Hindawi Publishing Corporation
International Journal of Forestry Research
Volume 2014, Article ID 607372, 6 pages
http://dx.doi.org/10.1155/2014/607372
Research Article
Forest Biomass, Carbon Stocks, and Macrofungal Dynamics:
A Case Study in Costa Rica
Carlos Rojas1,2 and Erick Calvo1
1 Engineering Research Institute, University of Costa Rica, 11501 San Pedro de Montes de Oca, Costa Rica
2Department of Biosystems Engineering, University of Costa Rica, 11501 San Pedro de Montes de Oca, Costa Rica
Correspondence should be addressed to Carlos Rojas; rojas carlos@outlook.com
Received 18 December 2013; Revised 17 February 2014; Accepted 17 February 2014; Published 20 March 2014
Academic Editor: Piermaria Corona
Copyright © 2014 C. Rojas and E. Calvo. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
There are few published studies providing information about macrofungal biology in a context of forest dynamics in tropical areas.
For this study, a characterization of above-ground standing tree biomass and carbon stocks was performed for four different forest
subtypes within two life zones in Costa Rica. Fungal productivity and reproductive success were estimated and analyzed in the
context of the forest systems studied and results showed fungal dynamics to be a complex and challenging topic. In the present
study, fungal productivity was higher in forest patches with more tree density but independent from life zones, whereas fungal
biomass was higher in premontane areas with ectomycorrhizal dominant trees. Even though some observed patterns could be
explained in terms of climatic differences and biotic relationships, the high fungal productivity observed in dry forests was an
interesting finding and represents a topic for further studies.
1. Introduction endophytism, lichenization, and mycorrhization have been
used to generate functional data on tropical fungi (e.g., [4]).
Macroscopic fungi within the group of the Basidiomycota However, an integration with forest ecology research is weak,
stand out among human groups for their aesthetic beauty and and thus the information generated has been useful for trop-
role in sociocultural paradigms [1]. Ironically, the fungi are ical fungal biologists but not necessarily for forest ecologists.
one of the biological groups for which limited scientific data For instance, in the case of mycorrhizal research, most of the
in relation to ecosystem dynamics are available (e.g., [2]), and efforts on tropical areas have focused on the applied aspects
thus popular beliefs are dramatically based on speculation. of the fungus-plant relationship (e.g., agriculture; see [5]).
In fact, the fungi comprise one of the groups for which This bias has created an information gap between what
fine information on natural history, ecological strategies, is known about the species participating in the relationship
and across-level trophic relationships still accumulates at a and their ecosystem role as a biological unit. Such disparity
slow pace (see [3]). An obvious constraint of the situation is evident in comparative functional studies between nat-
is that the study of modern evolutionary questions of forest ural versus managed forest systems since usually different
functioning, particularly in tropical areas with high levels of approaches are taken to study either one. The problem of
nutrient recycling, develops at an even slower speed. this strategy is that the low number of comparative studies
The paradox of the research on the tree-fungus system on natural systems also translates into a weak database of
in the tropics derives from the fact that even though it is scientific parameters for the evaluation of forest performance
an important component of forest dynamics, there are a in managed scenarios (see [4]). In the context of ecosystem
comparatively small number of local scientists generating restoration and conservation of genetic biodiversity, this is a
data about the different shapes of the relationship. In the critical point that needs to be stressed by researchers involved
past, some interactions such as saprophytism, parasitism, in the decision-making process.
2 International Journal of Forestry Research
The case of Costa Rica is not different to the situation eight plots for the complete study. In Grecia, the two subareas
in most developing tropical countries. Biological research in selected were the Cupressus lusitanica patch (abbreviated
this area has focused on the generation of baseline data at hereafter as G1) and the Quercus-dominated section (G2).
the species level and has not been traditionally integrated In Horizontes, the two subareas were the Samanea saman-
with functional dynamics research. Ironically, during recent Hymenaea courbaril (abbreviated as H1) and the Hymenaea
years the National Biodiversity Institute has estimated that courbaril-Diphysa americana (H2) reforestation treatments.
after the insects, fungal species are the dominant forms in The study plots were georeferenced with a Garmin Nüvi
the country with about 13% of the total potential biodiversity 40, marked with flagging tape, and visited during the dry and
[6]. However, such a level of biological prominence and wet seasons of 2012 and 2013. A HOBO U12-012 datalogger
potential importance in forest dynamics does not match positioned in the middle of each of the eight plots recorded
the development of integrated research lines since only a the temperature (abbreviated as T), atmospheric moisture
handful of local researchers generate information about the (AM), and illuminance (I) for those two years. Datasets from
topic. Even though the situation is not as precarious as in replicated treatments were combined and averaged to obtain
other countries in Central America where the majority of mean values and standard deviations.
