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170 results for “forest litter”
Autumnal Litter Input in DIRT Litter Manipulation Experiment at Harvard Forest 2008
Climate change will alter forest ecosystem productivity, changing the quantity and quality of detrital inputs to soil and altering rates of soil organic matter (SOM) accumulation and stabilization. To examine changes in forest soil SOM pools, we have used the Detritus Input and Removal Treatments (DIRT) Project to alter organic matter input rates and sources (roots, leaves) to soils, allowing us to measure contributions of organic matter sources to long-term SOM storage at five temperate forests (Harvard Forest, HJ Andrews, Bousson (PA) Experimental Forest (BEF), U. Michigan Biological Station (UMBS), Síkfokut ILTER, Hungary). Organic matter inputs are altered by excluding or adding leaf inputs, or by excluding roots from forested plots. Soil respiration partitioning at HF, BEF, and UMBS shows that soil fertility controls the allocation of C to above- and belowground tissue. At UMBS, glacial outwash sandy soils are extremely low in N, and C released from root respiration plus root litter decomposition is 87% of total soil respiration. Conversely, at the N-rich BEF site, total belowground sources of CO2 are only 61% of soil respiration, with 47% attributed to root litter. These data suggest that at BEF, leaf litter, comprising only 39% of soil respiration, would be a more important source of long-term SOM than root litter. However, soil chemistry and radiocarbon data have shown us that long-term soil C storage is complex. The year 2010 represents the 20-year anniversary of the initiation of DIRT treatments at the Harvard Forest (2010), and we are therefore planning to conduct systematic sampling campaigns for a comprehensive study of changes in SOM quality after long-term manipulation of inputs. One objective is to quantify how 20 years of litter input alterations have affected SOM quantity and quality at the surface (0-20 cm) and deeper in the soil profile (20-100 cm). To uderstand these changes, we need to quantify the quantity and quality of aboveground litter inp
Litter Decomposition in Response to Nitrogen Addition and Soil Warming at Harvard Forest 2010-2012
The purpose of this study is to examine whether two environmental change stressors (warming and nitrogen deposition) differentially impact litter decomposition. We investigated this using a two year litterbag decomposition experiment at the chronic N amendment experiment and the Barre Woods Soil warming experiment, and measured litter decay dynamics, enzyme activities and litter chemistry. In both years mass loss of the mixed litter was suppressed under N addition, with most of the mass loss observed in the first year compared to the second year (70% and 30% of total mass loss, respectively). Both years showed either increased activity for some hydrolytic enzymes (e.g. cellobiohydrolase) or no difference (e.g. ß-N-acetylglucosaminidase) with increased N. The lignolytic enzymes (e.g. peroxidases) showed no difference in activity in the first year, but had a highly reduced activity in year 2 under elevated N conditions. Soil warming did not significantly affect litter mass loss, and only had an effect on the activity of a few enzymes. In the oak reciprocal litterbag study, decay of oak litter originating from the highest N addition plot was negatively affected by simulated N deposition in the first year of decomposition, while after two years, simulated N deposition negatively affected all litter, and litter originating from the highest N addition plot decayed more slowly than control litter even without added N (i.e. in the control plot). In addition, in the first year of decomposition lignolytic enzyme activities were suppressed in litter originating from the N addition treatments, but due to simulated N deposition in year two.
DIRT Litter Manipulation Experiment at Harvard Forest since 1990
The DIRT Experiment (Detritus Input and Removal Treatments) is a long-term study of controls on soil organic matter formation. Our goal is to assess how rates and sources of plant litter inputs control the accumulation and dynamics of organic matter and nutrients in forest soils over decadal time scales. Results from 11 years of field and laboratory studies demonstrate the relative importance of above- and belowground sources on soil organic matter (SOM) dynamics and show emerging long-term non-linear changes in soil carbon release and storage. Treatments established in a mixed hardwood stand in 1990 are: doubling annual aboveground litter (DL), exclusion of aboveground litter (NL), exclusion of root inputs by trenching (NR), and exclusion of aboveground litter and root inputs (NI), on replicated 3m x 3m plots (n=3 for treatments, 6 for controls). The O/A-less treatment, implemented in 1991, tracks the recovery of impoverished soil by replacing O and A horizon soil with B horizon material and allowing normal litter inputs thereafter. Comparison of data among treatments (soil respiration, soil solution chemistry, soil physical and chemical properties, and microfaunal and microbial community structure) allows us to determine the contributions of live roots, above-ground litter, and belowground detritus to SOM and nutrient dynamics in this forest soil. Similar experiments in Pennsylvania, Wisconsin, Oregon, and Hungarian forests provide information on these processes across climate and soil texture gradients. First-year soil respiration results from the Harvard Forest DIRT plots showed that live root respiration, production of aboveground litter (leaf, twig, other fine litter) and fine root detritus each constitute about one-third of C inputs to soil. Soil respiration is influenced more by root inputs than aboveground litter in this forest. CO2 efflux from root-excluded soils (NR, NI) declined to 32% of controls over the first 11 years of treatments as soil C became mo
Leaf Litter Moisture Content at Harvard Forest HEM and LPH Towers 2006
Leaf litter was collected at the time of soil respiration measurements and its moisture content was measured in order to determine the contribution of leaf litter decomposition to measurements of total soil respiration including the litter layer. Leaf litter moisture has been shown to strongly affect CO2 release from organic soil layers (Borken et al. 2003).
