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A comparison of the wet and dry season DNA-based soil invertebrate community
characteristics in large patches of the bromeliad Bromelia pinguin in a primary forest in
Costa Rica
Katie M. McGeea, William D. Eatonb*
a
School of Environmental and Life Science, Kean Univeristy, 1000 Morris Ave, Union, New Jersey, USA
07083
b
Biology and Health Sciences, Pace University, One Pace Plaza, New York, NY, USA 10038
*E-mail of corresponding author: weaton@pace.edu
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Abstract
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In Costa Rica, the Maquenque National Wildlife Refuge (MNWLR) contains a unique habitat
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gradient ranging from primary old growth forests, grasslands, pastures, to various ages of
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secondary forests. Within these primary old growth forests are extremely dense naturally
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occurring Bromelia pinguin (Bromeliaceae) patches that often grow with densities up to 2
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plants per square meter. A previous study found that anti-fungal activity of this particular
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plant appears to be altering the fungal community in soils adjacent to these plants. No work
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has been previously conducted on the possible effects of this plant community on soil faunal
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communities and if seasonality contributes to changes in soil invertebrate populations along
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a moisture gradient. Thus, a study was conducted to assess the effects of this specialized
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plant community on soil invertebrates with respect to season, and if these changes in soil
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fauna guild structure could prove to be valid candidates as indicators of ecosystem condition
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with changes in precipitation. In addition, a meta-analysis was done to determine how the
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bromeliad-associated soil invertebrate communities differ from those in adjacent primary
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forest soils. Therefore, comparisons were determined from previous primary forest wet
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season metagenomic soil invertebrate community DNA to the current wet season Bromeliad
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metagenomic soil invertebrate community DNA. Roche 454 sequencing was conducted on
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the 650 bp fragment of the cytochrome oxidase subunit I (COI) gene of invertebrates to
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obtain and characterize soil invertebrate community composition. To determine
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relationships among soil faunal guilds across seasons, relative abundance was calculated,
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and used in conjunction with EcoSim niche overlap and co-occurrence values. From the
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Bromeliad seasonal metagenomic soil faunal DNA study, it appears certain invertebrate
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guilds are driven by moisture as indicated by fluctuations in relative abundance of each
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invertebrate guild across seasons in Bromeliad patch soils, as well as indicated by EcoSim
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niche overlap values. In particular, guilds 1, 4, and 5, should warrant further investigation
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as indicators of habitat condition. The meta-analysis showed that a naturally occurring
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modified environment (the Bromeliad patches), can result in differences in relative
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abundance and partitioning of a limited resource between invertebrate guild structure.
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Those guilds associated with microbivorous and complex decomposition activities (i.e. Guilds
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3 and 4), are more abundant Primary forest soils than Bromeliad patch soils and could be
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potentially used for bioindicators of habitat perturbations.
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Key Words: Soil fauna, Bromeliad, Costa Rica, tropical ecology, ecological indicator
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1. Introduction
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Primary old growth forests in Costa Rica’s Northern Zone ecosystems, in particular, the
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Maquenque National Wildlife Refuge (MNWLR), contain extremely dense naturally occurring
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Bromelia pinguin (Bromeliaceae) patches that are often 100 m x 40-50 m in size with
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densities up to 2 plants per square meter (Looby and Eaton 2012). Bromelia pinguin is a
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perennial plant found in Mexico, to South America, to the Caribbean Islands. Growing 1-2 m
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in height, and 2-3 m in diameter, these plants were once used as hedges and living fences
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around Indian Villages (Looby et al. 2012; Hallwachs 1983). Bromelia pinguin also provides
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food and habitat for small mammals as well as invertebrate assemblages. Camacho-
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Hernandez et al., 2002 showed that the methanol extract of the B. pinguin fruit pulp
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possesses antifungal properties against 8/9 strains of Trichophyton and against a
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nematophagus fungus, Paecillomyces variotti (Claviciptaceae). Few ecological studies have
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been conducted on this bromeliad, however recent work by Looby et al (2012) showed that
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the anti-fungal activity of these Bromeliads appears to be altering the fungal community in
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the soils adjacent to these plants. They showed that the fungal abundance and diversity,
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and microbial biomass all were all lower in soil closer to the Bromeliad plants as compared
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to soil from the adjacent primary forest. However, there has been no work previously
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conducted on the possible effects of these plants, either directly or indirectly, on the soil
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invertebrate populations and if seasonal shifts have an affect on these soil fauna
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assemblages, even though there are many well-recognized trophic level interactions
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between fungi and invertebrates (Chapin et al. 2011).
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Scientists are developing and attempting to use indicator methods to characterize ecological
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variations within different habitats to study ecological processes, to assess ecosystem
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quality/health, and to identify the impact of ecosystem restoration and damaging land
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management strategies. Invertebrate assemblages have been used ubiquitously in aquatic
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environmental studies as indicators of environmental condition (e.g., the United States
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Environmental Protection Agency’s Environmental Monitoring and Assessment Program,
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http://www.epa.gov/emap/), however, the applicability of soil invertebrate guild function in
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terrestrial studies pertaining to ecosystem function appears less common, but is gaining in
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popularity (e.g. Bik et al. 2011; Emerson et al. 2011; Hamilton et al. 2009; Meusnier et al.
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2008; Yu et al. 2012; Hattenschwiler and Gasser 2005; Coleman et al. 2004; Decaëns et al.
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2006; Lavelle et al. 2006; McGee and Eaton 2013a). Soil invertebrates play an essential role
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in the recycling of organic matter and have a significant affect on decomposition in soils of
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moist temperate and tropical ecosystems by enhancing primary production directly or
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indirectly for microbial communities, resulting in more efficient C utilization (Cragg and
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Bardgett 2001; Chamberlain et al. 2006; Lavelle et al. 1996; Brussaard 1998; Wang et al.