functional relationships have not even been studied, it does
reflect the need to generate regional information on the role 2.2. Protocol for Tree Data. In all study plots, diameter at
of interactive biological units in forest dynamics research. breast height (abbreviated hereafter as DBH) was calculated
Within this framework of limited data about functional by using field collected information with a Stanley 34–794
relationships in tropical areas, a weak research focus on the field measuring tape. Canopy height (CH) was calculated
tree-fungus relationship in Costa Rica and a local trend to by measuring the horizontal distance between an arbitrary
generate valuable data on forest dynamics is that the present point and the tree under study as well as the angle between
study has been designed. As such, the primary objective of such horizontal and an imaginary line to the tree crown
the study presented herein is to generate baseline data about with a Leica Disto D5 Laser Range Finder. A trigonometric
the dynamics of the tree-fungus relationship in contrasting calculation provided the height value after corrections for
local environments as a model to study forest management terrain slope and distance between the ground and the
practices and their effect on species and functional diversity. horizontal. Tree volume (TV) was calculated assuming a
tubular shape of the tree trunk and the values for DBH and
2. Material and Methods tree height obtained in previous steps.An estimation of the above ground biomass (AGB) was
This study was carried out between 2011 and 2013 in Costa performed using the data for living standing trees. For this
Rica. The areas selected were the Grecia Forest Reserve calculation, the following adjusted equation from Chou and
(hereafter referred to as Grecia) and the Horizontes Exper- Gutiérrez-Espeleta [7] for Costa Rican tropical forest was
imental Forest Station (referred to as Horizontes). The first used:
area is located in a premontane wet forest zone with a 2/5
mean temperature around 17 C, a precipitation close to 𝐵 = 0.1438 + 0.2051 ⋅ dbh ⋅ 𝛿 − 0.0744 (dap − 50) 𝑥.∘
3500mm rain/year, and amean elevation of 1700m above sea (1)
level.The second area is located within the lowland dry forest In this equation 𝐵 is the biomass in kg, dbh is the diameter
zone with a mean temperature around 26∘C, a precipitation at breast height in cm, 𝛿 is the wood density in g/cm3, dap is
close to 1300mm rain/year, and a mean elevation of 155m diameter at breast height, and 𝑥 is a dichotomic variable that
above sea level. equals 1 when dbh ≥ 50 cm and 0 when dbh < 50 cm. In all
The Grecia Forest Reserve is a 2000-hectare area created cases, the wood density values used were the recommended
with the purpose of protecting water resources and com- ones by the IPCC [8] for the forest types evaluated in the
prised by a mixture of public and private lands. In a 30- present study.
hectare public section called Bosque del Niño, there is a 8- In a similar way, a value of 0.49 for the carbon fraction of
hectare forest patch reforested in 1979 with the introduced aboveground forest biomass was used for the calculation of
Cupressus lusitanica. The rest of that patch is comprised by above ground carbon (AGC) from biomass according to the
a native Quercus-dominated forest. recommendation of the IPCC. For the calculation of CO -
In contrast, theHorizontes Experimental Forest Station is 2equivalent sequestered unit (CO -EU), the values of carbon
a 7000-hectare public area created in 1989with the purpose of 2per tree were multiplied by a factor equal to 3.667, based on
studying the process of reforestation and ecosystem restora- the molecular weight ratio of carbon dioxide to molecular
tion in the dry forest life zone of Costa Rica. In Horizontes, a carbon. The recommended values from the IPCC [8] were
53-hectare section of pasture was planted with a combination also used to calculate the below ground biomass (BGB) in the
of native trees in 1991 and it is today an experimental forest study plots by using the below to above ground biomass ratios
patch used by a series of researchers. known for tropical mountain [9] and tropical dry forests [10]
in the case of Grecia and Horizontes, respectively.
