Factors causing temporal and spatial variation in heterotrophic and rhizospheric components of soil respiration in afforested organic soil croplands in Finland

Partitioning soil respiration (SR) into its components, heterotrophic and rhizospheric respiration, is an important step for understanding and modelling carbon (C) cycling in organic soils. However, no partitioning studies on afforested organic soil croplands exist. We separated soil respiration originating from the decomposition of peat (SR_P), and aboveground litter (SR_L) and root respiration (SR_R) in six afforested organic soil croplands in Finland with varying tree species and stand ages using the trenching method. Across the sites temporal variation in SR was primarily related to changes in soil surface temperature (?5 cm), which explained 71–96% of variation in SR rates. Decomposition of peat and litter was not related to changes in water table level, whereas a minor increase in root respiration was observed with the increase in water table depth. Temperature sensitivity of SR varied between the different respiration components: SR_P was less sensitive to changes in soil surface temperature than SR_L or SR_R. Factors explaining spatial variation in SR differed between different respiration components. Annual SR_P correlated positively with peat ash content while that of SR_L was found to correlate positively with the amount of litter on the forest floor, separately for each tree species. Root respiration correlated positively with the biomass of ground vegetation. From the total soil respiration peat decomposition comprised a major share of 42%; the proportion of autotrophic respiration being 41% and aboveground litter 17%. Afforestation lowered peat decomposition rates. Nevertheless the effect of agricultural history can be seen in peat properties for decades and due to high peat decomposition rates these soils still loose carbon to the atmosphere.     

Indirect regulation of heterotrophic peat soil respiration by water level via microbial community structure and temperature sensitivity

Northern peatlands contain a considerable share of the terrestrial carbon (C) pool, which climate change will likely affect in the future. The magnitude of this effect, however, remains uncertain, due mainly to difficulties in predicting decomposition rates in the old peat layers. We studied the effects of water level depth (WL) and soil temperature on heterotrophic soil respiration originating from peat decomposition (R_PD) in six drained peatlands using a chamber technique. The microbial community structure was determined through PLFA. Within the studied sites, temperature appeared to be the main driver of R_PD. However, our results indicate that there exist mechanisms related to lower WL conditions that can tone down the effect of temperature on R_PD. These mechanisms were described with a mathematical model that included the optimum WL response of R_PD and the effect of average WL conditions on the temperature sensitivity of R_PD. The following implications were apparent from the model parameterisation: (1) The instantaneous effect of WL on R_PD followed a Gaussian form; the optimum WL for R_PD was 61 cm. The tolerance of R_PD to the WL, however, was rather broad, indicating that the overall effect of WL was relatively weak. (2) The temperature sensitivity of R_PD depended on the average WL of the plot: plots with a high average WL showed higher temperature sensitivity than did those under drier conditions. This variation in temperature sensitivity of R_PD correlated with microbial community structure. Thus, moisture stress in the surface peat layer or, alternatively, the lowered temperature sensitivity of R_PD in low water level conditions via microbial community structure and biomass may restrict R_PD. We conclude that a warmer future climate may raise R_PD in drained peatlands only if the subsequent decrease in the moisture of the surface peat layers is minor and, thus, conditions remain favourable for decomposition.     

Induced Spawning of Wild American Shad Alosa sapidissima Using Sustained Administration of Gonadotropin-Releasing Hormone Analog (GnRHa)

American shad Alosa supidissima broodstock were collected from the Susquehanna River during their spawning migration. Mean volume of expressible milt (± standard deviation) was 2.5 (±1.7) mL/kg body weight; mean spermatozoid count was 66.2 ± 10⁹ (±163 ± 10⁹) spermntozoa/mL; and duration of 50% motility was 36.5 (±10.3) see. Ovarian biopsies indicated the presence of oocytes of various sizes (200–2,000 μm in diameter) and stages of development. Fish were implanted with a delivery system loaded with gonadotropin-releasing hormone analog (GnRHa) and started spawning 2 d after treatment. Fertile eggs were collected daily for the next 9 d, for a total of 50,100 eggs/kg body weight with a mean fertilization success of 62%. Upon cessation of spawning, the ovaries of all females still contained large numbers of oocytes at various stages of development, as at the beginning of the experiment, but with a greater number of atretic oacytes. Our observations show that American shad have an asynchronous ovarian development, and treatment with a GnRHa delivery system is effective in inducing several successive spawns of fertile eggs.     

