scholarly journals How habitat moisture condition affects the decomposition of fine woody debris from different species

CATENA ◽  
2022 ◽  
Vol 208 ◽  
pp. 105765
Author(s):  
Wojciech Piaszczyk ◽  
Jarosław Lasota ◽  
Ewa Błońska ◽  
Kacper Foremnik
Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 881
Author(s):  
Nathalie Korboulewsky ◽  
Isabelle Bilger ◽  
Abdelwahab Bessaad

Volume or biomass estimates of downed woody debris are crucial for numerous applications such as forest carbon stock assessment, biodiversity assessments, and more recently for environmental evaluations of biofuel harvesting practices. Both fixed-area sampling (FAS) and line-intersect sampling (LIS) are used in forest inventories and ecological studies because they are unbiased and accurate methods. Nevertheless, most studies and inventories take into account only coarse woody debris (CWD, >10 cm in diameter), although fine woody debris (FWD) can account for a large part of the total downed biomass. We compared the LIS and FAS methods for FWD volume or biomass estimates and evaluated the influence of diameter and wood density measurements, plot number and size. We used a Test Zone (a defined surface area where a complete inventory was carried out, in addition to FAS and LIS), a Pilot Stand (a forest stand where both LIS and FAS methods were applied) and results from 10 field inventories in deciduous temperate forest stands with various conditions and amounts of FWD. Both methods, FAS and LIS, provided accurate (in trueness and precision) volume estimates, but LIS proved to be the more efficient. Diameter measurement was the main source of error: using the mean diameter, even by diameter class, led to an error for volume estimates of around 35%. On the contrary, wood density measurements can be simplified without much influence on the accuracy of biomass estimates (use of mean density by diameter class). We show that the length and number of transects greatly influences the estimates, and that it is better to apply more, shorter transects than fewer, longer ones. Finally, we determined the optimal methodology and propose a simplification of some measurements to obtain the best time-precision trade-off for FWD inventories at the stand level.


2009 ◽  
Vol 63 (3) ◽  
pp. 239-263 ◽  
Author(s):  
Michael L. Ferro ◽  
Matthew L. Gimmel ◽  
Kyle E. Harms ◽  
Christopher E. Carlton

2015 ◽  
Vol 63 (2) ◽  
pp. 115 ◽  
Author(s):  
Danswell Starrs ◽  
Brendan C. Ebner ◽  
Christopher J. Fulton

Transport and processing of allochthonous material is crucial for trophic pathways in headwater streams. Freshwater crayfish are known to affect and exploit the break-down of in-stream terrestrial plant material into detritus. We recorded Euastacus armatus (Murray River crayfish) individuals feeding on discrete patches of allochthonous material within an unregulated section of the Goodradigbee River, an upland stream in temperate Australia. Despite suggestions of aggressive territoriality, E. armatus were observed by remote and manual underwater filming to feed in non-aggressive aggregations on these piles of fine woody debris and leaf litter. On the basis of observations of 25 individuals found in the vicinity of the allochthonous patches, this population comprised mostly female individuals at smaller sizes of maturity than has been recorded for lowland populations of E. armatus. Our study confirms the importance of concentrated allochthonous food patches for detritivores, and points to the important trophic linkage between terrestrial and aquatic ecosystems via a widespread and iconic freshwater invertebrate. Moreover, these non-aggressive feeding aggregations of E. armatus challenge notions of aggression in this species that have been developed in small-scale aquarium studies.


2013 ◽  
Vol 33 (3) ◽  
pp. 248-255 ◽  
Author(s):  
Kiomars Sefidi ◽  
Mohammad R. Marvie Mohadjer ◽  
Reinhard Mosandl ◽  
Carolyn A. Copenheaver

2020 ◽  
Vol 29 (3) ◽  
pp. e021
Author(s):  
Ovidiu Copoț ◽  
Cătălin Tănase

Aim of the study: The main objective of this study was to find the factors which best explains the wood-inhabiting fungal species’ richness in beech and oak-dominated forests.Area of study: We focused on broadleaved and mixed forests found in Northeastern Romania.Materials and methods: 59 plots were randomly set up in broadleaved and mixed forest stands, in which vegetation structure, composition, and topoclimatic factors were quantified along with wood-inhabiting fungal richness. Generalized linear models were used to characterize relationship between fungal diversity and biotic and abiotic factors.Main results: 374 taxa were identified, with numerous species found to cohabitate, the highest sharing being between Fine Woody Debris and Downed Coarse Woody Debris. The best predictors of total diversity were related to the substrate, management, stand structure, and macroclimate. Higher volumes of logs and large branches in various decay stages increased fungal richness. The same effect was found in diverse forests, with large snags. Macroclimate and topoclimate positively influenced diversity, through De Martonne Aridity Index and snow cover length, both indicating macrofungi preferences for higher moisture of substrate. Silvicultural interventions had an ambivalent effect to fungal diversity, phenomenon observed through stump numbers and proportion.Research highlights: Particular environmental characteristics proved significantly important in explaining different wood-inhabiting fungal richness patterns. Substrate-related variables were the most common ones found, but they were closely linked to climate and forest stand variables.Keywords: Wood-inhabiting fungi; oak, beech and coniferous forests; substrate diversity; dead wood types; coarse woody debris; fine woody debris; climatic variables.Abbreviations used:ALT, elevation; ASPI, Aspect Index; BIO1, mean annual temperature; BIO4, temperature seasonality; BIO7, annual temperature range; BIO12, annual precipitation; BIO15, precipitation seasonality; CWD, coarse woody debris; DBH, diameter at breast height; DCWD, downed coarse woody debris; DCWD_DECAY, DCWD decay diversity; DCWD_DIV, DCWD taxonomic diversity; DCWD_SV, surface-volume ratio of DCWD; DCWD_VOL, DCWD volume; DMAI, De Martonne Aridity Index; DMAI_AU, Autumn DMAI; DMAI_SP, Spring DMAI; DMAI_SU, Summer DMAI; DMAI_WI, Winter DMAI; FAI, Forestry Aridity Index; FWD, fine woody debris; L_SNAG_BA, large snag basal area; OLD_BA, basal area of old trees; POI, Positive Openness Index; RAI, Recent Activity Index; SCL, snow cover length; SLOPE, slope; SNAG_N, snag density; STUMP_N, stump density; TPI, Topographic Position Index; TREE_BA, mean basal area of trees; TREE_DIV, tree' Shannon diversity.


2011 ◽  
Vol 138 (2) ◽  
pp. 192-206 ◽  
Author(s):  
Becky G. Fasth ◽  
Mark E. Harmon ◽  
Jay Sexton ◽  
Peter White

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