2.1. Study Plots. In each of the study areas, two subareas
representing different forest types were selected and a series 2.3. Protocol for FungalData. In the case of all forest subtypes,
of two 20 × 50m plots was established in them for a total of several planned visits during the rainy season were carried
International Journal of Forestry Research 3
out in order to collect fungal fruiting bodies. For the purpose was evaluated by using the continuous fit option on the
of this project, only macroscopic (larger than 1 cm) fungi distribution analysis subplatform. A posterior goodness of
belonging to the basidiomycete group were considered. In all fit test was used to assess normality. Since data values for
study plots, collections were carried out by two people and most parameters are shown not to be normally distributed,
fruiting bodies were collected up to 50 cm of vertical distance nonparametric statistical analyses were performed in all
from the ground. cases.
Once collected, all fruiting bodies were carefully taken For treatment and/or parameter comparison across forest
to a field station where all morphospecies were separated, subtypes using a continuous variable as a response, the
identified to the genus level, and assigned to either the Kruskal-Wallis test was used by using the ranked-based
saprophyte or the mycorrhizal functional category. Each testing option in the analysis platform of the program used.
fruiting body was then studied separately and both the pileus For comparison ofmeans using a numerical variable between
(gill supporting structure at the apex of stalk) and stalk two treatments, the Wilcoxon test was used in a similar
diameter were measured using a Starret 799 digital caliper. manner to the last approach. For correlation analysis between
With both measurements, an estimation of the hymenial two continuous variables, Spearman’s Rho nonparametric
surface (area where spores are produced) was performed by coefficient was used by using the nonparametric option in the
calculating the result of the pileus area minus the stalk area. multivariate platform. For all analyses, the alpha value used
For these calculations, it was assumed that the shape of both was 0.05.
the pileus and the stalk was circular as it is the case for the
majority of umbrella shaped fungi. In the case of flat wood 3. Results and Discussion
decaying fungi, the hymenial areawas calculated by assuming
rectangular shapes. A total of 568 trees were studied in the eight study plots. Tree
Theweight of each fruiting bodywas alsomeasured in the density was estimated in 490, 275, 1250, and 825 trees per
field with an A&D N29 digital scale and this measurement hectare for the H1, H2, G1, and G2 forest types, respectively.
was considered as the wet weight value. For the calculation It is interesting to note that dry forest subtypes had the lowest
of fungal biomass, dry weights were calculated indirectly by density values and that the Cupressus lusitanica dominated
estimating that about 21% ± 4% of the wet weight values in subtype had the highest one.This is a referent to the difficulty
the forest types studied was due to biomass. Even though of establishing reforestation projects in tropical dry areas (see
the relationship between wet/dry weight is species-specific, a [12]) and to the high value of cypress for timber production
general value was used as a proxy for the fungal communities purposes [13] due to its rapid growth. However, it also shows
studied due to the lack of enough information for some the relative effectivity of the Samanea saman-Hymenaea
genera and the homogeneity of values observed during the courbaril (H1) system to sustain a forest ecosystem.
analysis. Differences were found in canopy height among all study
The latter percentage was obtained after measuring and forest types (𝐻[3, 661] = 192.7, 𝑃 < 0.0001; individual
analyzing the wet to dry weight relationship of a 500 fruiting comparisons 𝑃 < 0.0001 in all cases). In the case of DBH,
body random sample from both study areas that took place differences were found between G1 and the other forest types
in areas adjacent but outside of the study plots. Dry weights (𝐻[3, 567] = 114.9, 𝑃 < 0.0001; comparison G1 and others
were considered the value for biomass after a correlation 𝑃 < 0.0001). A similar pattern to the latter was also found for
analysis showed a high level of consistency in the water loss tree volume (𝐻[3, 567] = 143.96, 𝑃 < 0.0001; comparison
relationship at the mentioned percentage value (𝜌 = 0.81). In G1 and others 𝑃 < 0.0001). Interestingly, the G1 forest
this case, both weight measurements were performed in the type was the area that showed the highest values for canopy
field and the measurement of dry weights took place after a height, DBH and tree volume, whereas the lowest values were
24 h period in which the fruiting bodies were dried out in a recorded in the H2 type (Table 1).