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2009). More specifically, soil fauna accelerate microbial inoculation to materials and nutrient
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availability through fecal material production rich in substrates and other microbes (Wang et
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al. 2009; Chapin et al. 2011; Lavelle et al 1997; McGee and Eaton 2013a), as well as
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through the fragmentation, transformation, transportation, comminution, and grazing in soil
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environments (Wang et al. 2009; Chapin et al. 2011; Brussaard 1998; McGee and Eaton
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2013a).
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An examination of the invertebrate community structure associated with these Bromeliads
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could show results that parallel studies of the fungal community, as well as how seasonal
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shifts influence the biotic communities in tropical ecosystems, and warrants investigation.
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Thus, a DNA metagenomics study was conducted to determine the invertebrate community
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structure within the Bromeliad plant soils and to identify any differences in these
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invertebrate populations associated with moisture changes that occur moving from the wet
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season to dry season. One of our goals with this seasonality study was to show that
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monitoring this specialized plant community for differences in the invertebrate population
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structure by seasons might show differences along a moisture gradient. This could, then,
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provide possible indicators of a changing climate over time. As well, we were interested in
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determining how these Bromeliad-associated soil invertebrate communities differed from
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those in the adjacent primary forest soils. Therefore, a meta-analysis was conducted to
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compare previous wet season primary forest metagenomics invertebrate DNA data on the
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invertebrate populations (McGee and Eaton 2014) with wet season Bromeliad metagenomics
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invertebrate DNA data. Due to the known decreased fungal communities in these bromeliad
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patches, as shown by Looby et al. (2012), we proposed that the meta-analysis hypothesizes
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that a decrease in certain invertebrate assemblages associated with less complex carbon
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source utilization should be observed. Given that many types of land disturbances affect
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fungal community and invertebrate community structures (Wardle 2002; Wardle et al.
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2004; Blanchart et al. 1993; Giller 1984; Carrillo et al. 2010), we hoped to show that
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differences in the invertebrate community structures between the primary forest soils and
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Bromeliad soils could be used to suggest ecosystem condition.
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2. Materials and Methods
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2.1 Field Location
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The Costa Rican Ministry of Environment and Energy established the San Juan-La-Selva
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Biological Corridor (SJLSBC) in 2001 to connect six protected areas into a single integrated
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biological unit of 1,204,812 ha (http://www.lapaverde.org.cr). This biological corridor
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initiative was developed to protect the Northern Zone ecosystems from further damage of
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3-4 decades of legal and illegal extraction based land management practices (Monge et al.
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2002) in this region. Situated about 15 km south of Nicaragua in the Northeast region of
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Costa Rica, is the core conservation unit, the Maquenque National Wildlife Refuge (MNWLR).
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This portion of the corridor conserves the highest percentage of forest cover most valuable
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for biodiversity (Chassot and Monge 2006; McGee and Eaton 2014; McGee and Eaton 2013)
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and contains a unique habitat gradient ranging from old growth primary forests, grasslands,
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pastures, to various ages of secondary forests. The habitats used for this current study were
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within the MNWLR (10.7151, -84.1697) and located within the private lands of the Laguna
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del Lagarto Lodge. Four 20 m transects were established in a naturally modified
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environment, the Bromeliad patches, which are found within the primary old growth forests.
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Due to the high Bromeliad patch density, 20 m transects were preferred rather than 20 m x
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15 m plots. For a Bromeliad dry season versus Bromeliad wet season soil fauna community
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DNA comparison, sampling occurred in March 2011 for dry season, and July 2011 for wet
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season. In a meta-analysis, previously described primary forest soil fauna sample
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community structure determined by Next Generation Sequence analysis of DNA from the
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wet season of July 2011 (McGee and Eaton 2013a) were compared to the current study
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Bromeliad soil faunal wet season sample community.
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2.2 Biotic Community Analysis
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To characterize the invertebrate community composition in each soil sample, we collected
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four 7 cm x 10 cm cores from each of the 4 subplots per habitat type, at the same location
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where the LiCor readings were taken, using sterile methods. The soil cores were pooled by
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habitat type; thoroughly mixed and then sieved at 8 mm mesh size. The soil community
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DNA was extracted from three 0.3-g replicate samples of pooled soil using the Power Soil
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DNA Isolation Kit (MO BIO Laboratories, Inc., Carlsbad, CA, USA). PCR amplification of
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extracted DNA was performed using the HCO2198 (5'-TAAACTTCAGGGTGACCAAAAAATCA-
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3') and LCO1490 (5'-GGTCAACAAATCATAAAGATATTGG-3') primers and the methods (i.e., 3
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min 94°C; 5x at 30 sec 94°C, 30 sec 45°C, 1 min 72 °C; 35x at 30 sec 94°C, 1 min 51°C,1
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min 72°C; and 10 min at 72°C) originally described by Folmer et al. (1994) to amplify a 650
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bp fragment of the cytochrome oxidase subunit I (COI) gene of invertebrates. The
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concentration and purity (A260/A280 ratio) of the PCR products DNA samples were determined
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using a Nanodrop 2000/2000c (Thermo Fisher Scientific, Waltham, MA). These samples
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were then sent to the Georgia Genomics Facility at the University of Georgia, where they
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conducted library preparation and Roche 454 sequencing development support for this
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project, and delivered the FASTA/QUAL file results to us for analysis. The resulting
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sequences were aligned and grouped into contigs using Laser Gene Genomics Suite, SeqMan
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NGen software (DNASTAR Inc, Madison, WI). These contigs were subjected to BLAST
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analysis within the National Center for Biotechnology Information (NCBI) database for
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phylogenetic inferences and grouped by the lowest taxonomic category as Operational
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Taxonomic Units (OTUs).
