The chambers were secured to the tree stem at a height of 0.1-0.3-m for the 2014 and 2015 campaigns (with additional heights at 0.75-m, 1.30-m and 2.00-m in 2015) using cam buckle straps. Gas samples were taken by syringe at 0, 5, 10 and 15 minutes to account for chamber size, and injected into vials as described above. Collection of soil temperature and soil water content data during gas sampling was limited to 28 May - 14 June 2014 and 2 - 6 July 2014 due to equipment malfunction. Consequently, the values presented here were collected monthly from the plots as part of the long-term monitoring of the litter manipulation experiment (Brechet et al. unpublished data). Soil temperature at 0-10-cm depth was measured adjacent to the collars using a soil temperature probe and volumetric soil water content at 0-6 cm depth was measured using a Thetaprobe (Delta-T Devices, Cambridge, UK) calibrated to local soil conditions following the manufacturer’s instructions. Solar radiation data is provided by the Physical Monitoring Program of the Smithsonian Tropical Research Institute in 15-minute intervals, measured on a meteorological tower on BCI at 48-m height using a LiCor LI200X pyranometer (LiCor, Nebraska, USA). The daytime data were modified in R to provide a weekly mean solar radiation value.
1800 % for N 2 O) (Kroon et al., 2010). Based on the mass
balance in the atmospheric boundary layer, the equilibrium method assumes that the exchange at the top of the boundary layer and the exchange at the land surface are in equilibrium over periods longer than about 1 month (Betts, 2000). The largest source of uncertainty of this method lies in determin- ing the background concentration above the boundary layer and the entrainment rate at the top of the boundary layer. In- verse modeling determines the land surface flux by using at- mospheric transport models that are constrained by observed tracegas concentrations. The prior land surface flux, land surface observations, the meteorological inputs, and atmo- spheric transportation schemes are all important for deter- mining the accuracy of the modeled flux (Peters et al., 2007). As a result, the deficiency in any of these four factors can limit the accuracy of the model.
In the UK, which formed the initial focus for this review, lowland peat ecosystems are less commonly studied than upland peatlands. In many other areas of the boreo- temperate zone, where continental type bogs and fens pre- dominate, a distinction between ‘upland’ and ‘lowland’ peats is rarely made, with most peatlands (and hence most peat-related research) falling within the latter category. Nevertheless, this systematic review has demonstrated that there are relatively few studies in the evidence base that provide robust comparisons of C and GHG fluxes in relation to management, and that more studies are re- quired on the impacts of land management on lowland peatland systems. We have identified a range of com- monly investigated land management practices and a list of commonly recorded outcome measures. These findings demonstrate the key knowledge gaps within this topic area. They also highlight areas for which some evidence currently exists but where additional data are required to strengthen current findings. Table 10 demonstrates the major gaps in the evidence-base in regards to meta- analysable groups of studies. These knowledge gaps ap- pear to lie in the following areas: the effect of restoration on N 2 O emissions; the effect of fertilizer on fluxes of all
Exchange of sensible and latent heat constitutes an impor- tant part of the surface energy balance, driving many local- , regional- and global-scale climatological processes. The available energy for these turbulent fluxes is determined pre- dominantly by net radiation and the ground heat flux. The partitioning of available energy between the sensible and latent heat fluxes, which can be described in terms of the Bowen ratio, is strongly influenced by vegetation and soil properties (Betts et al., 2007). Also, release of latent heat to the atmosphere, i.e. evapotranspiration, is a key compo- nent of the water cycle in peatlands and forests, also affecting soil moisture and forest productivity, which further affect the GHG fluxes in a forest. In a temperate deciduous broadleaf forest, evapotranspiration has been found to recover rapidly after clear-cutting: the latent heat flux increased over the first 3 years, while the sensible heat flux declined correspondingly (Williams et al., 2013). It is unknown if this also happens in peatland forests.