Thermolyne DV35435 oven at 60∘C. As mentioned before, the latter values can be seen as an
With the values for hymenial surface and biomass, the indicator of the success of the cypress subforest in terms of
ratio between these parameters was calculated in order to biomass accumulation. However, it is interesting to analyze
correct the error inherent to one-dimensional biometricmea- the results in the context of the other subforests studied.
surements. The latter ratio, herein referred to as reproductive Nonnative forest patches have lost popularity in Costa Rica
success ratio, was used to analyze the tree-fungus relationship
in the forest types studied since it provides an indication [14] as well as in other places due to the changes in ecosystem
of the resources used in the formation of true reproductive dynamics produced by a rapid introduction of selective forces
organization (hymenium) in relation to the formation of associated to the introduction of species.
reproductive assisting structures (fruiting body itself). Such When forest parameters were analyzed, neither the total
ratio is the equivalent to the “evolutionary effectiveness” value above ground biomass nor the average ground biomass
mentioned by [11], but in this study it was preferred to use the showed any significant differences among forest subtypes.
term reproductive success ratio. Above ground carbon, CO -equivalent sequestered units and2
below ground biomass showed a similar pattern with no
2.4. Analysis. For all basic and relational analyses using differences among forest subtypes when average values were
tree and fungal data, the statistical software JMP, version 10 studied (see Table 2). Results show that at this level, the
(SAS Institute 2012), was used. In all cases, data normality studied forest subtypes seem equivalent.
4 International Journal of Forestry Research
Table 1: Basic parameter values and standard deviations of the forest subtype characterization performed in the present study.
Plot DBH (cm) CH (m) TV (m3) MT (∘C) MAM (%) MI (Lux)
H1 20.7 ± 1.9 7.1 ± 0.2 0.56 ± 0.07 26.6 ± 4.1 75.3 ± 18.6 606.1 ± 1536.8
H2 20.2 ± 1.3 5.6 ± 0.3 0.34 ± 0.09 26.8 ± 4.5 72.0 ± 18.0 770.1 ± 1438.7
G1 29.1 ± 0.6 11.9 ± 0.2 0.98 ± 0.04 16.6 ± 1.7 88.8 ± 12.7 128.4 ± 398.4
G2 21.9 ± 0.7 9.2 ± 0.2 0.63 ± 0.05 16.6 ± 1.9 68.2 ± 27.2 314.3 ± 1259.5
Abbreviations correspond to diameter at breast height (DBH), canopy height (CH), total tree volume (TV), mean temperature (MT), mean atmospheric
moisture (MAM), and mean illuminance (MI).
Table 2: Tree-based estimator average values and standard deviations calculated for the forest subtypes in the present study. All values are
given in megagrams per hectare.
Plot AGB AGC CO2-EU BGB
H1 154.4 ± 13.1 76.6 ± 6.4 277.4 ± 27.5 43.2 ± 3.6
H2 76.4 ± 36.3 35.9 ± 17.7 131.8 ± 65.2 20.5 ± 10.1
G1 470.1 ± 2.8 230.3 ± 1.4 844.5 ± 5.1 90.0 ± 0.5
G2 243.9 ± 63.4 119.5 ± 31.0 438.3 ± 80.5 58.5 ± 15.2
Abbreviations correspond to average ground biomass (AGB), average ground carbon (AGC), carbon dioxide equivalent units (CO2-EU), and average below
ground biomass (BGB).
Similarly, neither of the microclimatic parameters mea- did not show any significant differences (𝐻[3, 7] = 4.6, 𝑃 =
sured showed differences between forest subtypes (𝐻[3, 7] = 0.19).
5.5, 𝑃 = 0.13 for temperature; 𝐻[3, 7] = 3.6, 𝑃 = 0.29 for The morphological parameters measured or calculated
atmospheric moisture; and 𝐻[3, 7] = 5.1, 𝑃 = 0.16 for illu- for fruiting bodies showed strong correlations among them-
minance). However, temperature showed some homogeneity selves (Table 4) but hymenial surface was the variable present
within forest types, whereas both atmospheric moisture in the majority of significant correlations. In this sense, the
and light intensity showed a higher degree of variability total hymenial surface was inversely and strongly correlated
(Table 1). Such result is easily understandable performing with atmospheric moisture (𝜌 = −0.81) and hymenial surface
a combined macro- and microclimatic analysis. However, was significantly larger in mycorrhizal than in saprophytic
what is important in this case is the actual quantification fungi (𝑍 = 9.44, 𝑃 = 0.0001). Both results relate to
of parameters and the implications for forest dynamics and fungal physiology but it is interesting that at higher levels of
integrated performance along with a different taxonomic atmospheric moisture, fruiting bodies within a forest subtype
group such as the fungi. showed a lower cumulative value of hymenial surface. This
In that second part of the study, the most commonly observation should be further evaluated due to the implica-
recorded fungal genera overall were Collybia andMarasmius tion for forest dynamics. In fact, the case ofmycorrhizal fungi
(see Table 3). However, for the G2 forest subtype, the genera should be of particular interest, due to the very particular
Laccaria and Lactarius were the dominant forms. The four cost-benefit balance with tree partners [16].
genera are among the most commonly recorded fungi in Finally, the reproductive success ratio showed amoderate
tropical areas. However, in spite of natural history differences negative correlation with the average biomass present in
among genera, the number of fungal fruiting bodies recorded the forest subtypes studied (𝜌 = −0.45) as well as with
was not significantly different across the different forest DBH values (𝜌 = −0.30). This result seems to indicate
subtypes (𝐻[3, 7] = 6.0, 𝑃 = 0.16). Interestingly, for G2 that functional strategies and resource allocation in fungal
about 47% of the records were mycorrhizal, whereas for H1 fruiting bodiesmay partially depend on forest characteristics.
all of the genera present were saprophytes, but this apparent For instance, it may not be surprising that in our study
differences in guild composition were marginally not seen mycorrhizal fungi, which were present in areas with higher
when the analysis across forest subtypes was performed tree biomass values, showed significantly lower reproductive
(𝐻[3, 7] = 6.8, 𝑃 = 0.07). success ratios ( 2𝑍 = −18.45, 𝑃 = 0.0001; 3.34mm /g for
Such an analysis is an important aspect to consider mycorrhizal versus 8.26mm2/g for saprophytic fungi).
because the enzymatic battery among guilds is not equiva- Mycorrhizal fungi have a constant influx of carbon from
lent [15] and biochemical differences have the potential of trees and thus can allocate more resources in the production
modifying the level in which wood decay, nutrient recycling, of biomass than their saprophytic counterparts. In our study,
and soil biodiversity interactwith trees.The latter observation the average biomass of fruiting bodies was significantly
may be the driver of the fact that fungi present in the G2 higher for mycorrhizal fungi than for saprophytic ones (𝑍 =
forest subtype, mostly mycorrhizal, were the heaviest ones. 18.76, 𝑃 = 0.0001; 0.28 g for saprophytes versus 1.89 for
However, an analysis of total dry weights per forest subtype mycorrhizal fungi), providing anothermeasurement of forest
International Journal of Forestry Research 5
Table 3: Relative percentages of fruiting body incidence by forest Table 4: Spearman’s Rho (𝜌) correlation values for all four variables
subtype and average values for parameters measured across some of calculated after the fungal fruiting bodies were studied in the present
the fungal genera observed in the present study. study.
Genus (fungi) Forest subtype Parameters measured DW PD SD HS
G1 G2 H1 H2 DW PD SD HS RSR DW 1.00 0.83 0.76 0.79
Amanita 0.8 5.5 3.9 0.6 13.8 2.9 PD 1.00 0.64 0.92
Boletus 4.7 8.4 2.9 0.6 8.5 2.4 SD 1.00 0.61
Clitocybe 5.8 6.7 0.7 13.5 3.0 3.4 0.6 9.6 2.8 HS 1.00
Collybia 16.8 6.2 79.7 16.4 0.5 2.0 0.2 3.9 9.5 Abbreviations correspond to average dryweight (DW), pileus diameter (PD),
Coltricia 2.5 1.1 3.0 0.4 8.6 10.1 stalk diameter (SD), and hymenial surface (HS).
Coprinus 2.6 9.6 0.3 2.1 0.2 3.9 13.0
Coriolopsis 0.3 3.7 2.2 2.8 n/a 7.4 3.9 dynamics assessment. For the forest subtypes studied in
Cortinarius 3.6 4.3 2.8 1.0 6.0 3.2 the present investigation, such values represent a valuable
Daedalea 0.9 0.2 2.6 3.0 n/a 3.3 1.9 quantification of parameters for the understanding of the role
Entoloma 0.6 0.3 0.7 2.4 1.0 2.9 4.2 of fungi in tropical forest dynamics.
Fistulina 5.9 27.2 5.1 1.1 35.0 1.2 A more thorough examination of certain aspects doc-
Hexagonia 2.9 4.7 6.8 n/a 34.5 13.4 umented in the present study is necessary in order to
Hydnum 2.0 5.0 3.4 0.8 10.3 2.3 understand in more detail the dynamics and functional
Hygrocybe 4.5 1.1 0.6 1.6 0.5 2.3 4.7 relationships between trees and fungal inhabitants of forest
Inocybe 6.9 0.3 1.0 0.1 1.0 4.5 ecosystems. In spite of the latter, due to the early stage of
Laccaria 2.9 16.7 1.1 1.9 0.3 3.9 5.4 integrated tree-fungus ecological analyses in Costa Rica, we
Lactarius 1.2 15.3 0.2 18.7 5.8 1.2 30.8 2.1 consider the present effort a locally based contribution in the
Leccinum 0.4 11.4 2.7 1.3 5.0 0.4 right direction.
Lentinula 0.3 2.1 3.9 0.3 13.3 6.1
Lentinus 1.1 0.2 1.6 3.6 0.2 11.2 7.7 4. Conclusion
Lenzites 1.3 0.5 3.9 5.1 n/a 8.9 2.7
Lepiota 0.6 0.4 1.8 2.7 0.8 2.4 0.3 5.8 6.9 It is difficult to understand tropical forest dynamics by analyz-
Leucoagaricus 1.2 1.7 1.6 3.2 0.6 1.8 0.3 3.1 4.5 ing only tree data. As an effort to integrate forest performance
Leucocoprinus 1.2 0.2 1.0 0.1 1.3 4.9 values and microbial dynamics, basidiomycete fungi were
Macrolepiota 0.9 0.5 21.2 6.5 1.1 43.4 3.1 selected in the present study. Results from four different
Marasmius 2.0 3.6 8.5 15.4 0.2 1.2 0.1 1.6 9.8 forest subtypes belonging to two different life zones in Costa
Merulius 0.1 0.5 2.6 0.2 0.6 1.1 Rica showed that even though tree biomass accumulation
Mycena 1.4 0.7 1.0 0.2 1.1 0.1 1.1 9.4 may be higher in forest patches dominated by introduced
Oudemansiella 1.3 0.9 0.2 2.4 3.4 0.3 10.9 6.1 species, a parallel biodiversity-based assessment can be useful
Panellus to understand the dynamics within the forest.0.2 2.8 6.5 0.5 3.0 1.1
Paneolus 0.1 2.3 0.6 1.6 0.2 2.1 4.0 For tropical areas of the world, where integrated forest
Panus 2.9 5.5 0.3 2.1 0.5 3.3 15.0 studies are less common than monothematic ones, this typeof investigation is valuable to accumulate data on forest
Phellinus 1.3 0.4 1.4 3.0 3.4 9.9 10.8 interactions with both external and internal evolutionary
Pholiota 0.6 1.5 0.2 1.4 1.9 0.3 3.8 5.1 forces and monitor their performance over time.
Pycnoporus 0.3 14.2 6.2 1.5 9.5 0.8
Pleurotus 2.3 0.9 4.7 0.5 2.2 0.3 5.5 12.2
Pluteus 4.6 1.5 5.1 2.8 3.5 0.6 14.4 4.1 Conflict of Interests
Polyporus 0.7 1.4 8.9 0.3 1.5 0.3 0.7 2.0 The authors declare that there is no conflict of interests
Psatyrella 0.1 0.2 0.4 1.3 0.1 1.4 9.5 regarding the publication of this paper.
Psilocybe 0.2 7.3 4.0 0.7 12.2 1.7
Russula 3.2 8.0 4.4 1.0 16.6 2.8 Acknowledgments
Schizophyllum 1.1 0.5 2.9 0.4 1.2 2.6
Scleroderma 1.2 4.6 5.1 2.3 0.7 4.8 1.5 This study has been funded by University of Costa Rica
Stereum 1.8 0.6 2.2 n/a 6.0 14.3 through Vicerrectoŕıa de Investigación research code 731-B2-
Trametes 15.7 1.5 0.3 0.7 3.0 3.6 n/a 13.3 5.4 222. Gratitude is expressed to the personnel of the Reserva
Tricholoma 8.7 0.1 3.9 4.5 4.3 0.6 19.3 4.9 Forestal Grecia and the Estación Experimental Forestal
Tylopilus 0.4 174.2 12.4 1.8 121.3 0.7 Horizontes for granting permission to work in those areas.
Abbreviations correspond to dry weight (DW), pileus diameter (PD), stalk Appreciation is also extended to Irene Calderón, Stephanie
diameter (SD), hymenial surface (HS), and reproductive success ratio (RSR). Somerville, and Randall Valverde for field support and to
6 International Journal of Forestry Research
the Engineering Research Institute atUniversity of Costa Rica
for logistic help. Finally, appreciation is extended to anony-
mous reviewers that constructively increased the quality of a
previous version of the paper.
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