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Three functional guilds have been recognized in soil invertebrate ecology: Micro-predators,
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Litter Transformers, and Ecosystem Engineers (Lavelle 1996; Lavelle et al. 1997; Wardle
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2002). However, based on previous literature (Lavelle et al., 1997; Wardle 2002 Lavelle
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1996; Lavelle et al., 2006; Lavelle et al., 1995), as well as our own conclusions, each class
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of soil fauna (micro-, meso-, macro-) was not limited to one specific functional group. Thus,
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these OTUs were then clustered together into 5 functional guilds known to perform specific
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and critical ecological functions in soil development (Lavelle et al., 1997; Wardle 2002
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Lavelle 1996; Lavelle et al., 2006; Lavelle et al. 1995) for further analysis. These Guilds are
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(1) Litter Transformers; (2) Ecosystem Engineers; (3) Micropredators/Litter Transformers;
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(4) Ecosystem Engineers/Litter Transformers; (5) Primary Decomposers.
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2.3 Biotic Community DNA Sequence Data Analysis
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The data from the invertebrate COI DNA sequences were rarified to 1000 sequences prior to
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analysis. The abundance of the different OTU members of each invertebrate guild were
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determined and converted into the percent relative abundance (%RA) by habitat, as in
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previous methods done by McGee and Eaton (2014). From these data, differences in
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invertebrate guild community structure were determined using EcoSim (version 7.0; Gotelli
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and Entsminger 2001).
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To take a more holistic or networking approach to begin identifying possible complex
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ecological community patterns associated with soil fauna functionality, simple assessment of
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the alpha and/or beta diversity was not used, but rather the Monte Carlo Null model
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systems to explore interactions between taxa and possible functional roles or environmental
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niches associated with the different taxa. We used EcoSim to analyze the different DNA
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sequences to determine: a) if the communities were randomly or non-randomly structured;
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b) the level of co-occurrence and competition between and among guilds, as an indicator of
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shared space and niche among and competition between guilds; and c) if these biotic
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communities were structured around a limiting resource or environmental condition using
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the niche overlap analysis method. These analyses were conducted on total soil invertebrate
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communities and on each of the soil invertebrate guild members to assess for differences in
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community patterns between the different seasons studied.
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To quantify patterns of co-occurrence and determine the relative strength of these
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relationships, we used the Standardized Effect Size (SES) of the C-score index (Stone and
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Roberts 1990) in EcoSim. The C-score is calculated by the simulated pseudo-communities
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and this C-score should be significantly greater than expected by chance (Gotelli and Graves
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1996). The Null Model hypotheses have been used to suggest the degree of co-occurrence
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and non-randomness, as well as being the least sensitive of the models exposed to noise in
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the data set, while still having good statistical value (Gotelli 2000). The Null Model
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hypothesis is that the SES-C scores are 0, and that 95% of the observations will fall
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between -2 and 2. For example, an SES-C score observed at 1.5 or more suggests a non-
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random community and that there is significantly less co-occurrence than predicted among
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species. Thus, members of the same group do not co-exist leading to a greater
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“checkerboard” effect. This model supports the idea of a community that may be more
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competitive for resources and space, however, the opposite can be said of a SES-C score
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less than -1.5.
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Recent use of C-scores in microbial ecology have generally shown non-randomly structured
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communities and more co-occurrence of microbial taxa than anticipated (e.g. Horner-Devine
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et al. 2007; Barberan et al 2011). The advantage in detecting such non-random assembly
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patterns, which demonstrate specifically existing structured communities due to possible
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competitive interactions between groups, is that it allows one to determine relationships
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among these communities across different habitats or environmental conditions (i.e.
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differences in nutrient content, anthropogenic perturbations, ecosystem management). In
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the current study, the communities that showed a significantly greater observed SES-C
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score than the simulated C-scores, were considered to be exhibiting less co-occurrence of
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species than predicted, thus, suggesting a non-randomly structured community that was
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competing for their appropriate environmental need.
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The pseudo-communities were established by randomly reshuffling the Guild species
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abundance data in EcoSim for 30,000 iterations to reduce the rate of Type I errors and
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other algorithm biases as recommended by Lehsten and Harmand (2006). We used the
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default EcoSim parameters as they are recommended when assessing communities that are
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assumed to have different environmental conditions—such as we had in the Bromeliad wet
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season conditions versus the dry season conditions. Reported are the number of times the
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observed C score of the actual data was greater or less than the expected (simulated) C-
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score, the SES-C score, and the p value of the chance that this difference was random
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(thus, the community is randomly or non-randomly structured) for the total community and
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the individual Guilds. When pexp > pobs was very small (usually <0.1), we said that the
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greater observed SES-C score was meaningful, and represented a condition of competition
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and a non-randomly structured community. Under the opposite conditions we said that
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there were sufficient members of a group to suggest the community was not competitively
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structured.