Effects of ectomycorrhizal fungi on pine litter decomposition in temperate pine forests in California, Florida, and Minnesota
This experiment is designed to assess the generality of the effect of ECM fungi on leaf litter decomposition in temperate pine forests. To assess ECM fungal effects on decomposition, we established and ECM fungal knockdown experiment (via trenching) in nine temperate pine forests in California, Florida, and Minnesota. In litter bags incubated (July 2021-July 2022) in paired trenched and untrenched plots at each site we compared leaf litter decomposition (of native pine litter and a common Pinus strobus litter), fungal community composition (via high throughput sequencing), fungal abundance (via qPCR), decomposition enzyme expression, and soil nutrient availability. Contrary to widely cited theory and other results from a subset of our field sites, we found that ECM fungi either increased or did not impact pine litter decomposition in temperate pine forests.
Hubbard Brook Experimental Forest: Litter and soil radiocarbon and selective metal measurements from Bear Brook, 1998–2023
Radiocarbon time series of archived litter and soil samples from Bear Brook (west of watershed 6) at lower elevation from 1998 to 2023. Additional measurements include total carbon and nitrogen for all samples, and selective dissolution metal concentrations for the Oa/A and mineral soil layers. Selective dissolution metals include pyrophosphate-extractable aluminum (Al); iron (Fe), calcium (Ca), magnesium (Mg), and manganese (Mn); oxalate-extractable Al, Fe, Ca, Mg, and Mn; and dithionite-extractable Al, Fe, Ca, Mg, and Mn. All samples are from the Microbial Biomass and Activity Sampling Effort (Groffman and Martel, 2025, https://doi.org/10.6073/pasta/aff4a2074fd56102f62f13a19ce46f2d). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the US Forest Service, Northern Research Station.
Forest Transition Experiment - Leaf Litter in a Coastal Virginia Forest
Leaf litter collected in basket-based litter traps in forest transition plots
Data for a leaf litter decomposition study and soil density fractionation analysis at a whole-watershed fertilization experiment in a temperate forest
To assess how elevated N deposition influences leaf litter decomposition dynamics and soil organic matter formation in a temperate deciduous forest, we coupled a reciprocal transplant leaf litter decomposition study with an analysis of the distribution of soil organic matter in mineral associated and particulate organic matter fractions at a long-term, whole-watershed, N fertilization experiment. We found that nearly 30 years of N additions slowed decay rates by about 11% for leaf litter decomposed in the fertilized watershed, regardless of the watershed from which the initial litter was collected. An apparent consequence of the altered rates of decomposition was that the soil in the fertilized watershed had about a 40% greater fraction of SOM in light particulate organic matter compared to the reference watershed, which was positively correlated with the bulk soil carbon to nitrogen ratio. Collectively, our results suggest that under conditions of N saturation, the physical transfer pathway of SOM formation is favored, which can have important implications for the future of the soil organic matter stock and nutrient cycling.
Short-term disappearance of foliar litter of three tree species native to rain forest of Puerto Rico
Litter disappearance was examined before (1989) and after (1990) Hurricane Hugo in the Luquillo Experimental Forest, Puerto Rico using mesh litterbags containing abscised Cyrilla racemiflora or Dacryodes excelsa leaves or fresh Prestoea montana leaves. Biomass and nitrogen dynamics were compared among: i) species; ii) mid- and high-elevation forest types; iii) riparian and upland sites; and iv) among pre- and post-hurricane disturbed environments. Biomass disappearance was compared using multiple regression and negative exponential models in which the slopes were estimates of the decomposition rates subsequent to apparent leaching losses and the y-intercepts were indices of initial mass losses (leaching). C. racemiflora leaves with low nitrogen (0.39 %) and high lignin (22.1 %) content decayed at a low rate and immobilized available nitrogen. D. excelsa leaves had moderate nitrogen (0.67 %) and lignin (16.6 %) content, decayed at moderate rates, and maintained the initial nitrogen mass. P. montana foliage had high nitrogen (1.76 %) and moderate lignin (16.7 %) content and rapidly lost both mass and nitrogen. There were not significant differences in litter disappearance and nitrogen dynamics among forest types and slope positions. Initial mass loss of C. racemiflora leaves was lower in 1990 but the subsequent decomposition rate did not change. Initial mass losses and the overall decomposition rates were lower in 1990 than in 1989 for D. excelsa. D. excelsa and C. racemiflora litter immobilized nitrogen in 1990 but released 10-15% of their initial N in 1989, whereas P. montana released nitrogen in both years (25-40 %). Observed differences in litter disappearance rates between years may have been due to differences in the timing of precipitation. Foliar litter inputs during post-hurricane recovery of vegetation in Puerto Rico may serve to immobilize and conserve site nitrogen. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-00
Litter decomposition of the tabonuco forest before hurricane Hugo