The primary study location is a large compensatory mitigation site (1704 ha; 35854 0 22 00 N, 76809 0 25 00 E; Fig. 1), known as the Timberlake Restoration Project (TLRP) and owned by Great Dismal Swamp Mitigation Bank (Chesapeake, Virginia, USA). TLRP drains to the Little Alligator River, which ﬂows into the Alligator River and Albemarle Sound. The elevation in TLRP ranges from 1 m to 2 m above sea level (lidar survey by National Center for Airborne Laser Mapping 2008, Houston, Texas, USA). The TLRP property historically was the headwaters for coastal blackwater streams, with pocosin vegetation in higher elevation areas (Needham 2006). Swamp forests in the site were cleared, drained, and converted to agriculture in the 1970s, while some areas remained forested. The TLRP property currently contains drained shrub–scrub wetlands, restored and selectively timbered forested wetlands, and former agricultural ﬁelds undergoing stream and wetland restoration. The former corn and soybean farmland within TLRP (440 ha), last harvested in 2004, is the restored wetland (RW) that is the focus of our study. Restoration of the TLRP agricultural area towards a forested wetland was initiated in 2004 by lowering the
0.66 to 0.77; NSE = 0.66 to 0.77) compare to the validation results (Table 2.5); comparison of NEE means also resembled the validation and calibration results (daytime mean difference: 0.05 to 1.21 µmol/m 2 /s, nighttime mean difference: 0.03 to 0.51 µmol/m 2 /s) (Table 2.6).
For visualization, scattered plots of the observed versus the generalized model predicted NEE for different years between 2006 and 2013 (independent of the calibration years) for the five study forests were presented (Figure 2.10). Similar to the performance of the site-specific models (calibrations and validations), the quality of predictions from the generalized model was notably good for all the sites except the Missouri Ozark. The scaled harmonic model could not entirely predict the extreme peaks (carbon emissions) and troughs (sequestrations) of NEE, resulting in a reduction of modeling performance. The possible reasons could be (i) the existence of higher parameter sensitivity and modeling uncertainty in the nighttime hours away from the reference hour (Figure 2.11, 2.12) that is being reflected in the predicted extreme values, (ii) use of the temporally and spatiotemporally averaged parameters (day-specific model parameters would make far better predictions for extremes), (iii) random sampling errors, which are a function of averaging time (Baldocchi, 2003) and statistical error from gap filling (Falge et al., 2001), and (iv) inability of the model to predict instantaneous perturbations amid the moderate geographical gradients in climate, topography, soil type, hydrology, forest stand age and ecology among the five deciduous forests (Table 2.1). The predictions of different diurnal NEE cycles for all the study sites using a single parameter set demonstrated a high spatiotemporal robustness of the dimensionless, scaled model. The overall results indicate that the scaling-based generalized ESHA model can be utilized to predict diurnal NEE cycles at other deciduous forest ecosystems (which are not included in this study) if the corresponding day-specific single reference
pogenic global warming. Understanding the magnitude of GHG fluxes in natural ecosystems has recently become a pri- ority in the study of GHG balances (Merbold et al., 2015). Tropical intact forests cover 1392 Mha globally and repre- sent about 70 % of the total tropical forest area (1949 Mha), which accounts for the largest area of global forest biomes (∼ 50 %). Very few reliable long-term datasets on full GHG balances are available from tropical ecosystems, despite their known importance for the global cycles of these three GHGs (Dutaur and Verchot, 2007). This is in part due to the chal- lenges of designing and operating continuous, multi-gas flux analysis systems in tropical forests. Soil processes in partic- ular are responsible for an important part of GHGs that are produced or consumed in tropical ecosystems (Oertel et al., 2016). Soil physical, chemical, and biological characteristics are linked to variation in GHG emissions from soils, which in turn can display very high spatial and temporal variability (Arias-Navarro et al., 2017; Silver et al., 1999).
small changes or no changes, depending upon the size of anaerobic zone.
