Damage from infestations of spongy moth (Lymantria dispar L.) in oak-dominated stands and southern pine beetle (Dendroctonus frontalis Zimmermann) in pine-dominated stands have far exceeded impacts of other disturbances in forests of the mid-Atlantic Coastal Plain over the last two decades. We used forest census data collected in …
Journal: Plos One, Volume 17 (5): e0265955 (2022), ISBN . DOI: 10.1371/journal.pone.0265955 Sites: US-Ced, US-Dix, US-Slt
Coastal wetlands provide the unique biogeochemical functions of storing a large fraction of the terrestrial carbon (C) pool and being among the most productive ecosystems in the world. However, coastal wetlands face numerous natural and anthropogenic disturbances that threaten their ecological integrity and C storage potential. To …
Journal: Forests, Volume 13 (8): 1264 (2022), ISBN . DOI: 10.3390/f13081264 Sites: US-NC4
Drainage of freshwater wetlands is common in coastal regions, although the effects on microbial extracellular enzyme activity (a key mediator of soil organic matter decomposition) in relation to spatial variability (microtopography and soil depth) are poorly understood. Soils were collected from organic (Oi, Oe, Oa) and mineral (A, …
Journal: Forests, Volume 13 (6): 861 (2022), ISBN . DOI: 10.3390/f13060861 Sites: US-NC4
Catchment‐scale response functions, such as transit time distribution (TTD) and evapotranspiration time distribution (ETTD), are considered fundamental descriptors of a catchment’s hydrologic and ecohydrologic responses to spatially and temporally varying precipitation inputs. Yet, estimating these functions is challenging, especially …
Journal: Hydrological Processes, Volume 35 (3): e14082 (2021), ISBN . DOI: 10.1002/hyp.14082 Sites: US-MtB
Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements …
Journal: Agricultural And Forest Meteorology, Volume 301-302: 108350 (2021), ISBN . DOI: 10.1016/j.agrformet.2021.108350 Sites: CA-ARB, CA-ARF, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-DBB, CA-ER1, CA-Gro, CA-Let, CA-Man, CA-MR3, CA-MR5, CA-Na1, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-NS6, CA-NS7, CA-Oas, CA-Obs, CA-Ojp, CA-Qc2, CA-Qcu, CA-Qfo, CA-SCC, CA-SF1, CA-SF2, CA-SF3, CA-SJ2, CA-SJ3, CA-TP1, CA-TP3, CA-TP4, CA-TPD, CA-WP1, US-A03, US-A10, US-A32, US-A74, US-ADR, US-AR1, US-AR2, US-ARb, US-ARc, US-ARM, US-Aud, US-Bar, US-Bi1, US-Bi2, US-Bkg, US-Blk, US-Blo, US-Bn1, US-Bn2, US-Bn3, US-Bo1, US-Bo2, US-Br3, US-CaV, US-Ced, US-CF1, US-CF2, US-CF3, US-CF4, US-ChR, US-Cop, US-CPk, US-CRT, US-Ctn, US-Dia, US-Dix, US-Dk1, US-Dk2, US-Dk3, US-EDN, US-Elm, US-EML, US-Fmf, US-FPe, US-FR2, US-FR3, US-Fuf, US-Fwf, US-GLE, US-GMF, US-Goo, US-Ha1, US-Ha2, US-Hn2, US-Hn3, US-Ho1, US-Ho2, US-Ho3, US-IB1, US-IB2, US-Ivo, US-KFS, US-KLS, US-Kon, US-KS1, US-KS2, US-KUT, US-Lin, US-Los, US-LPH, US-LWW, US-Me1, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MOz, US-Mpj, US-MRf, US-MtB, US-Myb, US-NC1, US-NC2, US-NC3, US-NC4, US-Ne1, US-Ne2, US-Ne3, US-NGB, US-NR1, US-Oho, US-ORv, US-PHM, US-Pon, US-Prr, US-RC1, US-RC2, US-RC3, US-RC4, US-RC5, US-Rls, US-Rms, US-Ro1, US-Ro2, US-Ro5, US-Ro6, US-Rpf, US-Rws, US-SdH, US-Seg, US-Ses, US-SFP, US-Shd, US-Skr, US-Slt, US-Snd, US-Sne, US-Snf, US-SO2, US-SO3, US-SO4, US-SP1, US-SP2, US-SP3, US-SRC, US-SRG, US-SRM, US-Srr, US-Sta, US-StJ, US-Syv, US-Ton, US-Tw1, US-Tw2, US-Tw3, US-Tw4, US-Tw5, US-Twt, US-Uaf, US-UMB, US-UMd, US-Var, US-Vcm, US-Vcp, US-Vcs, US-WBW, US-WCr, US-Wdn, US-Wgr, US-Whs, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi6, US-Wi7, US-Wi8, US-Wi9, US-Wjs, US-Wkg, US-Wlr, US-Wpp, US-WPT, US-Wrc, US-xBR, US-xCP, US-xDL, US-xHA, US-xKA, US-xKZ, US-xRM, US-xSR, US-xWD
Salt marshes are large carbon reservoirs as part of blue carbon ecosystems. Unfortunately, there is limited information about the net ecosystem (NEE) and methane (CH4) exchange between salt marshes and the atmosphere to fully understand their carbon dynamics. We tested the influence of biophysical drivers by plant phenological phases …
Journal: Agricultural And Forest Meteorology, Volume 300: 108309 (2021), ISBN . DOI: 10.1016/j.agrformet.2020.108309 Sites: US-StJ
Coastal settings variations are linked to composition, structural, and functional differences among mangrove ecotypes. Basin mangroves undergo larger flooding and salinity fluctuations, yet remain understudied, compared to other ecotypes. We evaluated the effect of flooding and air temperature (T a) on the surface energy balance …
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 126 (2): e2020JG005811 (2021), ISBN . DOI: https://doi.org/10.1029/2020JG005811 Sites: MX-PMm
Measurements of the spatial heterogeneity of methane fluxes in wetlands are critical to better understand and predict methane emissions at the ecosystem scale. However, the within-wetland spatial heterogeneity of fluxes is rarely assessed. Here, we use a spatially balanced rapid chamber-based survey of methane at different ecohydrological …
Journal: Science Of The Total Environment, Volume 767: 144498 (2021), ISBN . DOI: 10.1016/j.scitotenv.2020.144498 Sites: US-OWC
Three-dimensional (3D) vegetation canopy structure plays an important role in the way radiation interacts with the land surface. Accurately representing this process in Earth System models (ESMs) is crucial for the modeling of the global carbon, energy, and water cycles and hence future climate projections. Despite the importance …
Journal: Remote Sensing of Environment, Volume 261: (2021), ISBN . DOI: https://doi.org/10.1016/j.rse.2021.112497 Sites: US-NR1, US-UMB
Journal: Global Change Biology, Volume 27 (2): 359-375 (2021), ISBN . DOI: 10.1111/gcb.15414 Sites: US-Ton, US-Var