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In order to validate niche overlap values as indicators of resource partitioning, the Monte
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Carlo method was used in EcoSim to estimate the level of niche overlap, the overlap non-
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randomness, and whether the overlap values were greater than or less than expected. The
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randomization algorithm 2 (RA2) conditions were used (Lawlor 1980) to test for the
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possibility that variations in certain resource states or conditions may be structuring the
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invertebrate communities studied, when there are no other constraints on resource
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utilization (Winemiller and Painka 1990; Gotelli and Graves 1996). Furthermore, we
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developed pseudo-community assemblages by randomly re-shuffling the abundance data in
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EcoSim through 30,000 iterations. The niche overlap indices were calculated for the total
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invertebrate and also for each invertebrate guild. The observed overlap from the data, the
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mean expected (simulated) overlap, the number of times the observed was > or < than the
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simulated overlap, the probability that these differences were random occurrences, and the
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Standardized Effect Size were calculated. Resource partitioning (and, thus, possible
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resource limitations) was considered important in structuring the biotic communities when
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the observed niche overlap was significantly (generally <0.1) less than the expected
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(simulated) overlap (pobs < pexp). Evidence for a relatively “unlimited” resource was assumed
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when the observed niche overlap was significantly greater than the expected overlap (pobs >
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pexp) as suggested by Gotelli and Graves (1996).
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3. Results
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The 454 pyrosequencing yielded 9788 sequences total, and 7205 sequences that were classifiable.
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These were rarefied to 1000 sequences per habitat, and grouped into 45 clearly distinct OTUs or
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phylotypes, representing 17 distinct taxonomic groups that were then placed into the 5 functional groups
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or Guilds described above and presented as the percent relative abundance (% RA) in Table 1.
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3.1 Bromeliad wet season soil vs. Bromeliad dry season soil
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Guild 1:
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The wet season soils had the greatest relative abundance of this guild (50%), which were
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dominated by Gammaridea Amphipoda (Table 1). During the dry season this guild
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decreased in relative abundance (13%) and were dominated by Gammaridea Amphipoda as
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well. The EcoSim analysis (Table 2) showed that this guild was non randomly structured and
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there was little inter-specific competition between member of this guild, such that there
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were significant enough members of the guild to suggest a non-competitively structured
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community (pexp > pobs = 0.21320; SES = 1.92; Cobs > Cexp = 23,604 of 30,000 iterations).
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It was also shown that there was a large amount of niche overlap among this guild, with
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minimal partitioning of a resource of limitation in resources (pexp > pobs = 0.03253; SES =
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1.79385; Number of times obs < exp = 29,024 of 30,000 iterations). These data in
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connection with the abundance data suggests that during the wet season, this guild is not
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limited by resources or some environmental condition. However, this is not the case during
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the dry season. The relative abundance of this guild in the dry seasons suggest there is a
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resource limitation that minimizes the abundance of this guild in Bromeliad soils.
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Guild 2:
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The Ecosystem Engineers, showed a similar relative abundance during the wet season
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(14%) and the dry season (11%) (Table 1).The EcoSim analysis (Table 2) showed that this
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guild was randomly structured, and there appears to be little inter-specific competition
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between members of this guild to suggest a non-competitively structured community (pexp >
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pobs = 0.33403; SES = 1.41197; Number of times Cobs < Cexp = 19,979 out of 30,000
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iterations). It was also shown that there was a low amount of niche overlap among this
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guild, suggesting the differential use of resources or limitation of some environmental
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condition that could be helping to structure this guild community (pexp < pobs = 0.00013;
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SES = -4.29660; Number of times obs > exp = 29,995 of 30,000 iterations). The relative
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abundance did not vary much across seasons (wet season = 14%; dry season = 11%). This
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guild appears to only be present when their resource is present.
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Guild 3:
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No detectable DNA for this guild.
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Guild 4:
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The wet season soil had a moderate amount of members in this guild (21%), but during the
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dry season, this relative abundance appears to decrease (9%) (Table 1). The EcoSim
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analysis (Table 2) showed that this guild was non-randomly structured, and that there is
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inter-specific competition occurring between members of this guild, such that it is a
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competitively structured community (pexp < pobs = 0.04923; SES = 2.59757; Number of
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times Cobs > Cexp = 28,523 of 30,000 iterations). It was also shown there was a large
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amount of niche overlap among members of this guild, suggesting no resource partitioning
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(pexp > pobs = 0.00360; SES = 2.4; Number of times obs > exp = 29,892 out of 30,000
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iterations). These data in connection with the abundance data suggests that during the wet
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season this guild is competitively structured around some environmental condition that is
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present due to the larger relative abundance (21%). However, during the dry season, there
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appears to be a lack of that environmental condition not fit for Guild 4 to thrive, as indicated
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by the minimized abundance of Guild 4 in the dry season (9%).
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Guild 5:
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During the dry season in the Bromeliad patch soils, representatives of this guild dominated
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by Peronosporales and Pythiales Oomycetes, showed a large amount of relative abundance
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(68%), while the wet season experiences a drop in the relative abundance of these guild
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members (15%) (Table 1). The EcoSim analysis (Table 2) showed that this guild was non-
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randomly structured, and that there is inter-specific competition occurring between
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members of this guild such that it is a competitively structured community pexp < pobs =
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0.11; SES = 2.28; Number of times Cobs > Cexp = 26,627 out of 30,000 iterations). It was
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also shown there was very little niche overlap among this guild, suggesting resource
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partitioning or limitation of some environmental resource (pexp < pobs = 0.00040; SES = -
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3.7; Number of times obs < exp = 29,998 out of 30,000 iterations). These data in
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connection with the abundance data suggests that during the dry season, this guild is
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competitively structured around some environmental resource, and that this resource is
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more present during dry seasons due to the large relative abundance of this Guild during
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the dry season as compared to decreased abundance in the wet season.