We examined forest structure, tree species composition, litterfall rate, and leaf litter decomposition in a mid-successional forest (MSF) and an adjacent mature tabonuco forest (MTF) in the Luquillo Experimental Forest of Puerto Rico. Whereas the MTF site received limited human disturbance, the MSF site had been cleared for timber production by the beginning of this century and was abandoned after hurricanes struck the Luquillo Mountains in the 1920s and 1930s. We found that the MSF was dominated by successional tree species 50 yrs after secondary succession, and did not differ in tree basal area and litterfall rate from the MTF. Leaf decomposition rate in the MSF was higher than in the MTF, but this difference was small. Our results show that deforestation has long-term (>50 years) influence on tree species composition and that leaf decomposition processes in secondary forest is relatively faster than recovery of tree species composition. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Soil carbon stock, litter decomposition, and weather data from Ethiopian forests
<p><strong>Introduction</strong></p> <p>100 sampling units (SU) were selected from the total of 631 SUs of the Forest Reference Level submission 2017 (FRL 2017). The sampling was designed unbiased for total growing stock per SU, altitude,and mean litter depth per SU. The actual field sampling succeeded on 98 of the pre-selected SUs due to accessibility restrictions.</p> <p><strong>Soil profile sampling</strong></p> <p>Soil sampling was performed from November 2017 till mid-January 2018. Samples were taken from undisturbed soil from depths of 0-10 cm, 10-20 cm, and 20-30 cm below the organic layer. Volumetric samples of 107.5 cm<sup>3</sup> were taken vertically, using a 10 cm long conically shaped corer with a cutting lower edge diameter of 37 mm and upper diameter of 40 mm. </p> <p>Composite samples were formed by combining the volumetric samples taken from different depths of two parallel soil profiles. The samples were transported to EEFRI Soil Laboratory in Addis Ababa after 1-4 weeks of sampling at distant locations. </p> <p> </p> <p><strong>Soil physical characteristics</strong></p> <p>The soil samples were air-dried, homogenized, and subjected to oven-drying at 105°C until constant mass. Total bulk density was determined using the total dry mass and volume of the composite samples. </p> <p>Organic carbon content (C % by wet oxidation method), and soil physical characteristics: moisture content, bulk density of the total sample, and bulk density of fine fraction (particles passing the 2 mm sieve). The mass of the coarse fraction was weighed. The soil fine fraction was also subjected to laser diffraction for more accurate particle size analysis for proportions of clay, silt, and sand. </p> <p> </p> <p>In addition to this 28 samples were also analyzed for C content in the laboratory of Natural Resources Institute Finland to determine C content by LECO CHN analyzer. This was done to calibrate the bulk of wet digestion-based estimates (Fig. 1). Before analysis, the soils were tested for the presence of inorganic C.</p> <p> </p> <p>For Figure 1. See Soil_C_Ethiopia.pdf</p> <p><strong>Figure 1</strong>. Comparison of results from wet oxidation (Walkley-Black) and dry oxidation (CHN analyzer). The dotted line shows the theoretical 1:1 match between the axis, the solid line shows linear regression (intercept = 0) between the methods. The estimated slope value of 1.165 was used in adjusting the wet digestion results to match those obtained by dry oxidation: OC<sub>adj</sub> = 1.165 * OC<sub>wet</sub>.</p> <p>Based on a linear regression between the wet and dry oxidation analysis results, a correction factor of 1.165 was applied to adjust the organic C% obtained by wet digestion. The adjusted data are shown in the file “SOC_Ethiopia_2017-2018.csv”.</p> <p> </p> <p>SOC stocks were calculated by multiplying the proportion of organic C with BD of fine earth, after which the result was corrected for stoniness, a visually estimated proportion of large stones (S, value from 0 to 1) in the soil profile that could not be included in the volumetric soil samples (FAO VS-FAST).</p> <p><span class="math-tex">\(SOCstock = C_{org} * BD_{fe} * (1-S)\)</span></p> <p><strong>Soil organic carbon stock data</strong></p> <p><strong>Files: “SOC_Ethiopia_2017-2018.csv” and “SOC_Ethiopia_2017-2018.xlsx”</strong></p> <p>The file includes soil characteristics from layers of 0-10 cm, 10-20 cm, and 20-30 cm below the loose organic layer on top of the soil. The data are used for SOC stock estimation in the respective layers as described above.</p> <p>In the .csv file individual columns are for </p> <p><strong>LAT</strong> is the latitude of the sampling site corresponding to <strong>FieldCode</strong> and <strong>SU_nr</strong></p> <p><strong>LON</strong> is the longitude of the sampling site corresponding to <strong>FieldCode</strong> and <strong>SU_nr</strong></p> <ul> <li>The coordinates are expressed as decimal degrees of the WGS84 system</li> </ul> <p><strong>FieldCode </strong>refers to the Region and Sampling Unit number of the Ethiopian NFI (see below) </p> <p><strong>SU_nr </strong>is the Sampling Unit number of the Ethiopian NFI</p> <p><strong>Region </strong>is the name of the administrative region where the sample was taken</p> <p><strong>Biome </strong>is the name of the forest biome type where the sample was collected</p> <p><strong>BiomeSimplified </strong>is the name of a biome with some close types combined</p> <p><strong>DepthRange </strong>is the upper and lower limit of the soil sample in the field, cm</p> <p><strong>StoninessVFAST </strong>is a percentage of stones (VS-FAST by FAO) in the ca. 40 cm deep soil profile exposed during the sampling</p> <p><strong>FreshMassInField </strong>is the mass of the total composite soil sample of the given layer, g, primarily indicative of checking the correct number of subsamples in composite</p> <p><strong>NrComposites </strong>is the number of subsamples included in the composite for each soil layer</p> <p><strong>CorerVolume </strong>is a constant of 107.5 cm<sup>3</sup> because only one type of corer was used for undisturbed, volumetric sampling</p> <p><strong>CompositeVolume </strong>is the volume of the composite sample for each soil depth layer</p> <p><strong>CoarseFractionMass </strong>is the dry mass, g of soil particles > 2mm that did not pass the sieve, but were included in the sample volume</p> <p><strong>FE_DryMass </strong>is oven-dry mass, g of the fine fraction that passed the 2 mm sieve.</p> <p><strong>BDtot </strong>is total bulk density, g m<sup>-3</sup>, calculated for the composite sample</p> <p><strong>BDfe </strong>is the bulk density of the fine earth fraction, g m<sup>-3</sup></p> <p><strong>OC_adj</strong> is organic carbon (OC) content (%) in the composite sample, adjusted according to the comparison between dry and wet oxidation methods (Fig. 1)</p> <p><strong>SOCfe </strong>is SOC stock calculated for soil fine earth fraction, t ha<sup>-1</sup> in the 10 cm deep soil layer</p> <p><strong>SOCfe_stoniness</strong> is SOC stock of the fine earth fraction, t ha<sup>-1</sup> in the 10 cm deep soil layer, adjusted for stoniness. The correction assumes that the volume occupied by larger stones would be void of OC. </p> <p> </p> <p><strong>Litter stock data</strong></p> <p><strong>File: “Litter_Ethiopia_2017-2018.csv”</strong></p> <p>The file includes measurements of litter layer on Ethiopian NFI Sampling Unit (SU) sites where sampling for SOC stock determination was done. The depth of the litter layer was measured in the SU’s of the NFI, and this data contains in addition to depth also a volumetric sample of the litter layer. The dry bulk density was used to calculate the carbon stocks in the litter pool.</p> <p> </p> <p>The depth of the litter layer was measured in the field. Litter from the respective spot was sampled quantitatively from a frame of 0.01m<sup>2</sup> of area for litter dry mass estimate.</p> <p>The organic C stock in a litter (L) was calculated as,</p> <p> </p> <p><span class="math-tex">\(L = {M\over z} * {C_{om}\over A}, \)</span></p> <p> </p> <p>where</p> <p><em>M</em> = Dry mass of the litter sample, g</p> <p><em>z</em> = Depth of the litter layer in the field, m</p> <p><em>C<sub>om</sub></em> = Conversion factor from dry organic matter to carbon (C), 0.5</p> <p><em>A</em> = area of quantitative collection of litter (0.01 m<sup>2</sup>)</p> <p> </p> <p>In the .csv file individual columns are for</p> <p><strong>LAT, LON</strong> is the GPS coordinates (decimal degrees of WGS84) for the Sampling Units (<strong>SU_ID</strong>)</p> <p><strong>SU_ID</strong> is the Sampling Unit identification number of the Ethiopian NFI</p> <p><strong>FieldCode </strong>refers to the Region and Sampling Unit number of the Ethiopian NFI (see below)</p> <p><strong>Region </strong>is the name of the administrative region where the sample was taken</p> <p><strong>Litter_dry</strong> is the dry mass, g of the litter sample</p> <p><strong>Area_m2</strong> is the area, m<sup>2</sup> of litter sampling</p> <p><strong>MeanLitterDepth </strong>is the mean depth of the litter layer at the sampling area</p> <p><strong>CDensityLitter </strong>is the dry bulk density of the litter, g m<sup>-2</sup> multiplied by the assumed organic C proportion of the oven-dry litter materials (0.50)</p> <p><strong>LitterCStock_tha</strong> is the litter stock, t ha<sup>-1</sup> calculated from the C density of the litter layer</p> <p> </p> <p><strong>Litter bag data (decomposition and quality)</strong></p> <p>The leaves and twigs were sampled from 2 species (Juniperus and Podocarpus) and 3 locations of the elevation gradient in the Chilimo forest (Table 1). The forest was considered an old-growth with <em>Juniperus procera</em> and <em>Podocarpus falcatus</em>being the main species forming the tree canopy. The sites form an elevation gradient (Table 1).</p> <p> </p> <p>Table 1. Geographical locations of the study sites in the Chilimo forest.</p> <p> </p> <table> <tbody> <tr> <td> <p>id</p> </td> <td> <p>Latitude (deg.)</p> </td> <td> <p>Longitude (deg.)</p> </td> <td> <p>Elevation</p> <p>(m a.s.l)</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>9.0672</p> </td> <td> <p>38.1443</p> </td> <td> <p>2500</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>9.0712</p> </td> <td> <p>38.1556</p> </td> <td> <p>2670</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>9.0869</p> </td> <td> <p>38.1684</p> </td> <td> <p>2800</p> </td> </tr> </tbody> </table> <p> </p> <p>The dying and dead leaves were sampled directly from the trees later referred to as “fresh” and from the branches found on the ground, referred to as “old”. The old leaves were assumed to be dead for around 3 months. The diameter of the branches/twigs was less than 1 cm in diameter. The samples were first sorted and air-dried in an elevated temperature of the greenhouse and thereafter oven-dried in the oven overnight at 45 °C. The samples were analyzed for acid, water, ethanol dissolved,and undissolved fractions (AWEN) (Table 2) and for the decomposition rates of the litter installed into the litter bags corresponding to each of the Chilimo sites. </p> <p> </p> <p>Table 2. Acid, water, ethanol (A, W, E, respectively) dissolved and undissolved fractions (N) from the litter components of the dominant tree species in the Chilimo forest.</p> <table> <tbody> <tr> <td> <p>Litter type</p> </td> <td> <p>Species</p> </td> <td> <p>A</p> </td> <td> <p>W</p> </td> <td> <p>E</p> </td> <td> <p>N</p> </td> </tr> <tr> <td> <p>leaves fresh</p> </td> <td> <p><em>Juniperus </em></p> </td> <td> <p>0.45</p> </td> <td> <p>0.13</p> </td> <td> <p>0.1</p> </td> <td> <p>0.33</p> </td> </tr> <tr> <td> <p>leaves fresh</p> </td> <td> <p><em>Podocarpus </em></p> </td> <td> <p>0.42</p> </td> <td> <p>0.28</p> </td> <td> <p>0.05</p> </td> <td> <p>0.25</p> </td> </tr> <tr> <td> <p>leaves old</p> </td> <td> <p><em>Juniperus </em></p> </td> <td> <p>0.44</p> </td> <td> <p>0.07</p> </td> <td> <p>0.08</p> </td> <td> <p>0.41</p> </td> </tr> <tr> <td> <p>leaves old</p> </td> <td> <p><em>Podocarpus </em></p> </td> <td> <p>0.44</p> </td> <td> <p>0.09</p> </td> <td> <p>0.05</p> </td> <td> <p>0.42</p> </td> </tr> <tr> <td> <p>twigs</p> </td> <td> <p><em>Juniperus </em></p> </td> <td> <p>0.61</p> </td> <td> <p>0.04</p> </td> <td> <p>0.02</p> </td> <td> <p>0.32</p> </td> </tr> <tr> <td> <p>twigs</p> </td> <td> <p><em>Podocarpus </em></p> </td> <td> <p>0.56</p> </td> <td> <p>0.15</p> </td> <td> <p>0.02</p> </td> <td> <p>0.27</p> </td> </tr> </tbody> </table> <p> </p> <p>A sufficient amount of litter was placed into the litter bags (polyurethane mesh 1 mm) and the mesh bags were installed on top of the soil surface under the forest canopy (later referred to as “canopy”) and in the forest gap caused by harvesting (later referred as “open”). The installation of the litter bags (for each species 3 replicates of each litter type for each site and canopy type for the 3 periods, in total 12 litter bags for leaves and 6 bags for twigs) was done on 22.9.2017. The mesh bags were left on the ground, protected from grazing by the fence, and retrieved subsequently on 12.10.2017, 31.10.2017, and 12.12.2017. Despite the efforts took few samples were lost. The retrieved samples were oven-dried and initial mass and mass loss data for each period and litter type with a detailed description of the variables can be found in the file “litter.chilimo_07.02.22.xlsx”.</p> <p> </p> <p><strong>Soil temperature data</strong></p> <p>During the period from 22.9.2017 to 12.12.2017, we monitored the soil temperature at 5 cm depth under the canopy and in the open canopy on all Chilimo sites continuously every 4 hours intervals with the Maxim iButton temperature loggers. However, some sensors were lost. Daily means and their standard deviation of the continuous temperatures can be found in the file “soil.temp.chilimo_07.02.22.xlsx”.</p> <p> </p> <p><strong>Processed weather data</strong></p> <p>The air temperature and precipitation data for 98 sampling units corresponding to soil carbon data originated from 73 weather stations located across Ethiopia and were obtained from Ethiopian Meteorological Agency (http://www.ethiomet.gov.et/). Sampling units were joined with weather data by the closest proximity to their corresponding weather stations. Precipitation was unaltered. The air temperature required correction by elevation is described in more detail in Lehtonen et al. (2020). The monthly values of air temperature and precipitation with an accompanied readme description of the variables can be found for 98 sampling units in the file “sampling.units98_meteo_07.02.22.xlsx” and the Chilimo study sites in the file “monthly.weather.chilimo_07.02.22.xlsx”. The monthly values in the file "sampling.units98_meteo_07.02.22.xlsx" correspond to long-term average over the period from 1986 to 2017.</p> <p> </p> <p> </p> <p><strong>References:</strong></p> <p> </p> <p>Lehtonen, A., Ťupek, B., Nieminen, T.M., Balázs, A., Anjulo, A., Teshome, M., Tiruneh, Y. and Alm, J., 2020. Soil carbon stocks in Ethiopian forests and estimations of their future development under different forest use scenarios. <em>Land Degradation & Development</em>, <em>31</em>(18), pp.2763-2774.</p> <p> </p> <p>FRL 2017. https://redd.unfccc.int/files/ethiopia_frel_3.2_final_modified_submission.pdf</p>
Mass of forest floor litter from cores in reference stands and inventory plots in the Pacific Northwest, 1992 to 2003
These data provide an inventory of the mass of forest floor organic matter stored within various forest types. This data is used to determine total organic matter, carbon, and nutrient stores in forests.
Fig. 5 in Camerobiid mites (Acariformes: Raphignathina: Camerobiidae) inhabiting epiphytic bromeliads and soil litter of tropical dry forest with analysis of setal homology in the genus Neophyllobius
Fig. 5. Neophyllobius tepoztlanensis sp. nov., ♀, holotype. A. Palp. B. Subcapitulum. C. Dorsal idiosoma. D. Ventral idiosoma. E. Trochanter–tibia of leg I. F. Tarsus I.
Fig. 4 in Camerobiid mites (Acariformes: Raphignathina: Camerobiidae) inhabiting epiphytic bromeliads and soil litter of tropical dry forest with analysis of setal homology in the genus Neophyllobius
Fig. 4. Schematic tarsal setations of Neophyllobius cibyci sp. nov. A–D. ♀, holotype. A. Tarsus I. B. Tarsus II. C. Tarsus III. D. Tarsus IV. E–H. ♁, paratype (CNAC009238). E. Tarsus I. F. Tarsus II. G. Tarsus III. H. Tarsus IV. I–L. Protonymph, paratype (CNAC009241). I. Tarsus I. J. Tarsus II. K. Tarsus III. L. Tarsus IV. M–O. Larva, paratype (CNAC009242). M. Tarsus I. N. Tarsus II. O. Tarsus III.
Fig. 1 in Camerobiid mites (Acariformes: Raphignathina: Camerobiidae) inhabiting epiphytic bromeliads and soil litter of tropical dry forest with analysis of setal homology in the genus Neophyllobius
Fig. 1. Neophyllobius cibyci sp. nov., ♀, holotype. A. Palp. B. Subcapitulum. C. Dorsal idiosoma. D. Ventral idiosoma. E. Trochanter–tibia of leg I. F. Tarsus I.
Fig. 2 in Camerobiid mites (Acariformes: Raphignathina: Camerobiidae) inhabiting epiphytic bromeliads and soil litter of tropical dry forest with analysis of setal homology in the genus Neophyllobius
Fig. 2. Neophyllobius cibyci sp. nov. A–B. ♁, paratype (CNAC009238). A. Dorsal idiosoma. B. Ventral idiosoma. C–D. Protonymph, paratype (CNAC009241). C. Dorsal idiosoma. D. Ventral idiosoma. E–F. Larva, paratype (CNAC009242). E. Dorsal idiosoma. F. Ventral idiosoma.
Long-term litter fall data series from 34 boreal forest stands in Finland
<p><strong>Introduction</strong></p> <p>Litter fall data were collected on a network of 34 forest sampling plots in Finland from late 1950s to 2010s. The data collection spanned different time periods in different sampling plots. The data have been used for studies on the flowering and seed crop of forest trees, air quality, and insect damage (see list of publications in the end of this document). They have been used to develop seed production and needle litter fall models for Scots pine (<em>Pinus sylvestris</em>) and Norway spruce (<em>Picea abies</em>), a branch litter model for pine, and total litter fall models used in greenhouse gas inventories.</p> <p><strong>Data collection</strong></p> <p>The litter fall collection was set up in mature, single species stands. The focal tree species include Scots pine (<em>Pinus sylvestris</em>), Norway spruce (<em>Picea abies</em>), Silver birch (<em>Betula pendula</em>), Downy birch (<em>Betula pubescens</em>), Grey alder (<em>Alnus</em> <em>incana</em>), European rowan (<em>Sorbus aucuparia</em>), European larch (<em>Larix decidua</em>), and Siberian larch (<em>Larix sibirica</em>). The sampling plots varied in shape and in size with a typical area of 0.1-0.25 ha. Between 6 and 30 litter collecting funnels were used per plot. The funnels were made of galvanized sheet metal and attached to cloth bags to collect the falling litter. The sampling sites were monitored for changes in conditions, such as natural disturbances, tree harvesting, forestry operations, or construction on the plot or in its immediate proximity (none observed).</p> <p>The litter samples were collected from the sampling plots, usually four to six times per year in spring to autumn. The samples were dried in room temperature (except male flowers in 1960s – 1970s, see note in Table 1) and stored in paper bags. The dried samples were sorted into litter fractions (Table 1). These fractions varied between tree species and between years to some extent. Cones and seeds were counted, and all other litter fractions were weighed to the nearest milligram.</p> <table> <caption>Table 1. Litter fractions and their codes. The code of the litter fraction is used in the data files.</caption> <thead> <tr> <th scope="col">Code</th> <th scope="col">Litter fraction</th> <th scope="col">Description / note</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>Male flowers</td> <td>In the 1960s – 1970s male flowers were dried in 105°C for 24 hours (Sarvas 1962, 1968).</td> </tr> <tr> <td>2</td> <td>Seeds</td> <td>Seed wings and seeds from species other than the focal one were included into the “other litter” fraction.</td> </tr> <tr> <td>3</td> <td>Female flowers</td> <td> </td> </tr> <tr> <td>4</td> <td>Needles</td> <td> </td> </tr> <tr> <td>5</td> <td>Insects and their faeces</td> <td> </td> </tr> <tr> <td>6</td> <td>Other litter</td> <td> </td> </tr> <tr> <td>7</td> <td>Lichens, branches, and tree bark</td> <td>In some years lichens, branches, and bark were combined in the same fraction, and in some they were separated in their own fractions (numbers 12-14 below).</td> </tr> <tr> <td>8</td> <td>Small cones (1 year)</td> <td>For pine stands, cones were separated into one-year old small cones and large cones. Cones were counted.</td> </tr> <tr> <td>9</td> <td>Cones</td> <td> </td> </tr> <tr> <td>10</td> <td>Cones and loose scales</td> <td>In some years loose scales were included in the same fraction as cones, and in some they were included into the “other litter” fraction.</td> </tr> <tr> <td>11</td> <td>Shifting dust</td> <td> </td> </tr> <tr> <td>12</td> <td>Branches</td> <td> </td> </tr> <tr> <td>13</td> <td>Lichens</td> <td> </td> </tr> <tr> <td>14</td> <td>Tree bark</td> <td> </td> </tr> <tr> <td>15</td> <td>Leaves</td> <td>For deciduous stands, leaves were separated into small (diameter < 1 cm) and large leaves (diameter > 1 cm), while for conifer stands all leaves were included into the “other litter” fraction.</td> </tr> <tr> <td>16</td> <td>Berries</td> <td> </td> </tr> </tbody> </table> <p>In addition to litter fall data, tree stand data were collected on most of the plots in some years. In the tree stand inventories, all trees in the sampling plot with diameter at breast height ≥ 7 cm were mapped, and all trees were counted and measured for diameter (at breast height and at 6 meters), total height, and height to first living branches. Stand basal area and dominant diameter and height were calculated. Stand age was estimated based on core samples from five trees outside but representative of the sample plot. Crown coverage was estimated with a Cajanus tube.</p> <p><strong>Description of the data files</strong></p> <p>The litter fall data is in eight csv-files, one per tree species. The files are named “Litter_Tree_species.csv”, for example “Litter_Betula_pendula.csv”.</p> <p>Variables (in columns) are consistent across the files (explained in Table 2), but note that there are varying numbers of columns between the tables in the files, as each litter collecting funnel has its own column and different maximum numbers of funnels were used in different sampling sites and tree species (see row “S1 – S30” in Table 2 for more details).</p> <table> <caption>Table 2. Variables included in the litter fall data files.</caption> <thead> <tr> <th scope="col">Variable name</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>PlotName</td> <td>Name of sampling plot.</td> </tr> <tr> <td>PlotAbbr</td> <td>Abbreviation of sampling plot name.</td> </tr> <tr> <td>Form</td> <td>Number identifying the original paper form.</td> </tr> <tr> <td>Year</td> <td>Year of data collection.</td> </tr> <tr> <td>TreeSpecies</td> <td>Tree species code: 1 = Scots pine, 2 = Norway spruce, 3 = Silver birch, 4 = Downy birch, 5 = Grey alder, 6 = Siberian larch, 7 = European larch, 8 = European rowan.</td> </tr> <tr> <td>LitterFraction</td> <td>Code for the litter fraction (1-16), explained in Table 1.</td> </tr> <tr> <td>Coefficient</td> <td>Coefficient used to transform the weight of the litter (g) to weight per square meter (g m<sup>-2</sup>). The coefficient is based on the number and area of the collection funnels.</td> </tr> <tr> <td>Date</td> <td>Date of sample collection.</td> </tr> <tr> <td>Period</td> <td>Variable used to define the time of data collection as calendar year or phenological year. The variable is based on the schedule of data collection in different years and on the focal tree species so that it corresponds to the species-specific litter fall schedule. For spruce, the peak needle fall is in the spring, so the calendar year is appropriate for describing the temporal variation in litter fall. For pine, the peak needle fall is in August–September, so a phenological year defined as July 1<sup>st</sup> – June 30<sup>th</sup> is appropriate for describing the temporal variation in litter fall. Period = -1 means the values in the row are allocated to the previous calendar year; period = 0 means the values are allocated to the current calendar year; and period = 1 means the values are allocated to the next calendar year.</td> </tr> <tr> <td>S1 – S30</td> <td>Columns S1 – S30 refer to litter collection funnels 1 – 30. The maximum number of funnels varies between tree species: for <em>silver birch</em> up to 30 funnels were used per plot, for downy birch up to 20 funnels, for spruce up to 10 funnels, for pine up to 15 funnels, for rowan 10 funnels, and for both larch species and alder 8 funnels. Missing values (NA) mean that the funnel was not used in the plot. Value -1 means that the funnel was used but the sample was missing. The values give the dry weight of the litter in mg.</td> </tr> <tr> <td>Combined</td> <td>For some samples, litter collected by different funnels has been combined and the total weight is shown in column S1. In this column, 0 = values have not been combined, and 1 = values have been combined.</td> </tr> <tr> <td>TotalWeight</td> <td>Total weight of the litter (mg).</td> </tr> <tr> <td>TotalWeightArea</td> <td>Total weight of the litter per area (mg m<sup>-2</sup>). Value is same as TotalWeight × Coefficient.</td> </tr> <tr> <td>Note</td> <td>Note</td> </tr> </tbody> </table> <p>Tree stand data is in one csv-file, named “Tree_stand_data.csv”, and can be combined with the litter fall data based on the sample plot abbreviations (variable “PlotAbbr” in both litter fall data files and the tree stand data file). Note that there is no tree stand data available for all the same years as litter fall data. There is no tree stand data available at all for one downy birch site (abbreviation HEI568), one spruce site (NOO85), one pine site (HEI566), and the alder, rowan, and larch sites. Tree stand data variables are explained in Table 3.</p> <table> <caption>Table 3. Variables included in the tree stand data file.</caption> <tbody> <tr> <td>Variable name</td> <td>Description</td> </tr> <tr> <td>PlotName</td> <td>Name of sampling plot.</td> </tr> <tr> <td>PlotAbbr</td> <td>Abbreviation of sampling plot name.</td> </tr> <tr> <td>Year</td> <td>Year of data collection.</td> </tr> <tr> <td>TreeSpecies</td> <td>Dominant tree species. 1 = Scots pine, 2 = Norway spruce, 3 = Silver birch, 4 = Downy birch.</td> </tr> <tr> <td>Age</td> <td>Stand age (years).</td> </tr> <tr> <td>SiteType</td> <td>Forest site type describing site productivity. 2 = xeric heath forest, 3 = sub-xeric heath forest, 4 = mesic heath forest, 5 = herb-rich heath forest. </td> </tr> <tr> <td>North</td> <td>North coordinate (m), coordinate system ETRS-TM35FIN.