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261 results for “litter decomposition”

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edi48/100

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.

openCC (other)Nov 2023View details →

zenodo44/100

Litter decomposition is moderated by scale-dependent microenvironmental variation in tundra ecosystems

QHI_crop.tiff = We carried out topographic surveys using unoccupied aerial vehicles photogrammetry in August 2017. We used three UAV platforms to collect RGB multispectral data at a fine (3 cm) spatial resolution: DJI Phantom 4 Pro and Advanced (multicopter), and Phantom FX-61 (fixed wing), and used  used structure from motion with multiview steriopsis to obtain a fine-grain 10 cm spatial resolution digital surface model and orthomosaic as described in Cunliffe et al. (2019a, 2019b). thermsum.tif = We used the microclima package in R (Kearney et al., 2020; Maclean et al., 2019) to model surface air temperature at a 1-m spatial grain. Using our fine resolution DSM, we modelled mean surface temperatures at the study site for each day spanning the teabag burial period of 13th July to 9th August 2017. The microclima model incorporates local daily climate, radiation, cloud cover and coastal exposure data from gridded global datasets derived from RCNEP (<a href="https://www.zotero.org/google-docs/?broken=Zl6wgI">Kemp et al., 2012)</a>. We summed the 28 TIF files produced through this modelling technique to produce a 28-day thermal sum variable - a metric which captures the overall heating of the ground surface over the course of the experiment. Cited Works:   Cunliffe, A., I. Myers-Smith. J. Kerby and W. Palmer (2019a). Orthomosaic of permafrost landscape on Qikiqtaruk – Herschel Island, Yukon, Canada: August 2017. NERC Polar Data Centre. DOI:10.5285/29bf1c9f-a39a-452c-b9f9-de35d9fb9179.   Cunliffe, A., G. Tanski, B. Radosavljevic, W. Palmer, T. Sachs, H. Lantuit, J. Kerby, and I. Myers-Smith (2019b) Rapid retreat of permafrost coastline observed with aerial drone photogrammetry. The Cryosphere 13(5):1513-1528. DOI: 10.5194/tc-13-1513-2019.   <a href="https://www.zotero.org/google-docs/?hjdBYY">Maclean, I. M. (2020). Predicting future climate at high spatial and temporal resolution. Global Change Biology, 26(2), 1003–1011.</a>   Kearney, M. R., Gillingham, P. K., Bramer, I., Duffy, J. P., & Maclean, I. M. (2020). A method for computing hourly, historical, terrain‐corrected microclimate anywhere on Earth. Methods in Ecology and Evolution, 11(1), 38-43.   Kemp, M. U., Van Loon, E. E., Shamoun-Baranes, J., & Bouten, W. (2012). RNCEP: global weather and climate data at your fingertips. Methods in Ecology & Evolution, 3(1), 65-70. Paper Abstract: <ol> <li> The Arctic tundra is one of the world’s largest organic carbon stores, yet this carbon is  vulnerable to accelerated decomposition as climate warming progresses. We currently know very little about landscape-scale controls of litter decomposition in tundra ecosystems, which hinders our understanding of the global carbon cycle.  </li> <li> Here, we examined how local-scale topography, surface air temperature, soil moisture and permafrost conditions influenced litter decomposition rates across a heterogeneous tundra landscape on Qikiqtaruk - Herschel Island (Yukon, Canada). </li> <li> We used the Tea Bag Index protocol to derive decomposition metrics which we then compared across environmental gradients, including thermal sum surface temperature data derived from fine-resolution microclimate data modelled from drone derived topographic data. </li> <li> We found greater green tea litter mass loss and faster decomposition rates in wetter and warmer areas within the landscape, and to a lesser extent in areas with deeper permafrost active layer thickness. </li> <li> Spatially heterogeneous belowground conditions (soil moisture and active layer depth) explained variation in decomposition metrics at the landscape-scale (> 10 m) better than surface temperature. </li> <li> Surprisingly, there was no strong control of elevation or slope of litter decomposition. We also found higher decomposition rates on North-facing relative to South-facing aspects at microsites that were wetter rather than warmer. </li> </ol>

opencc-by-4.0Apr 2022View details →

zenodo44/100

Soil carbon stock, litter decomposition, and weather data from Ethiopian forests

Introduction 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. Soil profile sampling 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 cm3 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.  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.    Soil physical characteristics 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.  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.    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.   For Figure 1. See Soil_C_Ethiopia.pdf Figure 1. 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: OCadj = 1.165 * OCwet. 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”.   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). \(SOCstock = C_{org} * BD_{fe} * (1-S)\) Soil organic carbon stock data Files: “SOC_Ethiopia_2017-2018.csv” and “SOC_Ethiopia_2017-2018.xlsx” 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. In the .csv file individual columns are for  LAT is the latitude of the sampling site corresponding to FieldCode and SU_nr LON is the longitude of the sampling site corresponding to FieldCode and SU_nr <ul> <li>The coordinates are expressed as decimal degrees of the WGS84 system</li> </ul> FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below)  SU_nr is the Sampling Unit number of the Ethiopian NFI Region is the name of the administrative region where the sample was taken Biome is the name of the forest biome type where the sample was collected BiomeSimplified is the name of a biome with some close types combined DepthRange is the upper and lower limit of the soil sample in the field, cm StoninessVFAST is a percentage of stones (VS-FAST by FAO) in the ca. 40 cm deep soil profile exposed during the sampling FreshMassInField 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 NrComposites is the number of subsamples included in the composite for each soil layer CorerVolume is a constant of 107.5 cm3 because only one type of corer was used for undisturbed, volumetric sampling CompositeVolume is the volume of the composite sample for each soil depth layer CoarseFractionMass is the dry mass, g of soil particles > 2mm that did not pass the sieve, but were included in the sample volume FE_DryMass is oven-dry mass, g of the fine fraction that passed the 2 mm sieve. BDtot is total bulk density, g m-3, calculated for the composite sample BDfe is the bulk density of the fine earth fraction, g m-3 OC_adj is organic carbon (OC) content (%) in the composite sample, adjusted according to the comparison between dry and wet oxidation methods (Fig. 1) SOCfe is SOC stock calculated for soil fine earth fraction, t ha-1 in the 10 cm deep soil layer SOCfe_stoniness is SOC stock of the fine earth fraction, t ha-1 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.    Litter stock data File: “Litter_Ethiopia_2017-2018.csv” 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.   The depth of the litter layer was measured in the field. Litter from the respective spot was sampled quantitatively from a frame of 0.01m2 of area for litter dry mass estimate. The organic C stock in a litter (L) was calculated as,   \(L = {M\over z} * {C_{om}\over A}, \)   where M = Dry mass of the litter sample, g z = Depth of the litter layer in the field, m Com = Conversion factor from dry organic matter to carbon (C), 0.5 A = area of quantitative collection of litter (0.01 m2)   In the .csv file individual columns are for LAT, LON is the GPS coordinates (decimal degrees of WGS84) for the Sampling Units (SU_ID) SU_ID is the Sampling Unit identification number of the Ethiopian NFI FieldCode refers to the Region and Sampling Unit number of the Ethiopian NFI (see below) Region is the name of the administrative region where the sample was taken Litter_dry is the dry mass, g of the litter sample Area_m2 is the area, m2 of litter sampling MeanLitterDepth is the mean depth of the litter layer at the sampling area CDensityLitter is the dry bulk density of the litter, g m-2 multiplied by the assumed organic C proportion of the oven-dry litter materials (0.50) LitterCStock_tha is the litter stock, t ha-1 calculated from the C density of the litter layer   Litter bag data (decomposition and quality) 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 Juniperus procera and Podocarpus falcatusbeing the main species forming the tree canopy. The sites form an elevation gradient (Table 1).   Table 1. Geographical locations of the study sites in the Chilimo forest.   <table> <tbody> <tr> <td> id </td> <td> Latitude (deg.) </td> <td> Longitude (deg.) </td> <td> Elevation (m a.s.l) </td> </tr> <tr> <td> 1 </td> <td> 9.0672 </td> <td> 38.1443 </td> <td> 2500 </td> </tr> <tr> <td> 2 </td> <td> 9.0712 </td> <td> 38.1556 </td> <td> 2670 </td> </tr> <tr> <td> 3 </td> <td> 9.0869 </td> <td> 38.1684 </td> <td> 2800 </td> </tr> </tbody> </table>   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.    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. <table> <tbody> <tr> <td> Litter type </td> <td> Species </td> <td> A </td> <td> W </td> <td> E </td> <td> N </td> </tr> <tr> <td> leaves fresh </td> <td> Juniperus  </td> <td> 0.45 </td> <td> 0.13 </td> <td> 0.1 </td> <td> 0.33 </td> </tr> <tr> <td> leaves fresh </td> <td> Podocarpus  </td> <td> 0.42 </td> <td> 0.28 </td> <td> 0.05 </td> <td> 0.25 </td> </tr> <tr> <td> leaves old </td> <td> Juniperus  </td> <td> 0.44 </td> <td> 0.07 </td> <td> 0.08 </td> <td> 0.41 </td> </tr> <tr> <td> leaves old </td> <td> Podocarpus  </td> <td> 0.44 </td> <td> 0.09 </td> <td> 0.05 </td> <td> 0.42 </td> </tr> <tr> <td> twigs </td> <td> Juniperus  </td> <td> 0.61 </td> <td> 0.04 </td> <td> 0.02 </td> <td> 0.32 </td> </tr> <tr> <td> twigs </td> <td> Podocarpus  </td> <td> 0.56 </td> <td> 0.15 </td> <td> 0.02 </td> <td> 0.27 </td> </tr> </tbody> </table>   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”.   Soil temperature data 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”.   Processed weather data 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.     References:   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. Land Degradation & Development, 31(18), pp.2763-2774.   FRL 2017. https://redd.unfccc.int/files/ethiopia_frel_3.2_final_modified_submission.pdf

opencc-by-4.0May 2022View details →

zenodo44/100

Nutrient controls on carbohydrate and lignin decomposition in beech litter

Raw data for Nutrient controls on carbohydrate and lignin decomposition in beech litter Lukas Kohl, Wolfgang Wanek, Katharina Keiblinger, Ieda Hämmerle, Lucia Fuchslueger, Thomas Schneider, Katharina Riedel, Leo Eberl, Sophie Zechmeister-Boltenstern, Andreas Richter https://doi.org/10.1016/j.geoderma.2022.116276

opencc-by-4.0Oct 2022View details →

edi44/100

Decomposition of Microstegium vimineum litter, plants grew through the Big Oaks National Wildlife Refuge in 2019. Litter used in this experiment naturally senesced in the fall 2019, decomposition data collected through 2020. Plants were infected or not-infected with the foliar fungal pathogen Bipolaris gigantea during the 2019 growing season.

Decomposition of plant litter, facilitated primarily by microbial decomposers, plays a critical role in biogeochemical cycling and ecosystem function. Emerging pathogens have the potential to impact litter decomposition by altering the chemical composition and associated microbial community of host tissue. Here, we compared litter decomposition of the invasive grass Microstegium vimineum collected from sites with Bipolaris leaf spot symptoms and sites with no apparent disease symptoms in a common garden experiment. Our results revealed that leaf tissue from litter from non-infected sites decomposed more rapidly through the spring than litter from infected sites. Differences in fungal composition between infected and non-infected litter at the start of the experiment largely persisted through the summer. Our work demonstrates that pathogen colonization may facilitate the persistence of infected host litter, potentially slowing the return of nutrients to the environmental pool while also promoting the survival and dispersal of primary inoculum the following season.

openCC (other)Jun 2023View details →

edi44/100

LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002

The primary objective of this study is to examine the control that substrate quality and climate have on patterns of long-term decomposition and nitrogen accumulation in above- and below-ground fine litter. Of particular interest will be to examine the degree these two factors control the formation of stable organic matter and nitrogen after extensive decay.

openCustomAug 2016View details →

edi44/100

Effects of experimentally altered wolf spider densities and warming on soil microarthropods, litter decomposition, litter N, and soil nutrients near Toolik Field Station, AK in summer 2012

Predators can disproportionately impact the structure and function of ecosystems relative to their biomass. These effects may be exacerbated under warming in ecosystems like the Arctic, where the number and diversity of predators are low and small shifts in community interactions can alter carbon cycle feedbacks. Here we show that warming alters the effects of wolf spiders, a dominant tundra predator, on belowground litter decomposition and nutrient dynamics. Specifically, while high densities of wolf spiders result in faster litter decomposition under ambient temperatures, they result instead in slower decomposition under warming. Higher spider densities are also associated with elevated levels of available soil nitrogen, potentially benefitting plant production. Changes in decomposition rates under increased wolf spider densities are accompanied by trends toward fewer fungivorous Collembola under ambient temperatures and more Collembola under warming, suggesting that Collembola mediate the indirect effects of wolf spiders on decomposition. The unexpected reversal of wolf spider effects on Collembola and decomposition suggests that in some cases, warming does not simply alter the strength of top-down effects but instead induces a different trophic cascade altogether. Our results indicate that climate change-induced effects on predators can cascade through other trophic levels, alter critical ecosystem functions, and potentially lead to climate feedbacks with important global implications. Moreover, given the expected increase in wolf spider densities with climate change, our findings suggest that the observed cascading effects of this common predator on detrital processes could potentially buffer concurrent changes in decomposition rates.

openCC (other)Jun 2018View details →

edi44/100

Nitrogen cycling at treeline VI. Common Litter Decomposition

To assess spatial and seasonal patterns of pools and fluxes of dissolved inorganic- N (DIN), amino acid- N (AAN) and microbial biomass N (MBN), we conducted in situ soil incubations at four time periods during May 2001 - May 2002: spring thaw, peak growing season, fall senescence and over-winter. The goal was to be consistent in sampling each of these time periods within each mountain range, which was possible due to the 3-4 week lag in phenology (e.g. budbreak or initiation of senescence) between the southernmost and northernmost sites. Sites were sampled in order from south to north. During the spring 2002 sampling period, soils in the Brooks Range thawed prior to those in the White Mts. and the sampling sequence was adjusted to accommodate this. Within each treeline or forested sub-site, a 50 m transect was established parallel with the slope contour of the mountain. Six points were randomly selected along each transect, and soils were sampled near these points for the entire year. Rates of net DIN mineralization and net AAN production were measured using an in situ buried bag technique (Robertson et al., 1999). We used a 6.7 cm diameter steel corer fitted with a perforated, plastic sleeve to collect paired adjacent soil cores, and sampled below the live moss and detritus layers to a depth of 20 cm. The function of the perforated sleeve was to maintain structural integrity of the soil core during sampling. The perforated sleeve containing the intact core was then placed in a 1 mil breathable polyethylene bag followed by a fine mesh bag, gently returned to the original location, covered with litter and left to incubate. Incubation length was 4 weeks for the spring, growing season, and senescence sampling periods, and from September 2001 to early June 2002 for the over-winter sampling period. The second core in each pair was stored on ice and transported to the laboratory in Fairbanks. Soils were rocky at some sites and sampling to 20 cm was not possible; for these

openOpenMar 2009View details →

edi44/100

Ectomycorrhizal fungal effects on soil carbon storage, root litter decomposition, and fungal necromass decomposition

This project investigates the impacts of ectomycorrhizal-saprotrophic fungal interactions on soil C storage and the decomposition of root litter and fungal necromass. Specifically, we conducted a field experiment wherein the ectomycorrhizal:saprotrophic fungal ratio was reduced via experimental trenching (with control plots left untrenched). From these plots we then measured bulk soil C stocks, particulate organic matter C stocks, mineral associated organic matter C stocks, and the decomposition of root litter and fungal necromass. The Cedar Creek Ecosystem Science Reserve (CCESR) experiment name is e309 "The effects of mycelial morphology and mycorrhizal type on fungal necromass decomposition."

openCC0Aug 2023View details →

edi44/100

Cross-site decomposition of leaf litter in terrestrial and aquatic habitats, CWT and LUQ, 2000 (species Buchenavia capitata, Dacryodes excelsa, Guarea guidonia, Quercus prinus).

Comparison of decomposition and nutrient losses from three species of leaf litter in terrestrial and aquatic habitats at CWT and LUQ LTER sites. Overall hypothesis is that macro-consumers have different patterns and impacts on decomposition rates than microbial decomposers, and that these patterns are magnified in litters of low vs. high qualities over the two years of the experiment.

openCustomJan 2020View details →

edi44/100

Litter decomposition in canopy gradient plots at the Coweeta Hydrologic Laboratory in 1998

Decomposition is frequently measured using litter bags containing known amounts of litter. A set of litter bags can be sampled over time and the weight loss which is measured serves as an index of decomposition. By measuring litter breakdown rate (decomposition) of the same species of litter along the elevation gradient, we could measure variation among the different elevations due to our treatments and elevation effects. Treatments used on quadrat boxes include frass additions (boxes 3,8,13,18,23), thrufall additions (boxes 4,9,14,19,24), controls (boxes 5,10,15,20,25), greenfall exclusion (boxes 2,7,12,17,22) and litterfall exclusion (boxes 1,6,11,16,21).

openCustomJan 2020View details →

edi44/100

Litter decomposition in quadrat treatments along elevation gradient for canopy herbivore input study at the Coweeta Hydrologic Laboratory from 1997 to 1999

Decomposition is frequently measured using litter bags containing known amounts of litter. A set of litter bags can be sampled over time and the weight loss which is measured serves as an index of decomposition. By measuring litter breakdown rate (decomposition) of the same species of litter along the elevation gradient, we could measure variation among the different elevations due to our treatments and elevation effects. Treatments included frass additions, thrufall additions, greenfall exclusion, all litter excluded, and controls.

openCustomJan 2020View details →

edi44/100

Coweeta Watershed 1 Litter and Soil Temperature for White Pine Decomposition Study from 2002 to 2004

These data are the hourly readings of litter and soil temperature in the center of each litter decomposition plot. The study was conducted at the Watershed 1 Permanent Census Plot Locations: 14, 15, 22, 28, 62, 70, 74, 90.

openCustomJan 2020View details →

edi44/100

Litter decomposition rates and litter nutrient content in Coweeta white pine watershed 1 from 2001 to 2004

Litterbag mass remaining in litterbags and rate of decay were compared between 4 beetle-infested and 4 non-beetle-infested white pine plots in watershed 1.

openCustomJan 2020View details →

edi44/100

Litter decomposition data from the Coweeta Hydrologic Laboratory from 1993 to 1995

Litter bags (5 X 5 cm, 1mm nylon mesh) were filled with 5 0.2 g of air dried litter from R. maximum or Q. prinus (two dominant tree species in the watershed). The bags were then placed upon the soil surface along transects 1, 5, and 15 meters upslope from the stream (as described for microbial C and N). Bags were placed in the field in December, 1993. Three replicate bags of each litter type were collected from both sites and all transects, every three months. Upon retrieval, leaves were dried and cleaned of any residual soil particles. Samples were then weighed to determine percent weight loss, over time. In these data files, litter decomp studies are saved by species (Q. prinus or R. max) and then by distance from the stream (1, 5, or 15 meters). The # of days column is the amount of time the bags were in the field. % weight remaining is> the proportion of weight upon collection to initial weight. This is followed by the average % weight remaining for each collection date and its standard deviation. The average C/N is the C/N ratio for the litterbags, by collection date. The total C and N for litter was determined using the Carlo Erba Total C and N analyzer.

openCustomJan 2020View details →

edi44/100

Decomposition rates of four litter types along coastal gradients in Everglades National Park (FCE LTER), Florida, USA: 2020-2021

Leaf litter, of variable quality, was deployed along freshwater-to-marine gradients to investigate the drivers of litter breakdown in the Florida Coastal Everglades. Sea-level rise provides both stressors and subsidies to microbial communities that break down litter, and is also causing shifts in the vegetation producing litter, changing the initial quality of litter being deposited in coastal wetlands. The goal of this project was to understand the complex relationship between marine stressors and subsidies, by performing a reciprocal transplant of litter. Litter from each major vegetation species along the freshwater to marine gradient were deployed at sites in freshwater, the ecotone, mangrove forest, and in Florida Bay. This reciprocal transplant of different qualities of leaf litter into novel environments across a gradient of salinity and phosphorus will give insights into the effects of litter carbon quality, littery chemistry, microbial productivity of decomposers, and environmental chemistry as drivers of the breakdown of leaf litter.

openCC (other)Apr 2022View details →

edi44/100

Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE): Leaf Litter Decomposition 2012-2014