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3.2 Bromeliad patch soil vs. Primary forest soil
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Guild 1:
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Both habitats had a substantial amount of this guild in the soils, with the Bromeliad patches
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containing the greatest abundance of this guild, representing 50% of the total relative
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abundance of all taxa in these soils (Table 3). In all these habitats, Gammarid Amphipods
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dominated this guild. The EcoSim analysis (Table 4) showed that this guild was non-
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randomly structured and that there was little inter-specific competition between members of
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this guild (pexp < pobs = 0.14950; SES = 1.86268; Cobs > Cexp = 25,515 of 30,000
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iterations). It was also shown that there was a low amount of niche overlap, suggesting
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resource partitioning or limitation of some environmental resource (pobs < pexp = 0.00136;
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SES = -2.71437; Number of times obs < exp = 29,862 out of 30,000 iterations). These
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data in connection with the abundance data suggests that member of this guild are non-
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competitively structured around some environmental resource and that this resource could
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be more present in Bromeliad soils due to the larger relative abundance (50%), as opposed
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to the lower relative abundance in Primary forest soils (30%).
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Guild 2:
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The Bromeliad patch soils had the greatest abundance of this guild (14%) which were
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dominated by several Ecosystem Engineers including: Haplogynae and Araneomorphe
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(Table 3). The EcoSim analysis (Table 4) showed that this guild was randomly structured
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with respect to competition (pobs > pexp = 0.335587; SES = 1.40617; Cobs > Cexp = 19,924
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out of 30,000 iterations). It was also shown this guild had a low amount of niche overlap,
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suggesting resource partitioning of limitation of some environmental resource (pobs < pexp =
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0.00980; SES = -2.73; Number of times obs < exp = 29,706 out of 30,000 iterations).
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These data in connection with the abundance data suggests that in Bromeliad soils this guild
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is structured around a limiting resource that could be more present in Bromeliad soils due to
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the larger relative abundance (14%). However, the Primary forest soils appear to lack this
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environmental resource given the lesser relative abundance (1.48%).
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Guild 3:
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The Bromeliad patch soils contained no detectable DNA from any members of this guild,
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however, the Primary forest soils contained 23% relative abundance of members of this
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guild (Table 3). Specifically, these representatives included: Onychiurinae and
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Proisotominae of Collembola, and Oribatida of Arachnida. The EcoSim analysis (Table 4)
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showed that this guild was non-randomly structured and that there was little inter-specific
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competition to suggest a non-competitively structured community (pobs < pexp = 0.13; SES
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= -2.45; Cobs < Cexp = 26,246 out of 30,000 iterations). It was also shown that there was a
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large amount of niche overlap with minimal partitioning of resources or limitations of
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resources (pobs > pexp = 0.0001; SES = 1.61; Number of times obs > exp = 30,000 out of
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30,000 iterations). However, these data in connection with the abundance data suggests
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members of Guild 3 are structured around a particular resource that could be more present
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in Primary forest soils as indicated by the high relative abundance in Primary forest soils
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(23%), and the lack of detectable DNA in Bromeliad soils (0%).
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Guild 4:
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The Primary forest soils had the greatest relative abundance of this guild (42%) while the
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Bromeliad patch soils only contained 21% relative abundance of this guild (Table 3). The
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EcoSim analysis (Table 4) showed that this guild was non-randomly structured and there
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appears to be inter-specific competition occurring between members of this guild, such that
440
it is a competitively structured community (pobs > pexp = 0.09007; SES = 1.91137; Cobs >
441
Cexp = 27,298 out of 30,000 iterations). It was also shown that this guild had very little
442
niche overlap suggesting resource partitioning or limitation of some environmental resource
443
(pobs < pexp = 0.0003; SES = -4.85070; Number of times obs < exp = 29,999 out of 30,000
444
iterations). These data in connection with the abundance data, suggests members of Guild 4
445
are structure around a limiting resource that could be more present in the Primary forest as
446
indicated by the large relative abundance in Primary forest soils (42%) as opposed to the
447
minimized relative abundance in Bromeliad patch soils (21%).
448
449
Guild 5:
450
The Bromeliad patch soils contained a moderate relative abundance of this guild (15%),
451
while only 4% relative abundance of this guild was observed in Primary forest soils (Table
452
3). The EcoSim analysis (Table 4) showed that this guild was randomly structured (pobs >
453
pexp = 0.40257; SES = 1.21820; Cobs < Cexp = 17,923 out of 30,000 iterations). It was also
454
shown that this guild had a low amount of niche overlap suggesting resource partitioning or
16
455
limitation of some environmental resource (pobs < pexp = 0.00883; SES = -2.62633; Number
456
of times obs < exp = 29,735 out of 30,000 iterations). However, these data in connection
457
with the abundance data suggests members of Guild 5 are structured around a limiting
458
resource that is more present in Bromeliad soils as indicated by the larger relative
459
abundance in Bromeliad soils (15%) compared to the lesser relative abundance in Primary
460
forest soils (4%).
461
462
4. Discussion
463
464
The data from this study suggests that certain invertebrate guilds appear to be driven by
465
moisture as indicated by fluctuations in relative abundance of each invertebrate guild across
466
seasons in Bromeliad patch soils. The data from this study also suggests that members of
467
Oomycota are structured around a limited resource and this resource could be moisture as
468
shown by the large changes in relative abundance moving from wet season to dry season in
469
Bromeliad patch soils. From the meta-analysis studied, the data suggests that a naturally
470
modified environment such as the Bromeliad patch soils, results in a modified environment
471
with respect to invertebrate guild structure. Invertebrate guilds associated with more
472
complex carbon development appear to be more abundant in Primary forest soils, than
473
Bromeliad patch soils.
474
475
In Bromeliad Patch soils moving from wet season to dry season, there is a decrease in
476
relative abundance of guilds 1 and 4, an increase in relative abundance of guild 5, and guild
477
2 had similar relative abundances. Members of guild 1 and 4 were competitively structured
478
with high niche overlap, however, the decrease in relative abundance of these guilds across
479
seasons, suggests that representatives of these guilds are driven by moisture. This is
480
consistent with the literature as Polychaeta and Gammaridea (guild 1) prefer dark, damp
481
habitats (Minor and Robertson 2006). The decrease of guild 4 members is also consistent
17
482
with the literature such that, during the wet season, more litter fall is occurring on the
483
forest floor that provide resources for representatives of guild 4 like Coleoptera, which make
484
up the majority of guild 4.
485
486
Members of guild 5 increased in relative abundance in the dry season, were competitively
487
structured, and had a low amount of niche overlap which suggests resource partitioning.
488
Guild 5 representatives appear to be driven by a decrease in moisture as indicated by the
489
increased relative abundance during the dry season. This could possibly be explained by the
490
germination strategies of Oomycota. Soil-dwelling and aquatic Oomycota commonly
491
reproduce asexually via sporangium that contain flagellated free swimming zoospores
492
(Sleigh 1989; Margulis et al. 1990); but the Bromeliad soil may become too saturated
493
during the wet season, that these motile spores are actually washed away. Given the low
494
fungal abundance and activity in these Bromeliad soils, this suggests Oomycota are the
495
primary decomposers in the Bromeliad soils during the dry season. However, the primary
496
decomposers might be the Amphipods during the wet season, as indicated by the increase
497
in relative abundance of guild 1.
498
499
In the meta-analysis comparing a complex primary forest to the specialized Bromeliad plant
500
community, there was an increase in relative abundance of guilds 1, 2, and 5, and a
501
decrease in relative abundance of guilds 3 and 4. Guild 1 representatives were competitively
502
structured and had a low amount of niche overlap. However, the relative abundance of guild
503
1 in the Primary forest soil is less than the relative abundance in Bromeliad soils. In primary
504
forest soils, guild 1 could be outcompeted by other more efficient litter transformers and
505
micro-predators that belong to guild 3, such as Collembolans and Oribatids. The more
506
complex vegetation associated with the Primary forest stimulates more complex fungal
507
decomposers which could account for the presence of guild 3 members that graze on these
508
fungi. In Bromeliad soils, there is a decrease in fungal activity and abundance (Looby et al.
18
509
2012), as well as vegetation complexity (Looby and Eaton 2014) which would not stimulate
510
those of guild 3 that are active micro-predators, thus allowing guild 1 to thrive.
511
512
Interestingly, guild 3 was only present in the Primary forest soils, were non competitively
513
structured, and had high niche overlap. The lack of guild 3 DNA in Bromeliad soils is no
514
surprise as there are fewer fungi and less organic matter present, as well as less vegetation
515
complexity and diversity. These conditions would be less conducive to the growth of
516
members of guild 3.
517
518
Guild 2 was randomly structured with respect to competition, but had a low amount of niche
519
overlap. Members of guild 2 were more abundant in Bromeliad soils as opposed to Primary
520
forest soils, most likely due to the prominent presence of complex guild 4 ecosystem
521
engineers/litter transformers associated with more efficient Carbon utilization in the Primary
522
forest. Guilds 2 and 4 exploit similar environmental resources but on different levels of
523
complexity. Therefore, it would be predicted that the soil invertebrate guilds (i.e., guild 4)
524
capable of comminuting recalcitrant residues, would outcompete those soil invertebrate
525
guilds (i.e., guild 1) that are less efficient at such decomposition. Since there was a greater
526
relative abundance of guild 2 in a specialized habitat, this increase could be an indicator of
527
an altered environment. Consequently, higher abundance of guild 4 in the Primary forest
528
habitats is most likely due to the increase in vegetation complexity which would attract
529
those members of guild 4 associated with the degradation of complex herbaceous and
530
woody plant material. The dearth of vegetation complexity in the bromeliad habitats may
531
not be capable of sustaining an ample amount of resources to stimulate high growth and
532
relative abundance of this particular guild. Thus, in the presence or absence of complex
533
vegetation, guild 4 could be a possible indicator of ecosystem condition since it appears that
534
the relative abundance of guild 4 parallels that of the vegetation community.
535
19
536
The results of this study showed that the relative abundance of guilds 1, 4, and 5 appear to
537
be driven by changes in moisture across seasons in Bromeliad patch soils. Members of guild
538
1 would be expected to decrease in relative abundance moving from wet to dry season due
539
to their preference for damp and dark habitats. Therefore, guild 1 could be used as an
540
indicator for disturbances in seasonality. Also, an interesting indirect relationship between
541
guild 1 and guild 5 could be occurring. As the relative abundance of guild 1 decreases from
542
wet to dry season, guild 5 is increasing in relative abundance. Due to the known roles of
543
guild 1 and guild 5 as decomposers, some compensatory effect may be taking place. Thus,
544
it could be beneficial to observe the relative abundance of guilds 1 and 5, rather than just
545
one of these guilds.
546
547
4.1 Conclusions
548
549
The results of the meta-analysis showed that a naturally occurring modified environment
550
(Bromeliad patches) found within a primary forest can have differences in relative
551
abundance between invertebrate guild structure, such that those guilds associated with
552
microbivorous and complex decomposition activities (i.e., guilds 3 and 4) are more
553
abundant in primary forest soils than Bromeliad patch soils and could potentially be used for
554
indicators of habitat disturbance. Along the gradient of environmental conditions moving
555
from primary forest soils to bromeliad patch soils, the relative abundance of guilds 1 and 2
556
increase, and Guilds 3 and 4 decrease. Since Guilds 3 and 4 are linked to more efficient
557
Carbon utilization in the primary forest, if their resource were depleted, such as occurs in
558
the Bromeliads, this could lead to a decrease in relative abundance of these guilds. Thus,
559
this would allow other guilds, such as guild 1 and 2 to increase in relative abundance due to
560
the decrease of competition among these guilds that may perform similar roles, at a lesser
561
complex level. Therefore, observing the difference in relative abundance patterns between
562
each guild in a naturally modified environment (i.e., the bromeliad patches) to those in the
20
563
primary forest soils, may be a valuable tool for bioindicators of habitat damage.
564
Interestingly, the meta-analysis in this study in connection with a previous study by McGee
565
and Eaton (2014) showed the relative abundance of the invertebrate community across
566
guilds between Grassland and Bromeliad wet season soils are very similar (Fig 1) This
567
suggests that should some environmental alteration occur, whether natural or
568
anthropogenic, could result in changes in invertebrate community structure that parallel the
569
vegetation community and could possibly be a good indicator of ecosystem condition.
570
571
Acknowledgments
572
573
We would like to thank Vinzenz and Kurt Schmack, and the staff members at the Laguna del
574
Lagarto Lodge in Boca Tapada, Alajuela, Costa Rica for their great assistance in this project.
575
and processing. This study was supported by a grant from the National Science Foundation
576
(DBI-1034896) and was conducted under the Costa Rican Government Permit #063-2008-
577
SINAC.
578
579
References
580
581
Barberán A., Bates S.T., Casamayor E.O., Fierer, N., 2012. Using network analysis to
582
explore co-occurrence patterns in soil microbial communities. The ISME Journal 6,
583
343–351
584
585
Bik, H.M., Porazinska, D.L., Creer, S., Caporaso, J.G., Knight, R., Thomas, W.K., 2012.
586
Sequencing our way towards understanding global eukaryotic biodiversity. Trends.
587
Ecol. Evol. 27(4), 233-243.
588
21
589
Blanchart, E., Bruand, A., Lavelle, P., 1993. The physical structure of casts of Millsonia
590
anomala (Oligochaeta: Megascolecidae) in shrub savanna soils (Cote d’Ivoire).
591
Geoderma 56, 119- 132.
592
593
594
Brussaard, L., 1998. Soil fauna, guilds, functional groups, and ecosystem processes. Appl.
Soil Ecol. 9, 123-135.
595
596
Camacho-Hernández, I.L., Chávez-Veláquez, J.A., Uribe-Beltrán, M.J., Ríos-Morgan, A.,
597
Delgado-Vargas F (2002) Antifungal activity of fruit pulp extract from Bromelia
598
pinguin. Fitoterapia 73: 411-413.
599
600
Carrillo, Y., Ball, B., Bradford, M., Jordan, C., Molina, M., 2010. Soil fauna alter the effects
601
of litter composition on nitrogen cycling in a mineral soil. Soil Biol Biochem 43, 1440-
602
1449.
603
604
Chamberlain, P.M., McNamara, N.P., Chaplow, J., Stott, A.W., Black, H.I.J., 2006.
605
Translocation of surface litter carbon into soil by Collembola. Soil Biol Biochem 38,
606
2655-2664.
607
608
609
Chapin III, F.S., Matson, P.A., Vitousek, P., 2011. Principles of terrestrial ecosystem
ecology. (2nd Ed). Springer, New York.
610
611
Chassot, O., Monge, G., Powell, G., Wright, P., Palminteri, S., 2005. Corredor Biológico San
612
Juan-La Selva. Un proyecto del Corredor Biológico Mesoamericano para la
613
conservación de la lapa verde y su entorno. San José, Costa Rica: Centro Científico
614
Tropical
22
615
Chassot, O., Monge, G. (eds.). 2006. Plan de manejo del Refugio Nacional de Vida Silvestre
616
Mixto Maquenque, 2006-2010. Ciudad Quesada, Alajuela, Costa Rica, Área de
617
Conservación Arenal Huetar Norte (ACAHN), Sistema Nacional de Áreas de
618
Conservación (SINAC), Ministerio del Ambiente y Energía (MINAE), Centro Científico
619
Tropical (CCT), 244 p.
620
621
622
Coleman, D.C., Crossley, D.A., Hendrix, P.F., 2004. Fundamentals of Soil Ecology. (2nd Ed.)
Elsevier Academic Press, Burlington, MA.
623
624
625
Cragg, R., Bardgett, R., 2001. How changes in soil faunal diversity and composition within a
trophic group influence decomposition processes. Soil Biol. Biochem 33, 2073-2081.
626
627
Creer S, Fonseca VG, Porazinska DL, Giblin-Davis RM, Sung W, et al. (2010)
628
Ultrasequencing of the meiofaunal biosphere: practice, pitfalls and promises. Mol.
629
Ecol., 19(Suppl 1): 4–20.
630
631
632
Decaëns, T., Jiménez, J., Gioia, C., Measey, G., Lavelle, P., 2006. The values of soil animals
for conservation biology. Eur. J. Soil Biol. 42, S23-S38.
633
634
Emerson, B.C., Cicconardi, F., Fanciulli, P.P., Shaw, P.J.A., 2011. Phylogeny,
635
phylogeography, phylobetadiversity, and the molecular analysis of biological
636
communities. Philos. T. R. Soc. B. 366, 2391-2402.
637
638
Giller, P.S., 1984. Community Structure and the Niche. Chapman and Hall, London.
639
640
Gotelli, N.J., G.L. Entsminger., 2012. EcoSim 7.72. Acquired Intelligence, Inc.
