Spatial Heterogeneity and Soil Nitrogen Dynamics in a Burned Black Spruce Forest Stand: Distinct Controls at Different Scales

Smithwick, Erica A. H.; Mack, Michelle C.; Turner, Monica G.; Chapin, F. Stuart; Zhu, Jun; Balser, Teri C.

doi:10.1007/s10533-005-0031-y

Cited by 48 publications

(52 citation statements)

References 58 publications

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“…In general, the relatively low SOM characteristic of lodgepole pine forests in the GYE probably constrains net N mineralization rates. In a burned black spruce (Picea mariana) stand in Alaska, net N mineralization rates were approximately six times higher during the second year postfire than we measured in the Glade and Moran fires (61). Net in situ annual ammonification in the black spruce system was high and positive (39 mg N⅐kg soil Ϫ1 ⅐yr Ϫ1 ), in contrast to our study, and SOM was 18.6% in the black spruce stands, approximately five times greater than in the burned stands we studied.…”

Section: Figcontrasting

confidence: 56%

Inorganic nitrogen availability after severe stand-replacing fire in the Greater Yellowstone ecosystem

Turner

Smithwick

Metzger

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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147

109

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Understanding ecosystem processes as they relate to wildfire and vegetation dynamics is of growing importance as fire frequency and extent increase throughout the western United States. However, the effects of severe, stand-replacing wildfires are poorly understood. We studied inorganic nitrogen pools and mineralization rates after stand-replacing wildfires in the Greater Yellow- Laboratory incubations using 15 N isotope pool dilution revealed that gross production of ammonium was reduced and ammonium consumption greatly exceeded gross production during the initial postfire years. Our results suggest a microbial nitrogen sink for several years after severe, stand-replacing fire, confirming earlier hypotheses about postdisturbance succession and nutrient cycling in cold, fire-dominated coniferous forests. Postfire forests in Yellowstone seem to be highly conservative for nitrogen, and microbial immobilization of ammonium plays a key role during early succession.nitrification ͉ nitrogen mineralization ͉ Rocky Mountains ͉ Pinus contorta ͉ lodgepole pine

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Section: Figcontrasting

confidence: 56%

Inorganic nitrogen availability after severe stand-replacing fire in the Greater Yellowstone ecosystem

Turner

Smithwick

Metzger

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

147

109

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“…Despite the limitation to one meter of the maximum prospectable depth in the NFI protocol is in agreement with recommendations made in previous studies (Berges and Balandier, 2010) , it can can also lead to SWHC under-estimations, the part of the soil prospectable by roots can be more important (Breda et al, 1995). An important source of errors can be due to the influence of local soil conditions, particularly on soil depth or stone content, that can make information collected on the pit not representative of the plot area (Smithwick et al, 2005). These different errors concerning the raw data are difficult to evaluate but are expected to be one of the most important source of uncertainties at the plot scale, probably explaining a part of the important nugget effect found in the semivariogram elaborated for the kriging procedure.…”

Section: Uncertainties Linked To the Initial Soil Informationmentioning

confidence: 99%

Mapping soil water holding capacity over large areas to predict potential production of forest stands