2.1. Site description
This study took place at two wetland sites, Area 3A (A3A) and Area 2 South (A2S), at High Acres Nature Area (HANA) in Fairport, NY (Figure 2). The distance between the sites is approximately one kilometer. These wetlands are managed by Waste Management of New England and New York, LLC and were created to comply with the Clean Water Act "No Net Loss" policy to mitigate the loss of natural wetlands. A2S was created in 2009, and A3A was created in 2012. The land-use history of these sites differ, A2S was used for row crop agriculture where as A3A was previously used as a livestock pasture. They also have different vegetation and hydrology. A2S is dominated by Typha spp. (Typha latifolia and Typha angustifolia, broad and narrow leaf cattail) and Phalaris arundinacea (reed canary grass. A3A is more diverse, with upland species including Polygonum persicaria (smart weed), Solidago canadensis (common goldenrod), Epilobium (willow herb), Schoenoplectus tabernaemontani (softsteam bulrush),
The unfertilized arable soil exhibited the highest N 2 O production, whereas all fertilized soil samples revealed similar patterns of N 2 O production with only small amounts of emitted nitrous oxide (figure 3.21). Thus, the denitrifiers could have been either inhibited by addition of the fertilizers or the ratio of the denitrification products N 2 O and N 2 was in favor of N 2 production. An inhibition of the denitrification activity could be excluded by incubation of the fertilized soils and the bare soil under anoxic atmosphere containing 10% acetylene to repress the N 2 O reductase so that only N 2 O was produced. All fertilized soil samples showed a similar or even faster N 2 O production than the bare soil (figure 3.23). After 53 h of incubation, similar N 2 O concentrations were found in all investigated samples. Consequently, the ratio of N 2 O and N 2 must have been decreased by fertilizer addition during the anoxic incubation without acetylene (figure 3.21). Firestone and Davidson (1989) and Granli and Bøckman (1994) compiled in their reviews the impact of different factors on the N 2 O/N 2 ratio during denitrification. Since temperature, absence of oxygen, soil moisture content, and nitrate content remained more or less unaffected by fertilization in comparison to the unfertilized soil, the addition of organic carbon through the fertilizers might have led to the shift of end products towards N 2 . The assumption is in accordance with the literature where easily degradable organic carbon is considered to promote full reduction to N 2 , i.e. low N 2 O/N 2 ratios (Elliott et al. 1990; Weier et al. 1993). Furthermore, the faster increase of N 2 O in the fertilized soils suggested a higher denitrification rate presumably also provoked by the added organic carbon through the manures (Paul and Beauchamp 1989; Drury et al. 1991). The question whether the soil autochtonous or the imported denitrifiers by the manures caused this result remains open. However, observations made during the greenhouse experiment investigating the nirS gene fragments of denitrifiers after manuring indicated a possible stimulation of fertilizer derived denitrifying bacteria (figure 3.28).
The conversion of forests to agricultural lands, followed by long-term agricultural use can lead to lower levels of soil organic matter (SOM). The loss of SOM in
agricultural soils can be counteracted by amendment with residual waste materials (RWM) like biosolids and composts. These materials add C and N to the soil, affecting physical, chemical, and biological properties and processes, including production of C and N-containing greenhouse gases (GHGs): CO 2 , CH 4 and N 2 O. This, coupled with spatial and temporal variations in temperature and moisture, control the flux of C and N-containing GHGs from soil. We used microcosms to investigate the magnitude and direction of GHG flux as a function of soil temperature and moisture in an agricultural soil amended with RWM. Soil was amended with 10 Mg total C ha -1 in the form of paper fiber with chicken manure (PF), dehydrated food waste (DFW), yard waste compost (YW), biosolids and yard waste compost (BIO), multisource compost (MC), or 112 kg N ha -1 of mineral fertilizer (MF). Un-amended soil was used as a control (CTL). Soil moisture was adjusted to permanent wilting point, field capacity or saturation. Microcosms were incubated at 10, 15, 20, or 25°C and gas concentrations determined over 14 days. The highest CO 2 flux was observed at 25°C and field capacity, with CO 2 production following the order
natural greenhousegas (GHG)) plays one of the key roles influencing global climate (Myhre et al., 2013). Through their properties of allowing short-wave solar radiation to fall onto earth almost unhindered and in turn to absorb long-wave radiation emitted from the warm earth, they exhibit an energetic state for a certain time period emitting infrared radiation of which a substantial share has a heating effect and thus results in global warming. This natural GHG effect is vital for the existence of life on planet earth by increasing mean global air temperature from around -18 °C to 15 °C (UBA, 2017). However, since the beginning of industrialization, human activity leads to strong in- creases (Figure 2.1) and changes in the composition of atmospheric GHGs.
