, and we quantify the statistical un- certainty of phenophase transition dates estimated using this method. Results show that the generalized sigmoid provides estimates of dates with less statistical uncertainty than other curve-fitting methods. Additionally, we find that dates de- rived from analysis of high-frequency PhenoCam imagery have smaller uncertainties than satellite remote sensing met- rics of phenology, and that dates derived from the remotely sensed enhanced vegetation index (EVI) have smaller uncer- tainty than those derived from the normalized difference veg- etation index (NDVI). Near-surface time-series estimates for the start of spring are found to closely match estimates de- rived from visual assessment of leaf-out, as well as satel- lite remote-sensing-derived estimates of the start of spring. However late spring and fall phenology metrics exhibit larger differences between near-surface and remote scales. Differ- ences in late spring phenology between near-surface and re- mote scales are found to correlate with a landscape metric of deciduous forest cover. These results quantify the effect of landscape heterogeneity when aggregating to the coarser spatial scales of remote sensing, and demonstrate the impor- tance of accurate curve fitting and vegetation index selection when analyzing and interpreting phenology time series.

The Environmental Protection Agency

Abstract: The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

On underestimation of global vulnerability to tree mortality and forest die‐off from hotter drought in the Anthropocene

Abstract: Patterns, mechanisms, projections, and consequences of tree mortality and associated broad-scale forest die-off due to drought accompanied by warmer temperatures—“hotter drought”, an emerging characteristic of the Anthropocene—are the focus of rapidly expanding literature. Despite recent observational, experimental, and modeling studies suggesting increased vulnerability of trees to hotter drought and associated pests and pathogens, substantial debate remains among research, management and policy-making communities regarding future tree mortality risks. We summarize key mortality-relevant findings, differentiating between those implying lesser versus greater levels of vulnerability. Evidence suggesting lesser vulnerability includes forest benefits of elevated [CO2] and increased water-use efficiency; observed and modeled increases in forest growth and canopy greening; widespread increases in woody-plant biomass, density, and extent; compensatory physiological, morphological, and genetic mechanisms; dampening ecological feedbacks; and potential mitigation by forest management. In contrast, recent studies document more rapid mortality under hotter drought due to negative tree physiological responses and accelerated biotic attacks. Additional evidence suggesting greater vulnerability includes rising background mortality rates; projected increases in drought frequency, intensity, and duration; limitations of vegetation models such as inadequately represented mortality processes; warming feedbacks from die-off; and wildfire synergies. Grouping these findings we identify ten contrasting perspectives that shape the vulnerability debate but have not been discussed collectively. We also present a set of global vulnerability drivers that are known with high confidence: (1) droughts eventually occur everywhere; (2) warming produces hotter droughts; (3) atmospheric moisture demand increases nonlinearly with temperature during drought; (4) mortality can occur faster in hotter drought, consistent with fundamental physiology; (5) shorter droughts occur more frequently than longer droughts and can become lethal under warming, increasing the frequency of lethal drought nonlinearly; and (6) mortality happens rapidly relative to growth intervals needed for forest recovery. These high-confidence drivers, in concert with research supporting greater vulnerability perspectives, support an overall viewpoint of greater forest vulnerability globally. We surmise that mortality vulnerability is being discounted in part due to difficulties in predicting threshold responses to extreme climate events. Given the profound ecological and societal implications of underestimating global vulnerability to hotter drought, we highlight urgent challenges for research, management, and policy-making communities.

Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009

Abstract: Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production.

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006 M I C H A E L A. W H I T E*, K I R S T E N M. DE BEURS w , K A M E L D I D A Nz, D AV I D W. I N O U Y E § ,

Abstract: Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ! 60 days and in standard deviation by ! 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS

Optical remotely sensed time series data for land cover classification: A review

Abstract: Accurate land cover information is required for science, monitoring, and reporting. Land cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring and mapping of land cover and land cover change in a consistent and robust manner over large areas is made possible with Earth Observation (EO) data. Land cover products satisfying a range of science and policy information needs are currently produced periodically at different spatial and temporal scales. The increased availability of EO data—particularly from the Landsat archive (and soon to be augmented with Sentinel-2 data)—coupled with improved computing and storage capacity with novel image compositing approaches, have resulted in the availability of annual, large-area, gap-free, surface reflectance data products. In turn, these data products support the development of annual land cover products that can be both informed and constrained by change detection outputs. The inclusion of time series change in the land cover mapping process provides information on class stability and informs on logical class transitions (both temporally and categorically). In this review, we present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization.