Abstraction: Coarse woody dust ( CWD ) is a ill understood constituent of the C rhythm. We report the first measurings of both CWD denseness ( specific gravitation ) and necromass in northwesterly Amazonia, utilizing both line-intersect and plot-based methods. Average CWD densenesss were similar in clay-rich and white sand unflooded woods, but lower in flood plain wood ( p ? 0.001 ) . Necromass of CWD lying on the land was besides lower in the flood plain ( 10.2 ± 6.0 Mg ha-1, average ± SE ) than in the clay-rich ( 30.9 ± 5.4 ) and white sand ( 45.8 ± 7.3 ) woods ( p ? 0.001 ) . These forms are likely driven by perturbation history, floristic composing, and decomposition rates. Plot-based information showed that standing and fallen CWD together accounted for 6.4 to 15.4 % of entire aboveground vegetive mass ( trees ?10 cm diameter ) . Entire necromass in the flood plain wood in this landscape is comparatively low, whereas the unflooded sites are more typical of other neotropical surveies. Across humid, lowland neotropical woods, densenesss of integral and partly decayed CWD are significantly correlated with unrecorded wood denseness at the same site ( p = 0.026 and 0.003, severally ) . These relationships can be applied to gauge CWD denseness for woods where destructive sampling has non been attempted.
A 3rd of the C pool in forest ecosystems is in neotropical woods ( Dixon et al. 1994 ) . However, coarse woody dust ( CWD ) , one of the cardinal constituents of this pool ( Harmon et al. 1986 ) , is still ill understood ( Clark et al. 2002 ; Keller et Al. 2004 ; Palace et Al. 2007 ) . Published surveies demonstrate that stocks of CWD ( necromass ) can account for 6 to 25 % of entire aboveground life and dead vegetive mass ( Delaney et al. 1998 ; Clark et Al. 2002 ; Nascimento and Laurance 2002 ) , and up to 25 % of the aboveground C content ( Rice et al. 2004 ) . However, most plot-based estimations of C balance typically focus merely on the life aboveground biomass ( e.g. , Phillips et Al. 1998 ; Baker et Al. 2004b ) .
This survey aims to lend to the long-run end of bettering estimations of the C stocks and balances of lowland Amazonian woods. In peculiar, in western Amazonia few elaborate surveies of forest C pool have been conducted. Western Amazonia histories for one one-fourth of the entire 6 M km2 Amazonian rain forest, if defined cautiously as the Amazon basin woods of Colombia, Ecuador, Peru, Bolivia, and Acre ( Brazil ) ( informations adapted from FAO 2000 ) . It is besides likely to include 20 Pg C for aboveground unrecorded woody biomass ( Malhi et al. 2006 ) . To our cognition, in the humid lowland woods of this part, there is merely one survey of necromass ( southern Peru, Baker et Al. in imperativeness ) and one of CWD volume ( Ecuador, Gale 2000 ) . Here, we report for the first clip for northwesterly Amazonian values for CWD denseness and stocks.
In contrast to well-established protocols for mensurating CWD volume such as line-intersect sampling ( Warren and Olsen 1964 ; new wave Wagner 1968 ) , there is no standard protocol for trying the denseness of CWD. For illustration, Gerwing ( 2002 ) assumed that the densenesss of integral, partly decayed, and rotten logs are 100, 88, and 60 % that of life trees severally, whereas Brown et Al. ( 1995 ) used a random sample of 20 pieces of CWD. Most humid, lowland neotropical surveies use a subjective categorization of the grade of CWD decay ( e.g. , Kauffman et al. 1988 ; Keller et Al. 2004 ) , with two to six categories, depending on research workers ‘ definitions, and the denseness of each category is calibrated by direct denseness measuring of sub-samples ( Kauffman et al. 1988 ; Delaney et Al. 1998 ; Clark et Al. 2002 ; Keller et Al. 2004 ) . In entire, there are merely five other CWD denseness surveies that use a direct sampling method to bring forth at least three decay categories, none of which is located in northwesterly Amazonia ( , ( a ) ) . Besides, direct sampling is a destructive method which is non suited for some protected militias. An indirect, non-destructive method is needed, to let rapid appraisal of CWD stocks from measurings of CWD volume, and particularly for some parts where at present merely measurings of CWD volume are available ( e.g. , Gale 2000 ) .
We conducted an probe of CWD densenesss and stocks in three forest types at Jenaro Herrera in Amazonian Peru. The line-intersect ( besides known as line-intercept ) method ( Warren and Olsen 1964 ; new wave Wagner 1968 ) was applied to try CWD pieces for denseness and necromass measurings in this landscape. Extra plot-based ( Harmon and Sexton 1996 ) measurings were made to mensurate the measures of both standing and fallen CWD, and besides to compare straight the C pools in CWD and populating trees in the same country.
Specifically, we ask: ( 1 ) What are the wood densenesss and stocks of CWD in the northwesterly Amazonia? ( 2 ) Are at that place differences in the wood densenesss and stocks of CWD between forest types in this part? ( 3 ) Is there a form of CWD denseness across Amazonia?
The field work was undertaken in northern Peru at the Centro de Investigaciones de Jenaro Herrera ( 400 55? S, 730 44? W ) , located 200 km upstream of Iquitos, and administered by the Peruvian Institute for Amazonian Research ( IIAP ) ( ( B ) ) . Annual rainfall in this landscape ranges from 2500 to 2700 millimeter, with average monthly precipitation from 140 to 309 millimeter, and average one-year temperature between 26 and 27 0C ( Spichiger et al. 1996 ; Kvist and Nebel 2001 ) . CWD densenesss and stocks were studied in one seasonally-flooded and two unflooded lowland woods. The unflooded woods are located on clay-rich and white sand dirts, and the flood plain wood is located in high restinga forest, which on norm is inundated for one month per twelvemonth ( Kvist and Nebel 2001 ) . The trying country surrounded four permanent secret plans which were established in the different wood types. In the unflooded wood, two 1-ha secret plans, established by the RAINFOR undertaking ( hypertext transfer protocol: //www.geog.leeds.ac.uk/projects/rainfor/index.html ) , were indiscriminately located in mature wood on two different dirt types: clay-rich ( RAINFOR codification: JEN-11 ) and white sand dirt ( JEN-12 ) . Every populating single tree ? 10 centimeter in diameter in the secret plans was measured, tagged and identified in March 2005 and later recensused in April 2006. In the seasonally flooded forest, two 1-ha secret plans were established in 1993 by Nebel et Al. ( 2001b ) ( Plot 2 and Plot 3, coded JEN-02 and JEN-03, severally ) .
Line-intersect based CWD measurings
We located two to four transects utilizing the line-intersect method ( van Wagner 1968 ) in March 2005 in the three types of woods. Each transect was started at least 10 m or more off from the corner of each lasting secret plan to avoid possible anthropogenetic impacts, and was oriented in analogue to the two perpendicular boundary line waies of each secret plan in order to cut down any consequence of orientation prejudice ( Bell et al. 1996 ) . These transects were 160 to 400 m in length depending on the spot size of the selected forest type. When the selected angle was non suited for transect apparatus ( e.g. , the line would traverse a watercourse, trail, or enter a different wood type ) , the transect line orientation was shifted by 20 grades if possible. When a trail could non be avoided, the transect stopped 20 m before and started 20 m after, go oning in the same way. In entire, we inventoried 800 m of transect in the wood on clay-rich dirts, 610 m in white sand wood, and 470 m in flood plain wood, meeting a sum of 249 fallen CWD.
CWD is defined as all dead woody stuff, including lianas and thenar trees, with diameter ? 10 centimeter. For every piece of CWD we measured diameter, recorded decay category ( see subdivision: Density of CWD ) , and sampled portion of the log for farther denseness standardization. All CWD diameter measurings from the transects were used to gauge entire CWD volume and necromass in each wood, except for informations from the short ( 50 m ) transect in the white sand wood. The CWD volume was calculated as:
where V is the CWD volume per unit country, Di is the diameter ( centimeter ) of log I and L ( m ) is the length of the transect line ( new wave Wagner 1968 ) . The discrepancy of the volume ( ?2 ) for n transects was weighted by transect lengths ( Lj ) , as recommended by De Vries ( 1986, p. 256, cited in Keller et Al. 2004 ) :
Density of CWD
Density samples were taken from the pieces of CWD intersected by the transect lines, and four standing dead short pantss next to the transects. If a tree was intersected more than one time by a sampling line, merely one subdivision from the tree was sampled. Sampling methods depended on softness of logs. For difficult pieces, a concatenation proverb was used to cut a cylindrical radial subdivision, and rectangular or cylinder solid wood stoppers were taken from each radial subdivision by a matchet. Power drill trying methods ( Keller et al. 2004 ) were non suited in this part because most samples disintegrated before extraction, which could be due to comparatively soft wood in western Amazonia ( Baker et Al. 2004 ) . Samples were removed indiscriminately in one of the three radii through a plane perpendicular to the land ( upper vertical, 0 & A ; deg ; ; middle horizontal, 90 & A ; deg ; /270 & A ; deg ; ; lower vertical, 180 & A ; deg ; ) , and at 5 centimeter intervals outwards from the Centre of each wood subdivision.
For to a great extent decayed pieces, we collected a part of the stuff by make fulling a known-volume ( 7 cm3 ) clear plastic cylinder ( n = 68 ) . The contents of each cylinder were removed to a known-weight envelope to allow measuring of dry weight in the research lab. In some instances, the stuff was excessively delicate to pull out a coherent rectangular form by matchet, but excessively solid to utilize the plastic cylinder method. Here, irregular shaped wood samples were taken. Where the decay categories of bark and duramen were different, both parts were sampled. Digital exposure were taken for each woody radial subdivision with a swayer in order to cipher null infinite proportion for the log.
Fresh volumes were determined by callipers in three length dimensions ( l1, l2 and l3 ) for a rectangular solid form, or radius ( R ) and length ( cubic decimeter ) for a cylindrical sample. Volumes of irregular form samples were determined by H2O supplanting measuring inside a calibrated plastic cylinder to the nearest 0.5 millimeter. All samples ( n = 381, from 252 sampled trees ) were so oven dried at 60 & A ; deg ; C. Dry weight was measured utilizing a Oertling HB 63 2/3 db balance. Density was calculated as oven dry weight divided by fresh volume ( Fearnside 1997 ) .
‘Original denseness ‘ was calculated by averaging the denseness samples within each log, and so averaging these densenesss within the same decay category. Null infinite in a wood subdivision can impact CWD volume and hence denseness computations. In our survey, we defined null infinite as hollows surrounded wholly by solid wood and was determined by numbering digital pels of field exposures utilizing ImageJ ( hypertext transfer protocol: //rsb.info.nih.gov/ij/ ) . ‘Revised denseness ‘ values were so calculated by seting the original denseness values by mean per centum of null infinite in each decay category. Except where specified, ‘density ‘ of CWD in this paper indicates the ‘revised denseness ‘ .
Decay categories of CWD were originally categorized into five categories, following Keller et Al. ( 2004 ) . Class 1 stuff was late fallen with more than 75 % of the wood integral and difficult, and sometimes still with all right branchlets attached. Class 1.5 stuff was solid wood with somewhat damaged bark. Material in category 2 was damaged, the log had experienced some decay, between the decay grade of category 1.5 and 2.5, and was besides applied to pieces of wood where the bark had gone but the duramen remained solid. Class 2.5 was applied to slightly rotten stuff, with portion of the wood crumbly and easy interrupt when kicked. Class 3 stuff was at least 75 % soft and rotten, which a matchet blade could come in easy, and which collapsed when stepped on. Where province of decay of the bark and duramen were really different, decay category of the log was attributed individually and treated as separate samples. To ease comparing within our landscape and with published surveies, we besides recomputed the ‘five decay category ‘ consequences into three major decay categories, by uniting category 1.5 with category 1, and category 2.5 with category 3.
As the sample size in ‘decay category one ‘ ( n = 1 ) of the original ‘five decay category ‘ categorization design was deficient, average stand-level life wood denseness values were applied for this category. Populating wood denseness norms were estimated on a radical country, instead than per-stem footing, because big trees are likely to disproportionately lend to measures of CWD, as tree size correlatives with biomass ( Chambers et Al. 2001 ) and decomposition rate ( Chambers et Al. 2000 ) . There was no such sample size job in the ‘three decay category ‘ categorization, so our existent measurings were used.
Average life wood denseness ( ?BA ) , weighted by radical country, was estimated utilizing the floristic composing of nearby lasting secret plans informations ( Nebel et al. 2001b ; Peacock et Al. in imperativeness ) and a species wood denseness database ( Baker et Al. 2004a ; Chave et Al. 2006 ; Lopez-Gonzalez et Al. 2006 ) ( ) . Wood denseness informations were matched to the secret plan informations on a tree-by-tree footing. In instances where no species wood denseness was available, the norm for the genus ( 24 % of 12 025 persons ) , or household ( 4 % ) was used. For unidentified trees, or persons in households missing wood denseness informations, the mean wood denseness of the available species in the secret plan, on a stems footing, was used ( 1 % ) .
Plot-based CWD measurings
We besides quantified CWD volume in March 2005 utilizing the plot-based method ( Harmon and Sexton 1996 ) within the two unflooded lasting secret plans. We recorded diameter, length, and decay category ( see subdivision Density of CWD ) of every CWD, whether standing or prone, in the whole clay-rich secret plan ( 1 hour angle ) and half of the white sand secret plan ( 0.5 hour angle ) . For fallen CWD, diameters at both terminals were estimated by two perpendicular waies to the nearest centimeter. Where accessible due to excavating, the thickness of bark was recorded and used to set the volume of CWD. For ‘standing ‘ stumps the diameters of smaller terminals and the length ( tallness ) were estimated. For logs tapering to less so 10 centimeter diameter, measurings were merely made up to the point of 10 centimeter diameter. For braced short pantss, diameters were taken above the buttresses.
The volume of each CWD piece by the plot-based method was calculated utilizing Smalian ‘s expression ( Phillip 1994 ) :
where LCWD ( m ) is the length of the CWD piece, and D is the geometric mean of bole diameter measurings ( m ) at either terminal 1 or 2. For CWD with bark thickness measurings, volumes were calculated by deducting the interior volume from the outer volume.
Stockss of CWD and biomass
Stockss of CWD are termed as necromass. Necromass ( N ) in each decay category K was calculated as the merchandise of the volume ( Vk, by either the plot-based or intersect-based method ) and the denseness ( ?k ) for all stuff in that category in each wood type.
The sampling mistake ( EN ) of necromass Nk ( k = 1 to 3 ) by the line-intersect method was calculated as:
where and EV represent the mistakes in denseness ( ?k ) and volume ( Vk ) , severally. This is a conservative attack which accounts for the possible interaction between mistakes in CWD denseness and volume ( Taylor 1997 ) . The entire mistake in the necromass was estimated by summing the component mistakes in each decay category.
AGBcoarse ( Mg ) is defined as aboveground populating short pantss or subdivisions ? 10 centimeter in diameter within secret plans. It is estimated by multiplying aboveground biomass ( AGB, kilogram ) by a harsh wood rectification factor of 0.85 ( Higuchi, unpublished information, cited in Chambers et Al. 2000 ) .
[ ] AGBcoarse = AGB – 0.85 / 1000
Estimates of AGB of the two unflooded woods ( clay-rich and white sand secret plans ) were derived from two different allometric theoretical accounts. The first is based on a one-site neotropical survey, developed from trees larger than 5 centimeter in diameter at 1.3 m or above the buttresses ( n = 315, near Manaus, Brazil, Chambers et Al. 2001 ) . We adjusted the equation utilizing species-level wood denseness values following Baker et Al. ( 2004a ) .
where ?i ( g cm-3 ) is the species-level wood denseness of each person I, and Di ( centimeter ) is the diameter at 1.3 m of the same tree.
The 2nd theoretical account is a multi-site pan-tropical ‘moist wood ‘ ( n = 15 ) survey, included all available biomass measurings of trees larger than 5 centimeter ( Chave et Al. 2005 ) .
AGB of the flood plain wood was estimated as the norm of biomass consequences reported by Malhi et Al. ( 2006 ) for JEN-02 and JEN-03. In Malhi et Al. ( 2006 ) , biomass was calculated utilizing known secret plan basal country and structural transition factors. The structural transition factors were interpolated utilizing distance-weighted kriging and soil-type leaden methods.
Density of CWD
Revised CWD densenesss showed important differences among decay categories and forest types ( ) , both for the five category categorization ( ln-transformed, bipartisan ANOVA, decay category, F3, 239 = 15.212, P ? 0.001 ; forest type, F2, 239 = 5.883, P = 0.003 ; no interaction, P = 0.109 ) and the three category categorization ( decay category, F2, 243 = 19.754, P ? 0.001 ; forest type, F2, 243 = 7.624, P ? 0.001 ; no interaction, P = 0.063 ) . Density declined monotonically with increasing degrees of decay ( ) . However, the densenesss of decay category 1 and 2 in the flood plain forest were similar which is due to the low CWD stocks and hence little sample size in decay category 1. Densities of CWD were identical between woods on clay-rich dirt and on the white sand, but both were significantly higher than densenesss of the flood plain forest ( ) .
More than one fifth ( 21.3 % ) of the sampled pieces had a null infinite in the wood, but the null country agencies were merely 3 to 4 % in each decay category ( ) . There were no important effects of diameter size category ( category 1: 10 ~ 20 centimeter, category 2: 20 ~ 40 centimeter, and category 3: ? 40 centimeter ) on CWD densenesss among the decay categories ( ln-transformed CWD densenesss, bipartisan ANOVA, diameter category, F2, 239 = 0.240, P = 0.787 for the five categories ; F2, 243 = 0.224, P = 0.800 for the three categories ) . Furthermore, the denseness of fallen wood was non affected by either radial place ( Kruskal-Wallis trial, P = 0.995 ) , or by the distance from Centre ( additive arrested development, difference in denseness with the piece in the cardinal of the same log against its distance from the Centre, r2 = 0.001, P = 0.723 ) .
Because the three category categorization method revealed comparable forms to the five category categorization and is less susceptible to possible jobs of little sample sizes, afterlife we merely report consequences from the three category categorization.
Stockss of CWD
Necromass besides varied between forest types and decay categories by the line-intersect method appraisal ( bipartisan ANOVA, forest type, F2, 15 = 11.318, P ? 0.001 ; decay category, F2, 15 = 13.155, P ? 0.001 ; no interaction, P = 0.423 ) . Based on the line-intersect method, there was no noticeable difference in necromass between woods on clay-rich dirts ( 30.9 Mg ha-1 ) and white sand ( 45.8 Mg ha-1 ) , but necromass was significantly lower in the flood plain wood ( 10.2 Mg ha-1 ) ( ) . Besides, necromass in decay category 2 was significantly greater than in categories 1 and 3 ( ) .
By the plot-based methods, the measure of entire necromass, including both fallen and standing CWD was 20.3 Mg ha-1 in the clay-rich wood, and 41.1 Mg ha-1 in the white sand wood ( ) . Necromass of standing CWD accounted for 29 to 32 % of entire necromass. In other words, the necromass of standing CWD was about half as much ( 41?47 % ) as the necromass of fallen CWD. The measures of fallen necromass measured by the plot-based method were by and large lower than those measured by the line-intersect method.
As standing CWD was non measured in the flood plain, we applied the mean proportion of standing CWD ( 44 % ) , derived from the unflooded woods, as a preliminary estimation of entire CWD in the flood plain wood. As a proportion of AGBcoarse in the three woods, CWD contributes proportionately most in the white sand wood ( 17.8?18.2 % ) , followed by the clay-rich wood ( 7.8?8.0 % ) , and least in the flood plain wood ( 6.8?6.9 % , ) . As a proportion of entire aboveground vegetive mass, CWD contributes 15.1?15.4 % in the white sand wood, 7.2?7.4 % in the clay-rich wood, and 6.4?6.5 % in the flood plain forest ( ) .
Stockss of CWD
CWD stocks were lowest in the flood plain wood and greatest in the white sand wood, even when the flood plain forest value was corrected for standing CWD ( ) . Baker et Al. ( in imperativeness ) reviewed other neotropical rain forest surveies and showed that CWD stocks range from 96.1 Mg ha-1 on a nutrient-poor oxisol forest, Brazil ( Rice et al. 2004 ) to merely 2.5 Mg ha-1 on a spodosol ( white sand ) forest, Venezuela ( Kauffman et al. 1988 ) . Our flood plain wood is located toward the lower terminal, whereas the unflooded woods, on clay-rich and white sand dirts, are in the center of this scope. The wide scope of CWD reported for the neotropical woods implies big local and regional fluctuations in perturbation history, decomposition rates, and/or input rates ( i.e. , mortality and subdivision autumn ) , and may besides be affected by differences in trying methods used by research workers.
The low stocks of CWD in the flood plain wood likely consequence from deluging transit and higher decomposition rates. A plot-based survey in a white-water flood plain wood ( 5 & A ; aacute ; rzea ) in Brazil showed that deluging redistributed CWD from higher to lower woods, and that the rhythm of wetting and drying enhanced the rate of decomposition ( Martius 1997 ) . In that survey, dead wood was comparatively undistinguished ( 2.7 % of the life wood mass ) , an even lower proportion than we found. Low necromass in our survey is besides driven by low CWD denseness in this wood type ( ) , as necromass is a merchandise of the volume and denseness of CWD.
Measures of CWD were non significantly different between the two unflooded woods, but CWD represented a higher proportion of AGBcoarse in the white sand than in the clay-rich wood. This phenomenon could be explained by either higher rates of CWD input, or lower decomposition rates of CWD in the white sand wood. Although we lack decomposition experiments, our short-run nose count consequences provide preliminary estimations of the CWD kineticss in this part. Mortality inputs ( Mg ha-1 yr-1 ) were calculated for trees deceasing between 2005 and 2006 by summing their AGBcoarse at the first nose count and dividing by the nose count interval. Inputs for the clay-rich wood scope from 4.5 to 4.6 ( Mg ha-1 yr-1, based on the Chave and the Chambers theoretical accounts, severally ) . Estimated mortality inputs of the white sand forest were much lower, runing from 0.5 to 0.6 ( Mg ha-1 yr-1 ) . As a consequence these informations do non back up the suggestion that CWD inputs are higher in white sand wood. If CWD stocks are assumed to be at steady province, the estimated decomposition rate ( yr-1 ) equals the mortality input ( Mg ha-1 yr-1 ) divided by CWD stocks ( Mg ha-1 ) . Under this premise, estimated decomposition rates are 0.22 yr-1 in the clay-rich wood and 0.01 yr-1 in the white sand wood. Our estimated decay rates are comparable ( but in the white sand secret plan is somewhat lower ) to a cardinal Amazon survey which showed that the decomposition rate of dead trees ranged from 0.015 to 0.67 yr-1 with an mean ± SE of 0.19 ± 0.03 yr-1 ( Chambers et al. 2000 ) . Low decomposition rates in our white sand wood are a plausible account for the comparatively high CWD stocks in this wood type. However, longer term observations, including mortality inputs, direct measurings of decomposition rates, deluging perturbation effects, and fluctuation in standing CWD stock are needed to better construe the necromass balance of this landscape.
Density of CWD
Null infinite was non an of import characteristic of CWD in this survey. By contrast, a survey in eastern Brazilian Amazonia reported that the null country of CWD ranged from 2 to 21 % ( Keller et al. 2004 ) and Fearnside ( 1997 ) suggested that approximately 20 to 30 % of life trees ( ? 10 centimeter diameter ) in Brazil have a hollow infinite in the Centre. One ground for this deficiency of null infinite phenomenon in NW Amazonia could be due to the smaller mean tree size ( Malhi et al. 2002 ) , and faster turnover rates and attendant shorter life-spans ( Phillips et al. 2004 ) in this part. Therefore, trees in western Amazonia may merely non turn big plenty or populate long plenty to develop null infinite. Difference in hollow infinite proportions across Amazonia could therefore affect both biomass and necromass estimations. Surveies based on allometric equations from eastern Amazonian, where the proportion of hollow subdivision is larger, could undervalue the biomass of trees in these northwesterly Amazonian woods. Consequently, the biomass consequences in our survey should be treated as lower edge estimations.
Our survey shows that within a comparatively little country wood may differ markedly in CWD denseness. A plausible account is the typical floristic composing of flood plain woods ( Terborgh and Andresen 1998 ; ter Steege et Al. 2000 ) . At Jenaro Herrera, the dominant households in the flood plain forest are Moraceae, Fabaceae, and Arecaceae ( Nebel et al. 2001a ) with average wood denseness 0.60, 0.73, and 0.43 g cm-3, severally ( Lopez-Gonzalez et Al. 2006 ) . In the nearby clay-rich wood the dominant households are Fabaceae ( 0.73 g cm-3 ) , Lecythidaceae ( 0.63 ) , and Sapotaceae ( 0.75 ) ( Lopez-Gonzalez et Al. 2006 ; Peacock et Al. in imperativeness ) . In the white sand wood, the dominant households besides differ, including Fabaceae ( 0.73 ) , Clusiaceae ( 0.66 ) and Euphorbiaceae ( 0.61 ) ( Lopez-Gonzalez et Al. 2006 ; Peacock et Al. in imperativeness ) . As wood denseness is a phylogenetically conserved trait ( Baker et Al. 2004a ) and the flood plain wood is composed of households with comparatively low wood denseness, fluctuation in floristic composing may explicate the landscape-scale life and hence CWD denseness differences.
However, the inquiry remains, why should denseness of life trees be lower in flood plain wood? Soil birthrate gradients may impact stand flat wood denseness values. For illustration, higher birthrate may favor low wood denseness species that grow fast, whereas low dirt birthrate slows tree growing and favor high wood denseness, longer-lived species ( Muller-Landau 2004 ) . Pan-Amazonian terra firma ( unflooded ) forest research shows that wood denseness is typically lower on the more fertile dirts in western Amazonia than on the less fertile dirts in cardinal and eastern Amazonia ( Baker et Al. 2004a ) . At Jenaro Herrera, the flood plain forest grows on a fertile dirt ( concentration of cations ( ECEC ) = 20.9 cmol+/kg in skyline A, Nebel et Al. 2001b ) while the clay-rich ( oxisols, Spichiger et Al. 1996 ) and the white sand woods ( ECEC = 1.84 cmol+/kg in skyline A, unpublished RAINFOR information ) are located on much poorer dirts. Together, the poorer dirt birthrate and hence higher life wood denseness could explicate why CWD densenesss were higher in the unflooded woods.
CWD and populating tree denseness in the neotropics
To research how of import life wood denseness may be in finding CWD denseness, we constructed arrested development theoretical accounts for humid, lowland, neotropical woods from available informations ( , except for Juruena, Mato Grosso, Brazil where populating wood denseness informations was non available ) . We found important relationships between wood densenesss of life trees ( ?BA, weighted by radical country ) and CWD, both in decay category one ( ?k=1, r2 = 0.661, P = 0.026 ) and two ( ?k=2, r2 = 0.860, P = 0.003 ) , but non for decay category three ( p = 0.324 ) ( ) . The equations are as follows.
[ ] ?k=1 = 1.17 – ?BA – 0.21 and
[ ] ?k=2 = 1.17 – ?BA – 0.31
where ?BA ( g cm-3 ) is the average wood denseness of life trees weighted by radical country in the same country, and ?k=1 and ?k=2 ( g cm-3 ) represent the CWD densenesss in decay category one and two, severally. For the CWD denseness in decay category three, we suggest using the mean 0.29 g cm-3 ( ± 0.04, SE ) for all humid, lowland neotropical woods. On norm, CWD denseness in decay category one is 82 ± 6 % of ?BA, decay category 2 is 66 ± 4 % of ?BA, and decay category 3 is 46 ± 6 % of ?BA. However, as shows, plot-average densenesss ( ?BA ) between 0.57 and 0.66 g cm-3 are ill represented in available neotropical surveies. Probes of the relationships within this scope are needed to derive a better apprehension of the overall relationships.
Measurement of CWD denseness
Although decay categories of CWD are classified subjectively, the direct mensural densenesss correlated good with that of unrecorded trees which suggests cross-site comparing between categories is executable. How many denseness categories are needed to accurately gauge necromass? Based on our consequences, the three category categorization has similar forms to the five category categorization method and is less susceptible to try size jobs. When utilizing the five category categorization, the fallen necromass was estimated as 31.5 ± 6.6 Mg ha-1 in the clay-rich wood, 45.3 ± 13.2 in the white sand wood, and 10.7 ± 6.1 in the flood plain forest. All of these values are within the standard mistake ranges of the consequences utilizing the three category categorization. Therefore, we believe that the three category categorization is sufficient for necromass appraisal.
Careful scrutiny of decay category in dead wood is besides of import. For illustration, the densenesss of the integral and partly decayed CWD are identical in the Venezuelan secret plans ( Delaney et al. 1998 ) ( ) . Delaney et Al. ( 1998 ) suggest that this form is because logs classified as partly decayed to rotten still had comparatively sound duramen or sapwood. Therefore, when the decay categories of duramen and sapwood are different, we recommend entering them individually.