Until recently, the vast majority of restoration activity, policy attention and research has been focused on upland blanket bogs. While blanket bogs are of great importance to the UK environment and its carbon stores given their great extent, the intensity of land-use pressures and the resulting magnitude of GHG emissions per unit area tends to be greater for modified lowland peatlands. Furthermore, the transferability of GHG flux measurements and wider scientific understanding from blanket bogs to lowland raised bogs and fens is doubtful given the differences between them in terms of vegetation, hydrological function, topography, nutrient status, climate and management. A review for JNCC by Evans et al. (2011) identified the scarcity of C/GHG research sites in lowland peats as a key evidence gap, which included a complete absence of measurement sites on peat under arable cultivation. The difficulty of quantifying C and GHG emissions for lowland peats is increased by their greater heterogeneity in terms of both typology and management, as well as their fragmented nature across England and Wales. Because of their importance for a wide range of ecosystem services (notably provisioning services, but also cultural services such as access to natural landscapes in otherwise often highly developed regions, and regulating services such as flood control in some areas; Bonn et al., 2010), the role of lowland peats in climate regulation must be weighed against these other ecosystem services to enable appropriate management decisions. On the other hand, ongoing peat oxidation under drainage-based agriculture will ultimately, and inevitably, lead to the exhaustion of the peat, further subsidence (increasing pumping costs and flood risk) and declining agricultural yields, thus consideration needs to be given to the long-term as well as the present-day economic value of lowland peat landscapes. This requires accurate estimates of net C and GHG fluxes as a function of peat type and management, at a range of sites sufficient to support upscaling. Reporting of these fluxes within the UK’s Land Use, Land Use Change and Forestry (LULUCF) emissions inventory, in line with the recent IPCC Wetland Supplement (IPCC, 2014) requires accurate estimation of emissions factors (EFs) for all modified peatlands. 1.1.2. Types and extent of lowland peat in England and Wales
Boulder County Open Space and Mountain Parks initiated thinning treatments at Heil Valley Ranch in 1999 in response to increased wildfire activity in surrounding forests. All stems <15 cm dbh (diameter at breast height) were selectively cut. As these small stems were not merchantable, the managers elected to dispose of the bio- mass using two methods, broadcast-chip and thinning-only. In the broadcast-chip plots, all of the cut stems were mechanically chipped and broadcast onto the forest floor with a 7.5 cm target depth. In the thinning-only plots all stems <15 cm dbh were cut, subsequently removed from the plots, and mechanically chipped into large piles at specific locations on the property. We sampled the three broadcast-chip plots that were thinned in 2002. These broadcast-chip plots had an average size of 27 acres. Thinning-only plots were thinned in 2003 and had an av- erage plot size of 27.5 acres. We randomly selected control plots from the untreated area of the property while still being within 1 - 2 km of the thinning-only and broadcast-chip plots.
The DeNitrification-DeComposition (DNDC) model version 9.5 was used in this study (Li et al., 1992). The DNDC model is a process-based model of carbon (C) and nitrogen (N) biogeochemistry in agricultural ecosystems. The DNDC model framework includes processes for soil, climate, crop production, C and N dynamics, and tracegas emissions reported at a daily time step (Jarecki et al., 2018). The DNDC model was initially developed for quantifying C sequestration and emissions of greenhouse gases (GHG). DNDC is a well-calibrated and validated model for studying carbon and nitrogen cycles in various ecosystems worldwide (Rui et al., 2017) and consists of two components. The first component contains sub-models for soil (bulk density, texture, soil hydraulic parameters, and SOC), climate (air temperature, precipitation, wind speed, solar radiation, and humidity), crop growth (crop type, potential yield, biomass fractions, C/N ratio, water demand, and optimal temperature), agricultural management (tillage, residue, irrigation, plant and harvest dates, and fertiliser) and decomposition (litter, labile humus, passive humus, and microbial biomass). The model converts primary drivers such as climate, soil, vegetation, and human activity into soil environmental factors such as soil temperature, humidity, pH, redox potential and concentration gradients of substrates (Zhang et al., 2018). The second component comprises sub-models for nitrification, denitrification, and fermentation and calculates nitrous oxide (N 2 O) and methane
the grass understory (CROP.100), and a second for the tree component (TREE.100). We used literature values for other ponderosa pine forests as estimates for initial conditions (pool sizes) for biomass and soil carbon, and ran simulations for each site for 2000 years. Between year 1 and 1500, we scheduled regular fires that reflected the fire return intervals at each site (Table 2). The length of these simulation runs has been found to bring other modeled ecosystems into equilibrium . We examined total soil organic matter pools at each site to verify steady state that we defined as having less than a 5% change in total soil organic matter from year to year. Each of the four simulated sites met this criterion.
the same sites 3 years after ﬁre ( Aaltonen et al., 2019b ; Köster et al., 2017 ). These ﬁndings are consistent with the dynamics regarding CO 2 production potential captured in Tas et al. (2014) 7 years after ﬁre.
