Variations in Atmospheric CO2CO_2 Mixing Ratios across a Boston, MA Urban to Rural Gradient

Urban areas are directly or indirectly responsible for the majority of anthropogenic $CO_2$ emissions. In this study, we characterize observed atmospheric $CO_2$ mixing ratios and estimated $CO_2$ fluxes at three sites across an urban-to-rural gradient in Boston, MA, USA. $CO_2$ is a well-mixed greenhouse gas, but we found significant differences across this gradient in how, where, and when it was exchanged. Total anthropogenic emissions were estimated from an emissions inventory and ranged from $1.5 to 37.3 mg·C·ha^{-1}·yr^{-1}$ between rural Harvard Forest and urban Boston. Despite this large increase in anthropogenic emissions, the mean annual difference in atmospheric $CO_2$ between sites was approximately 5% $(20.6 \pm 0.4 ppm)$. The influence of vegetation was also visible across the gradient. Green-up occurred near day of year 126, 136, and 141 in Boston, Worcester and Harvard Forest, respectively, highlighting differences in growing season length. In Boston, gross primary production—estimated by scaling productivity by canopy cover—was ~75% lower than at Harvard Forest, yet still constituted a significant local flux of $3.8 mg·C·ha^{-1}·yr^{-1}$. In order to reduce greenhouse gas emissions, we must improve our understanding of the space-time variations and underlying drivers of urban carbon fluxes.Engineering and Applied Science

Global urban environmental change drives adaptation in white clover

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

Mapping carbon storage in urban trees withmulti-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods

This dataverse repository contains two datasets: 1. A one square meter resolution map of biomass for the City of Boston. Units are Mg biomass per hectare (Mg/ha). 2. A one square meter resolution map of canopy cover for the City of Boston. Units are binary: 0 = no canopy, 1 = canopy Both datasets are derived from LiDAR and high resolution remote sensing imagery. Details of the methodology are provided in the following publications: Raciti, SM, Hutyra, LR, Newell, JD, 2014. Mapping carbon storage in urban trees withmulti-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods,Science of the Total Environment, 500-501, 72-83. http://dx.doi.org/10.1016/j.scitotenv.2014.08.070 Raciti, SM, Hutyra, LR, Newell, JD, 2015. Corrigendum to “Mapping carbon storage in urban trees with multi-source remote sensing data: Relationships between biomass, land use, and demographics in Boston neighborhoods”, Science of the Total Environment, 538, 1039-1041. http://dx.doi.org/10.1016/j.scitotenv.2015.07.154<br

Data from: Characterizing forest structure variations across an intact tropical peat dome using field samplings and airborne LiDAR

Tropical peat swamp forests (PSF) are one of the most carbon dense ecosystems on the globe and are experiencing substantial natural and anthropogenic disturbances. In this study we combined direct field sampling and airborne LiDAR to empirically quantify forest structure and aboveground live biomass (AGB) across a large, intact tropical peat dome in Northwestern Borneo. Moving up a 4m elevational gradient, we observed increasing stem density but decreasing canopy height, crown area and crown roughness. These findings were consistent with hypotheses that nutrient and hydrological dynamics co-influence forest structure and stature of the canopy individuals, leading to reduced productivity towards the dome interior. Gap frequency as a function of gap size followed a power law distribution with a shape factor (?) of 1.76 ± 0.06. Ground-based and dome-wide estimates of AGB were 217.7 ± 28.3 Mg C ha-1, and 222.4 ± 24.4 Mg C ha-1, respectively, which were higher than previously reported AGB for PSF and tropical forests in general. However, dome-wide AGB estimates were based on height statistics and we found the coefficient of variation on canopy height was only 0.08, three times less than stem diameter measurements, suggesting LiDAR height metrics may not be a robust predictor of AGB in tall tropical forests with dense canopies. Our structural characterization of this ecosystem advances the understanding of the ecology of intact tropical peat domes and factors that influence biomass density and landscape-scale spatial variation. This ecological understanding is essential to improve estimates of forest carbon density and its spatial distribution in PSF and to effectively model the effects of disturbance and deforestation in these carbon dense ecosystems

Mendaram live tree survey 2014

Csv contaning biometric data for live trees in Mendaram, Belait, Brunei

STEM LOCATIONS AND HEIGHTS IN ULU MENDARAM

THE STEM LOCATIONS AND HEIGHTS WERE EXTRACTED USING LOCAL MAXIMA FILTERING FROM A CANOPY HEIGHT MODEL AT 0.5M. THE CANOPY HEIGHT MODEL WAS PRODUCED USING SMALL FOOTPRINT AIRBORNE LIDAR DATA ACQUIRED IN 2010 OVER BRUNEI

Article Variations in Atmospheric CO2 Mixing Ratios across a Boston, MA Urban to Rural Gradient

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Methane Emissions from Natural Gas Infrastructure and Use in the Urban Region of Boston, Massachusetts

Archival datasets associated with with the paper McKain K, et al. (2015), including: continuous atmospheric methane and ethane concentration observations, and inventories of methane emissions by source type and natural gas consumption