et al. 2011

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Ingrid Seynave. Mapping soil water holding capacity over large areas to predict the potential production of forest stands. Geoderma, Elsevier, 2011, 160, pp.355-366. 10 AbstractEcological studies need environmental descriptors to establish the response of species or communities to ecological conditions. Soil water resource is an important factor but is poorly used by plant ecologists because of the lack of accessible data. We explore whether a large number of plots with basic soil information collected within the framework of forest inventories allows the soil water holding capacity (SWHC) to be mapped with enough accuracy to predict tree species growth over large areas. We first compared the performance of available pedotransfer functions (PTFs) and showed significant differences in the prediction quality of SWHC between the PTFs selected.We also showed that the most efficient class PTFs and continuous PTFs compared had similar performance, but there was a significant reduction in efficiency when they were applied to soils different from those used to calibrate them. With a root mean squared error (RMSE) of 0.046 cm 3 cm -3 (n = 227 horizons), we selected the Al Majou class PTFs to predict the SWHC in the soil horizons described in every plot, thus allowing 84% of SWHC variance to be explained in soils free of stone (n = 63 plots). Then, we estimated the soil water holding capacity by integrating the stone content collected at the soil pit scale (SWHC') and both the stone content at the soil pit scale and rock outcrop at the plot scale (SWHC") for the 100.307 forest plots recorded in France within the framework of forest inventories. The SWHC" values were interpolated by kriging to produce a map with 1 km² cell size, with a wider resolution leading to a decrease in map accuracy. The SWHC" given by the map ranged from 0 to 148 mm for a soil down to 1 m depth. The RMSE between map values and plot estimates was 33.9 mm, the best predictions being recorded for soils developed on marl, clay, and hollow silicate rocks, and in flat areas. Finally, the ability of SWHC' and SWHC" to predict 3 height growth for Fagus sylvatica, Picea abies and Quercus petraea is discussed. We show a much better predictive ability for SWHC" compared to SWHC'. The values of SWHC" extracted from the map were significantly related to tree height growth. They explained 10.7% of the height growth index variance for Fagus sylvatica (n = 866), 14.1% for Quercus petraea (n = 877) and 10.3% for Picea abies (n = 2067). The proportions of variance accounted by SWHC" were close to those recorded with SWHC" values estimated from the plots (11.5, 11.7, and 18.6% for Fagus sylvatica, Quercus petraea and Picea abies, respectively). We conclude that SWHC" can be mapped using basic soil parameters collected from plots, the predictive ability of the map and of data derived from the plot being close. Thus, the map could be used just as well for small areas as for large areas, directly or indirectly through water balance indices, to predict forest growth an...

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“…We assumed the between-plot spacing of roughly 10 m to produce spatially independent data as the autocorrelation distances for soil and understory vegetation parameters in boreal forests are generally found to be below 10 m (Liski 1995;Smithwick et al 2005;Lavoie and Mack 2012). Thus, here by the term "spatial variability" we mean the variability related to sample locations in a non-autocorrelated dataset.…”

Section: Samplingmentioning

confidence: 99%

Variability and patterns in forest soil and vegetation characteristics after prescribed burning in clear-cuts and restoration burnings

Čugunovs¹,

Tuittila²,

Mehtätalo³

et al. 2017

Silva Fenn.

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Highlights• Soil parameter variability is similar across sites of different disturbance type.• Variability of understory vegetation biomass and cover is higher and more different between sites than soil variability.• Sites studied here reflect well the assumed disturbance-type gradient based on PCA.• Sampling six forest sites per treatment should provide good statistical power to capture the differences in soil organic matter stocks. AbstractForest ecological restoration by burning is widely applied to promote natural, early-successional sites and increase landscape biodiversity. Burning is also used as a forest management practice to facilitate forest regeneration after clearcutting. Besides the desired goals, restoration burnings also affect soil biogeochemistry, particularly soil organic matter (SOM) and related soil carbon stocks but the long-term effects are poorly understood. However, in order to study these effects, a reliable estimate of spatial variability is first needed for effective sampling. Here we investigate spatial variability of SOM and vegetation features 13 years after burnings and in combination with variable harvest levels. We sampled four experimental sites representing distinct management and restoration treatments with an undisturbed control. While variability of vegetation cover and biomass was generally higher in disturbed sites, soil parameter variability was not different between the four sites. The joint ecological patterns of soil and vegetation parameters across the whole sample continuum support well the prior assumptions on the characteristic disturbance conditions within each of the study sites. We designed and employed statistical simulations as a means to plan prospective sampling. Sampling six forest sites for each treatment type with 30 independent soil cores per site would provide enough statistical power to adequately capture the impacts of burning on SOM based on the data we obtained here and statistical simulations. In conclusion, we argue that an informed design-based approach to documenting the ecosystem effects of forest burnings is worth applying both through obtaining new data and meta-analysing the existing.

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Spatial Heterogeneity and Soil Nitrogen Dynamics in a Burned Black Spruce Forest Stand: Distinct Controls at Different Scales

Cited by 48 publications

References 58 publications

Inorganic nitrogen availability after severe stand-replacing fire in the Greater Yellowstone ecosystem

Inorganic nitrogen availability after severe stand-replacing fire in the Greater Yellowstone ecosystem

Mapping soil water holding capacity over large areas to predict potential production of forest stands

Variability and patterns in forest soil and vegetation characteristics after prescribed burning in clear-cuts and restoration burnings

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