</td> </tr> <tr> <td>East</td> <td>East coordinate (m), coordinate system ETRS-TM35FIN.</td> </tr> <tr> <td>Elevation</td> <td>Elevation (m above sea level).</td> </tr> <tr> <td>N</td> <td>Stem number (ha<sup>-1</sup>).</td> </tr> <tr> <td>BA</td> <td>Basal area (m<sup>2</sup> ha<sup>-1</sup>).</td> </tr> <tr> <td>DomD</td> <td>Diameter (cm) of dominant trees.</td> </tr> <tr> <td>DomH</td> <td>Height (m) of dominant trees.</td> </tr> <tr> <td>CrownLength</td> <td>Crown length (m).</td> </tr> <tr> <td>V</td> <td>Stem volume (m<sup>3</sup> ha<sup>-1</sup>).</td> </tr> <tr> <td>CrownCover</td> <td>Crown coverage (%).</td> </tr> </tbody> </table> <p> </p> <p><strong>List of publications </strong></p> <p>Hilli, A., Hokkanen, T., Hyvönen, J. & Sutinen, M.-L. 2008. Long-term variation in Scots pine seed crop size and quality in northern Finland. Scandinavian Journal of Forest Research 23(5): 395-403. </p> <p>Koski, V. & Tallqvist, R. (1978). Results of long-time measurements of the quantity of flowering and seed crop of forest trees (in Finnish with English summary). Folia Forestalia, 364, 1-60. </p> <p>Kouki, J. & Hokkanen, T. 1992. Long-term needle litterfall of a Scots pine Pinus sylvestris stand: relation to temperature factors. Oecologia 89: 176-181. </p> <p>Lehtonen, A., Lindholm, M., Hokkanen, T., Salminen, H. & Jalkanen, R. 2008. Testing dependence between growth and needle litterfall in Scots pine - a case study in northern Finland. Tree Physiology 28(11): 1741-1749. </p> <p>Lehtonen, A., Sievänen, R., Mäkelä, A., Mäkipää, R., Korhonen, K.T. & Hokkanen, T. 2004. Potential litterfall of Scots pine branches in southern Finland. Ecological Modelling 180(2-3): 305-315. </p> <p>Leikola, M., Raulo, J. & Pukkala, T. (1982). Prediction of the variations of the seed crop of Scots pine and Norway spruce (in Finnish with English summary). Folia Forestalia, 537, 1-43. </p> <p>Niemistö, P., Hokkanen T. & Varama, M. 2004. Karikemäärän muutokset 1982–2001 ja puiden kunto lumi- ja hallamittariesiintymän vaivaamissa koivikoissa Noormarkussa. Metsätieteen aikakauskirja 1/2004: 21–41. </p> <p>Poikolainen, J. & Kuusinen, M. 2000. Abundance of epiphytic lichens in litterfall during 1967-1994. In: Forest condition in a changing environment - the Finnish case. Forestry Sciences, Vol. 65. Kluwer Academic Publishers / Ed. Mälkönen, E. Sivut: 171-172. </p> <p>Pukkala, T. 1987a. A model for predicting the seed crop of Picea abies and Pinus sylvestris (in Finnish with English abstract). Silva Fennica 21(2): 135-144. </p> <p>Pukkala, T. 1987b. Effect of seed production on the annual growth of Picea abies and Pinus sylvestris (in Finnish with English abstract). Silva Fennica 21(2): 145-158. </p> <p>Pukkala, T., Hokkanen, T. & Nikkanen, T. 2010. Prediction models for the annual seed crop of Norway spruce and Scots pine in Finland. Silva Fennica 44(4): 629-642. </p> <p>Ranta, E., Lindström, J., Kaitala, V., Crone, E., Lundberg, P., Hokkanen, T. & Kubin, E. 2010. Life history mediated responses to weather, phenology and large-scale population patterns. In: Hudson, I. L & Keatley, M. R. (eds.). Phenological Research. Springer, Dordrecht Heidelberg London New York, Netherlands. p. 321-338. </p> <p>Raulo, J. & Hokkanen, T. 1989. Litter fall of Alnus incana and Alnus glutinosa (in Finnish with English summary). Folia Forestalia 738. 25 s.</p> <p>Saarsalmi, A., Starr, M., Hokkanen, T., Ukonmaanaho, L., Kukkola, M., Nöjd, P. & Sievänen, R. 2007. Predicting annual canopy litterfall production for Norway spruce (Picea abies (L.) Karst.) stands. Forest Ecology and Management 242(2-3): 578-586. </p> <p>Sarvas, R. (1962). Investigations on the flowering and seed crop of Pinus Silvestris. Communicationes Instituti Forestalis Fenniae, 53, 1-198. </p> <p>Sarvas, R. 1968. Investigation on the flowering and seed crop of Picea abies. Communicationes Instituti Forestalis Fenniae 67.5. 84 pp. </p> <p>Starr, M., Saarsalmi, A., Hokkanen, T., Merilä, P. & Helmisaari, H.-S. 2005. Models of litterfall production for Scots pine (Pinus sylvestris L.) in Finland using stand, site and climate factors. Forest Ecology and Management 205: 215-225. </p> <p>Ťupek, B., Mäkipää, R., Heikkinen J., Peltoniemi, M., Ukonmaanaho, L., Hokkanen, T., Nöjd, P., Nevalainen, S., Lindgren, M. & Lehtonen, A. 2015: Foliar turnover rates in Finland — comparing estimates from needle-cohort and litterfall-biomass methods. Boreal Environment Research 20: 283–304</p>
Fig. 2 in Species Structure Of Oribatid Mite Population (Acari, Oribatea) In The Forest Floor Litter In The Reclaimed Territories (Ukraine)
Fig. 2. Stratigraphic types of artificial edaphotopes within the experimental-production reclamation site.
Fig. 1 in Species Structure Of Oribatid Mite Population (Acari, Oribatea) In The Forest Floor Litter In The Reclaimed Territories (Ukraine)
Fig. 1. Location of the Western Donbas coal basin in the Dnipropetrovsk Region, Ukraine: WD — Western Donbas.
Fig. 6 in Species Structure Of Oribatid Mite Population (Acari, Oribatea) In The Forest Floor Litter In The Reclaimed Territories (Ukraine)
Fig. 6. Average population density and species richness of oribatid mites on different recultivation types within red cedar plantation.
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