Assuming that during the ﬁrst few years after ﬁre soil CO 2 emissions correspond mainly to R h , the above ﬁndings suggest that the lack of strong ﬁre eﬀects on deeper previously frozen mineral layers curbs the R s rates in the ﬁrst years after ﬁre. Given the large size of the C reservoir of boreal forests, with the expected increase in ﬁre frequency and the resulting increase in the number of young forest stands, microbial re- covery and ﬁre-induced changes in SOM quality will become a central issue in accurately predicting global change feedbacks. Therefore, in addition to clarifying the contribution of decomposition to soil CO 2 emissions, future research should verify whether R h re ﬂects the patterns described in SOM and microbial biomass throughout the soil proﬁle and estimate what the timeframe of these patterns is. An even more urgent research question is whether these considerations apply under future climatic conditions, in other words, how the combined eﬀects of ﬁre and a warmer climate aﬀect the temperature sensitivity (Q 10 ) of SOM decomposition in di ﬀerent soil layers. Despite the growing body of literature on the Q 10 of soil respiration after boreal ﬁres, ﬁndings are still controversial ( Aaltonen et al., 2019b ). Furthermore, of the three studies that analysed R s responses to warmer and/or drier climate in a post ﬁre environment, only one was undertaken in soils underlain by permafrost ( Song et al., 2018 ). The authors attributed the higher R s observed during warming and drying manipulations to soil nutrient availability and enzymatic activity 7 –8 years after ﬁre. These results contrast with those of Allison et al. (2010) , who suggested that labile C was depleted 7 –9 years after ﬁres in boreal forests not underlain by permafrost. Among the issues emerging from this comparison is the possibility that exposure of previously frozen SOM to a warmer climate will trigger higher C emissions during the early ﬁre succession than in those areas not underlain by permafrost ( Allison and Treseder, 2011 ). However, in the study of Song et al. (2018) , R s after ﬁre was already higher than under the preﬁre conditions prior to the warming experi- ment, which goes against most of the previous published studies ( Köster et al., 2018 ; O'Neill et al., 2003 ; O'Neill et al., 2006 ; Sawamoto et al., 2000 ). Without knowledge of the contribution of each respiration component combined with assessment of the warming and drying ef- fects on both labile and recalcitrant SOM throughout the soil pro ﬁle, we cannot advance on the most relevant feedbacks involving ﬁre and permafrost. Further studies, which take these variables into account, will need to be undertaken.
tural fen areas. Changes in the assumptions for forestry and residual peatland can in some cases convert the national GHG budget from a sink to a source. Clearly, effects in the sensitivity tests exaggerate the uncertainty in the estimates because for many countries considered the data base of areas and land use is better than assumed here. Countries will be somewhere in-between the default and the variation in the sensitiv- ity analyses, depending on drainage status and whether fens or bogs are dominant. The total uncertainty in the GHG budget of Russia and UK is exaggerated because of the large residual, which is likely to be undrained as in the default estimate. Similarly, forests in Finland are likely to be sinks of C as in the default estimate. Russia is the largest GHG emitter and contributes most to overall uncertainty of the European GHG budget.
Small-scale, diverse operations used to occupy the majority of agriculture land which utilized residues and resting pasture for grazing animals (Sulc and Franzluebbers, 2014). Since then, the industrial era has led to the use of large machinery/equipment for labor, decoupling animal husbandry and crop production (Sulc and Tracy, 2007). The integration of crop and livestock production, referred to as integrated crop-livestock system (ICLS) (Nie et al., 2016) has been used in various parts of the world for improving farm productivity. Benefits associated with ICLS include diversity of enterprise, increased nutrient cycling, improved soil structure, and enhanced total production of livestock and crop with minimal inputs (Nie et al., 2016). However, producers seeking to re-integrate animal and crop productions are facing problems such as animal husbandry and regulation knowledge loss, lack of variation in animal genetics, processing infrastructure loss (Hilimire, 2011), as well as lack of soil and environmental assessments of ICLSs. The goal of this study was to evaluate the impacts of ICLS on soil properties and greenhousegas (GHG) emissions from soils.
In A3A, however, soil respiration was never significantly different in compost and control plots despite the absence of standing water. One explanation is that the higher species richness at this site could reduce the impact of OM addition. Several studies have found that vegetation composition impacts GHG fluxes by controlling C input and influencing organic matter quality ( Treat et al., 2015; Turetsky et al., 2014; Bhullar et al., 2014; Inglett et al., 2012; Reddy & DeLaune, 2008; Ding et al., 2003; Brix et al., 2001). Therefore, organic matter
Natural gas emissions factors can vary depending on the energy content of the gas. The Gas delivered to Endicott College was assigned the United States Pipeline Average emissions factor for the calculations. The pipeline average assumes a Higher Heating Value (HHV) between 1025 to 1050 Btu per scf. The CH4 and N2O emissions from the combustion of natural gas, fuel oil, and vehicle fuel are considered De Minimis due to the relatively small amounts emitted. CO 2 is the weakest of the main GHGs in terms of atmospheric effect per unit of gas, but it is