The densenesss in fallen CWD in our survey did non vary significantly with radial places and distance from Centre. Keller et Al. ( 2004 ) found that CWD denseness was significantly higher on the upper compared to the lower portion of the log, and declined with distance from the log Centre. These forms are likely due to microbe handiness and activity which vary within a log depending on wet content and the substrate ( Harmon et al. 1986 ) . Our ‘insignificant ‘ consequences may be caused by a mixture of species-specific decomposition mechanisms. For illustration, the Centre of thenar boles decomposes quicker than its exterior parts, whereas the sapwood of many dicotyledonous species appears to break up faster than duramen. A chronosequence survey of wood decomposition in boreal woods of Russia ( Yatskov et al. 2003 ) suggests there are four types of CWD denseness decay forms. ( 1 ) Linear diminishing with decay categories. ( 2 ) No denseness alteration until late decay phases due to decay-resistant duramen. ( 3 ) Fast decreasing in denseness at early decay phases but a levelling off due to a high sapwood-to-heartwood ratio or intermediate decay immune duramen. ( 4 ) Complex decomposition processes continuing at the same time from both the exterior and indoors due to bosom putrefaction. Therefore, in order to analyze the effects of radial place and distance to the Centre, a better method would be to try the same logs of known species at different radial places and distances from the Centre, instead than comparing these effects utilizing different logs from unknown species.
Both denseness and stocks of CWD vary between forest types within a northwesterly Amazonian landscape. The CWD denseness and stock of the flood plain wood in this survey are comparatively low, whereas the unflooded sites are more typical of other neotropical surveies. Low CWD denseness and necromass in the flood plain forest were perchance due to the typical floristic composing and hence low life wood denseness, and the implosion therapy perturbation government. In comparing, both CWD denseness and necromass were identical between the two unflooded woods. However, based on the higher measure of CWD as a proportion of the life, aboveground biomass, and utilizing short-run nose count informations, we suggest that the decomposition rate is lower in the white sand secret plan than in the clay-rich wood. Longer term observations are needed to better construe the necromass balance of this landscape. In a broader context of humid, lowland neotropical woods, CWD densities in decay category one and two were significantly correlated with the wood denseness of the life wood. Therefore, differences in floristic composing appear to supply a partial, by and large applicable, account for the fluctuation in CWD denseness. Besides, for countries where destructive measurings are unavailable or non possible, the direct sampling method of CWD denseness may be replaced by estimations based on life wood denseness.
We thank Eur & A ; iacute ; die Honorio, Julio Pacaya, and other helpers for their of import aid in the field work, Michael Keller for his methodological suggestions, and Julie Peacock for database aid. We besides acknowledge Instituto de Investigaciones de la Amazon & A ; iacute ; a Peruana ( IIAP ) for permission to entree their installations. This research is portion of the PhD survey of Kuo-Jung Chao, supported by the Overseas Research Students Award ( Universities UK ) , the School of Geography and the University of Leeds. Field work was funded through a Natural Environment Research Council ( NERC ) criterion grant to Oliver Phillips.
Table. Densities ( mean ± SE, g cm-3 ) of life and coarse woody dust ( CWD, diameter ? 10 centimeter ) in humid, lowland neotropical woods ( rainfall ? 2000 mm yr-1 ) . Populating wood denseness ( ?BA ) is the plot-average of life trees, weighted by radical country. CWD densenesss ( ?k ) are classified into three decay categories ( K ) , including integral ( k=1 ) , partly decayed ( k=2 ) , and rotten ( k=3 ) .
Table. Densities ( mean ± SE, g cm-3 ) of CWD in three forest types in Jenaro Herrera, northern Peru.
Table. Necromass ( mean ± SE, Mg ha-1 ) of fallen CWD in three forest types in Jenaro Herrera, northern Peru, based on the line-intersect method.
Table. Necromass ( Mg ha-1 ) of both standing and fallen CWD in two unflooded woods in Jenaro Herrera, northern Peru, based on the plot-based method.
Table. Biomass ( Mg ha-1 ) and necromass ( Mg ha-1, both standing and fallen ) in three forest types in Jenaro Herrera, northern Peru.