Decomposition of leaf litter is a major source of nutrient transfer from vegetation to soils and an important carbon flux. In northern hardwood forests, litter decomposition might be affected by nutrient availability, species composition, stand age or structure, or access by soil decomposers. We investigated these factors in four stands at the Bartlett Experimental Forest in New Hampshire that have had nitrogen and phosphorus added in full factorial design since 2011. Leaf litter of early and late successional species was collected in 2012 and deployed in bags of two mesh sizes (63 µm and 2 mm) in two young and two mature stands and collected three times over the next 2 years. Decomposition was evaluated by fitting mass loss as an exponential function of time represented by growing degree days. Litter decomposed more quickly in the small mesh bags (p < 0.001), which excluded mesofauna. This result was surprising, but might be explained by the greater rigidity of the large mesh material making poor contact with the soil. The litter with a species composition characteristic of our young stands decomposed more quickly than the litter representing mature stands (p = 0.01 for species mix in the full model). The environment in which is was placed was not as important: Neither the age of the stand in which it was placed (p = 0.31), nor N addition (p = 0.59), P addition (p = 0.41), or the interaction of N and P addition (p = 0.13) were significant predictors of the decomposition rate, defined by fitting an exponential decay constant. Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344 Litter was collected by Rick Bicher and sorted by species by middle school students. Litterbags were made, filled, and weighed by middle school students. Gracie Gilcrist

openCC (other)Oct 2024View details →

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Canopy Trimming Experiment (CTE) Litter decomposition and Connectivity basket data

This experiment was designed to decouple the effects of canopy opening from those of increased detrital inputs on rates of detrital processing and resultant community and ecosystem processes. In a study initiated after massive inputs of organic matter from Hurricane Georges in 1998, the forest floor returned to prehurricane values very quickly, within 2-10 months (Ostertag et al. 2003). However, it was unclear to what extent this homeostasis was caused by increased rates of decomposition. Furthermore, if accelerated decomposition was implicated in rapid recovery, the relative contributions of environmental and resource changes wrought by canopy opening versus green leaf deposition on the forest floor were unclear because these factors are confounded in hurricane damage. A full factorial design was therefore used to tease apart the separate and combined effects of simulated storm damage on rates of mass loss in pre-weighed senesced and green litter cohorts inserted into litter decomposition baskets following application of canopy trimming and debris deposition treatments. Natural litter cohorts (i.e., organic forest floor material and subsequent natural litterfall separated into 3-month cohorts) were also weighed when replicate baskets were harvested at approximately 3-month intervals. In addition to obtaining mass and percent moisture of litter cohorts, the extent of fungal connections between litter cohorts was quantified. Fungal connections between partly decomposed and fresh leaf litter have been shown to be important in importation of phosphorus (the most limiting major nutrient in decomposition of tabonuco forest litter) into the freshly fallen leaves in order to rapidly build fungal biomass and associated acceleration of decomposition (Lodge 1993, 1996). The thickest of these fungal colonization and translocation organs (rhizomorphs, cords and hyphal strands) are primarily basidiomycete fungi, which have an almost unique capacity to cause white-rot by breaking

openCC (other)Nov 2023View details →

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Figure 1 in The TeaComposition initiative: Unleashing the power of international collaboration to understand litter decomposition

Figure 1. TeaComposition initiative. (A) An illustration to the asymptotic model (cf Berg 2014) for decomposition of standard tea bags (0.25mm mesh) of Green (Camelia sinensis) and Rooibos (Asphalantus linearis) tea, representing litter decomposition (here as mass remaining) over a period of three years. Dashed horizontal line shows the limit value (stabilized residue); (B) site distribution in terrestrial (red dots) and aquatic (blue dots) ecosystems across nine world biomes in 2020; (C) Number of participating sites per biome; (D) Networking activities of the initiative include active and potential collaborations with the following global research networks: Soil Biodiversity Observation Network (SoilBON), International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects (ICP), Greenhouse gas inventory (GHG), Sustainable Development Goals (SDGs), Tree Diversity Network (TreeDivNet), Detrital Input and Removal Treatments (DIRT), and Terrestrial Environmental Observatories (TERENO).

opencc-by-4.0Dec 2021View details →

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UV radiation accelerates litter decomposition in a valley-type savanna by enhancing microbial community diversity and function

We present the data of the study by Gao et al. (2024): <a name="_Hlk179470571"></a><a name="OLE_LINK42"></a>UV radiation accelerates litter decomposition in a valley-type savanna by enhancing microbial community diversity and function. The excel file (Raw Data) includes the following sheets: 1- Radiation (w·m-2) variation of UV-A and UV-B during the experimental period. 2- Decay constants (K, yr−1) and changes in the mass loss rate of litter under different UV conditions during the experimental period. 3- The content of lignin, cellulose, C, N and P of litter under different UV conditions during the experimental period. 4- 16S ASVs under different UV conditions. 5- ITS ASVs under different UV conditions.

opencc-by-4.0Nov 2024View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record