Biophysical drivers of carbon dioxide and methane fluxes in a restored tidal freshwater wetland

Wetlands store large amounts of carbon (C) in biomass and soils, playing a crucial role in offsetting greenhouse gas (GHG) emissions; however, they also account for 30% of global yearly CH4 emissions. Anthropogenic disturbance has led to the decline of natural wetlands throughout the United States, with a corresponding increase in created and restored wetlands. Studies characterizing biogeochemical processes in restored forested wetlands, particularly those that are both tidal and freshwater, are lacking but essential for informing science- based carbon management

Tower-based greenhouse gas fluxes in a restored tidal freshwater wetland: A shared resource for research and teaching.

The goals of this study are: 1) to use an eddy-covariance system to continuously measure wetland-atmosphere CO2 and CH4 exchange in a restored forested wetland, 2) to quantity C sequestration in plant biomass and soils in restored (Kimages Creek watershed) and old-growth (Harris Creek watershed) forested wetlands, and 3) to establish a shared long-term, shared research and teaching platform centered on eddy-covariance tower measurements. Since the old-growth forest wetland has had longer to accumulate C, the current C stocks are likely much larger than those of the restored wetland; however, the rate of C accumulation (i.e., C sequestration or net ecosystem production) may be higher in young ecosystems (De Simon et al. 2 | Goodrich-Stuart (Stuart-Haëntjens) 2012). While natural wetlands generally offset the warming effect of CH4 emissions by also sequestering large amounts of CO2, but it has been suggested that, in the short-term, this may not hold true for restored wetlands (Petrescu et al. 2015). Very few restored wetlands have studied, however, so knowledge is lacking in this area

Net primary production of a temperate deciduous forest exhibits a threshold response to increasing disturbance severity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116346/1/ecy20159692478.pd

The Potential of Satellite Remote Sensing Time Series to Uncover Wetland Phenology under Unique Challenges of Tidal Setting

While growth history of vegetation within upland systems is well studied, plant phenology within coastal tidal systems is less understood. Landscape-scale, satellite-derived indicators of plant greenness may not adequately represent seasonality of vegetation biomass and productivity within tidal wetlands due to limitations of cloud cover, satellite temporal frequency, and attenuation of plant signals by tidal flooding. However, understanding plant phenology is necessary to gain insight into aboveground biomass, photosynthetic activity, and carbon sequestration. In this study, we use a modeling approach to estimate plant greenness throughout a year in tidal wetlands located within the San Francisco Bay Area, USA. We used variables such as EVI history, temperature, and elevation to predict plant greenness on a 14-day timestep. We found this approach accurately estimated plant greenness, with larger error observed within more dynamic restored wetlands, particularly at early post-restoration stages. We also found modeled EVI can be used as an input variable into greenhouse gas models, allowing for an estimate of carbon sequestration and gross primary production. Our strategy can be further developed in future research by assessing restoration and management effects on wetland phenological dynamics and through incorporating the entire Sentinel-2 time series once it becomes available within Google Earth Engine.Arts, Faculty ofNon UBCGeography, Department ofReviewedFacult

Increased salinity decreases annual gross primary productivity at a Northern California brackish tidal marsh

Tidal marshes sequester 11.4–87.0 Tg C yr ^−1 globally, but climate change impacts can threaten the carbon capture potential of these ecosystems. Tidal marshes occur across a wide range of salinity, with brackish marshes (0.5–18 ppt (parts per thousand)) dominating global tidal marsh extents. A diverse mix of freshwater- and saltwater-tolerant plant and microbial communities has led researchers to predict that carbon cycling in brackish wetlands may be less sensitive to changes in salinity than fresh- or saltwater wetlands. Rush Ranch, a well-monitored brackish tidal wetland of the San Francisco Bay National Estuarine Research Reserve, experiences highly variable annual salinity regimes. Within a five-year period (2014–2018), Rush Ranch experienced particularly extreme drought-induced salinization during the 2014 and 2015 growing seasons. During drought years, tidal channel salinity rose from a 15 year baseline of 4.7 ppt to growing season peaks of 10.3 ppt and 12.5 ppt. Continuous eddy covariance data from 2014 to 2018 demonstrate that during drought summers, gross primary productivity (GPP) decreased by 24%, whereas ecosystem respiration remained similar among all five years. Stepwise linear regression revealed that salinity, not air temperature or tidal height, was the dominant driver of annual GPP. A random forest model trained to predict GPP based on environmental data from low salinity years (i.e. naive to salinization) significantly over predicted GPP in drought years. When growing season salinities were doubled, annual estimates of net ecosystem exchange of CO _2 decreased by up to 30%. These results provide ecosystem-scale evidence that increased salinity influences CO _2 fluxes dominantly through reductions in GPP. This relationship provides a starting point for incorporating the effect of changes in salinity in wetland carbon models, which could improve wetland carbon forecasting and management for climate resilience

Appendix A. Aboveground wood net primary production (ANPPw) and litter trap leaf area index (LAIt) for all plots prior to and following peak disturbance, the fraction of tree basal area girdled in each plot, and the three most dominant upper canopy tree species with respect to basal area in each plot prior to disturbance.

Aboveground wood net primary production (ANPPw) and litter trap leaf area index (LAIt) for all plots prior to and following peak disturbance, the fraction of tree basal area girdled in each plot, and the three most dominant upper canopy tree species with respect to basal area in each plot prior to disturbance

The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)

Climate change is a world‐wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high‐quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. To overcome these challenges, we collected best‐practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re‐use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re‐use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second‐order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world

Defining a spectrum of integrative traitâ based vegetation canopy structural types

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest subâ set of this spectrum, we assess gradients in canopy structural traits, characterise canopy structural types (CST) and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that withinâ ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with subâ continental variation in forest types and ecoâ climatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modelling structureâ function relationships in vegetated ecosystems.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152994/1/ele13388_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152994/2/ele13388.pd