Airborne small-footprint discrete-return LiDAR data in the assessment of boreal mire surface patterns, vegetation, and habitats

Boreal mires encompass high diversity in species and habitats, many of which are endangered. In Finland, extensive use of peatlands has resulted in habitat fragmentation. A need for accurate and cost-efficient vegetation mapping and monitoring of habitat changes exists in mire conservation, restoration and peatland forestry. LiDAR is an emerging and excellent tool for probing the geometry of vegetation and terrain. Modern systems measure the backscattered signal accurately and also provide radiometric information. Experiments were carried out in a complex minerotrophic–ombrotrophic eccentric raised bog in southern Finland (61°47′N, 24.18′E). First, we tested discrete-return LiDAR for the modeling of mire surface patterns and the detection of hummocks and hollows, as well as the effect of mire plants on the Z accuracy of the surface echoes. Secondly, the response of different mire vegetation samples in LiDAR intensity was examined. Thirdly, we tested area-based geometric and radiometric features in supervised classification of mire habitats to discover the meaningful variables. The vertical accuracy of LiDAR in mire surface modeling was high: 0.05–0.10 m. A binary hummock-hollow model that was estimated from a LiDAR-based elevation model matched flawlessly in aerial images and had moderate explanatory power in habitat classification trials. The intensity of LiDAR in open-mire vegetation was mainly influenced by the surface moisture, and separation of vegetation classes spanning from ombrotrophic to mesotrophic vegetation proved to be difficult. Area-based features that characterize the height distribution of LiDAR points in the canopy were the strongest explanatory variables in the classification of 21 diverse mire site types. Actual qualifying differences in the ground flora were unattainable in the LiDAR data, which resulted in inferior accuracy in the characterization of ecohydrological conditions and nutrient level of open mires and sparsely forested wet sites. Mire habitat classification accuracy with LiDAR surpassed earlier results with optical data. The results suggested that LiDAR constitutes an efficient aid for monitoring applications. We propose the co-use of images and LiDAR for enhanced mapping of open mires and tree species. In situ calibration and validation procedures are required until invariant geometric and radiometric features are discovered.     

Soil–atmosphere CO2, CH4 and N2O fluxes in boreal forestry-drained peatlands

Greenhouse gas emissions from managed peatlands are annually reported to the UNFCCC. For the estimation of greenhouse gas (GHG) balances on a country-wide basis, it is necessary to know how soil–atmosphere fluxes are associated with variables that are available for spatial upscaling. We measured momentary soil–atmosphere CO₂ (heterotrophic and total soil respiration), CH₄ and N₂O fluxes at 68 forestry-drained peatland sites in Finland over two growing seasons. We estimated annual CO₂ effluxes for the sites using site-specific temperature regressions and simulations in half-hourly time steps. Annual CH₄ and N₂O fluxes were interpolated from the measurements. We then tested how well climate and site variables derived from forest inventory results and weather statistics could be used to explain between-site variation in the annual fluxes. The estimated annual CO₂ effluxes ranged from 1165 to 4437 g m⁻² year⁻¹ (total soil respiration) and from 534 to 2455 g m⁻² year⁻¹ (heterotrophic soil respiration). Means of 95% confidence intervals were ±12% of total and ±22% of heterotrophic soil respiration. Estimated annual CO₂ efflux was strongly correlated with soil respiration at the reference temperature (10 °C) and with summer mean air temperature. Temperature sensitivity had little effect on the estimated annual fluxes. Models with tree stand stem volume, site type and summer mean air temperature as independent variables explained 56% of total and 57% of heterotrophic annual CO₂ effluxes. Adding summer mean water table depth to the models raised the explanatory power to 66% and 64% respectively. Most of the sites were small CH₄ sinks and N₂O sources. The interpolated annual CH₄ flux (range: −0.97 to 12.50 g m⁻² year⁻¹) was best explained by summer mean water table depth (r² = 64%) and rather weakly by tree stand stem volume (r² = 22%) and mire vegetation cover (r² = 15%). N₂O flux (range: −0.03 to 0.92 g m⁻² year⁻¹) was best explained by peat CN ratio (r² = 35%). Site type explained 13% of annual N₂O flux. We suggest that water table depth should be measured in national land-use inventories for improving the estimation of country-level GHG fluxes for peatlands.