641
http://www.uvm.edu/~ngotelli/EcoSim/EcoSim.html
23
642
643
644
Gotelli, N.J., 2000. Null model analysis of species co-occurrence patterns. Ecology 81, 26062621.
645
646
647
Gotelli, N.J., Graves, G.R., 1996. Null Models in Ecology. Smithsonian Institution Press,
Washington, D.C.
648
649
650
Hallwachs, W., 1983. Bromelia pinguin and B. karatas. In: Janzen DH. Costa Rican Natural
History. Chicago: The University of Chicago Press. pp. 195-197.
651
652
653
Hattenschwiler, S., Gasser, P., 2005. Soil animals alter plant litter diversity effects on
decomposition. PNAS 105, 1519-1524.
654
655
Hattenschwiler, S., Fromin, N., Barantal, S., 2011. Functional diversity of terrestrial
656
microbial decomposers and their substrates. C. R. Biol. 334 (5), 393-402
657
658
Horner-Devine, M.C., Silver, J.M., Leibold, M.A., Bohannan, B.J., Colwell, R.K., Fuhrman,
659
J.A., 2007. A comparison of taxon co-occurrence patterns for macro- and
660
microorganisms. Ecology 88, 1345–1353
661
662
663
664
Laurance, W.F., Peres, C.A., 2006. Emerging threats to tropical forests. University of
Chicago Press, Chicago.
665
666
Lavelle, P., Decaëns, T., Aubert, M., Barot, A., Blouin, M., Bureau, F., Margerie, P., Mora, P.,
667
Rossi, J.-P.,2006. Soil invertebrates and ecosystem services. Eur. J. Soil Biol. 42, S3-
668
S15.
24
669
670
671
Lavelle, P., 1996. Diversity of soil fauna and ecosystem function. Biology International
N°33, 3-16.
672
673
674
Lavelle, P., Bignell, D., Lepage, M., 1997. Soil function in a changing world: The roles of
invertebrate ecosystem engineers. Eur. J. Soil Biol. 33, 159-193.
675
676
677
Lawlor, L.R., 1980. Structure and stability in natural and randomly constructed competitive
communities. The American Naturalist 116, 394-408
678
679
680
Lehsten, V., Harmand, P., 2006. Null models for species co-occurrence patterns: assessing
bias and minimum iteration number for the sequential swap. Ecography 29, 786-792
681
682
683
Leopold, C.A., Andrus, R., Finkeldeyc, A., Knowles. D., 2001. Attempting restoration of wet
tropical forests in Costa Rica. Forest Ecol. Manag. 142, 243-249.
684
685
Looby, C., Hauge, J.B., Barry, D., Eaton, W.D., 2012. Fungal inhibition by Bromelia pinguin
686
(Bromeliaceae) and its effects on nutrient cycle dynamics. Trop. Ecol. 53(2), 225-234.
687
688
689
Looby, C., Eaton, W.D., 2014. Effects of Bromelia pinguin (Bromeliaceae) on soil ecosystem
function in the lowland forests of Costa Rica. BMC Ecol., In Review.
690
691
692
Margulis, L., Corliss, J.O., Melkonian, M., Chapman, D.J., 1990. Handbook of Protocista, 2nd
ed. Jones and Bartless Publishing, 1024 pp.
693
25
694
McGee, K.M., Eaton, W.D., 2013a. Linking soil funal and fungal community diversity with
695
carbon and nitrogen cycle dynamics at potential indicators of ecosystem condition in
696
three habitats in the Northern Zone of Costa Rica. Soil Biol Biochem: In Review.
697
698
McGee, K.M., Eaton, W.D., 2013b. The effects of the conversion of a primary to a secondary
699
tropical lowland forest on Bullet Ant (Paraponera clavata) foraging behavior in Costa
700
Rica: A possible indicator of ecosystem condition. J. Insect Behav. 26 (5), DOI
701
10.1007/s10905-013-9413-5.
702
703
Meusnier, R., Nolte, V., Pandey, R.V., Jost, S., Ottenwälder, B., Schlötterer, C., J. Boenig,
704
K., 2010. Diversity in a hiddenworld: potential and limitation of the next-generation
705
sequencing for surveys of molecular diversity of eukaryotic microorganisms. Mol. Ecol.
706
19, 32-40.
707
708
Minor, M.A., Robertson, A.W., 2006. Amphipoda. Soil Bugs - An Illustrated Guide to New
709
Zealand Soil Invertebrates (updated 11-Dec-2012), http://soilbugs.massey.ac.nz (27-
710
Jan-2013)
711
712
Monge, G., Chassot, O., Lopez, R., Chaves, H., 2002. Justificación biológica para el
713
establecimiento del propuesto Parque Nacional Maquenque. San José, Costa Rica:
714
Corredor Biológico San Juan-La Selva / Centro Científico Tropical, 50 p.
715
716
717
718
719
Monge, G., Chassot, O., Powell, G., Palminteri, S., Aleman, U., Wright, P., 2003 Ecología de
la lapa verde (Ara ambigua) en Costa Rica. Zeledonia 7, 4-12.
Sader, S., Joyce, A., 1988. Deforestation Trends and Rates in Costa Rica. Biotropica 20,
1940-1983.
26
720
721
Sánchez-Azofeifa, G.A., Harris, G.A., Skole, D.L., 2001. Deforestation in Costa Rica: A
Quantitative Analysis Using Remote Sensing Imagery. Biotropica 33, 378-384.
722
Sleigh, M.A. 1989. Protozoa and other protists. Cambridge University Press. 352pp. 1st ed.
723
Stone, L., Robers, A., 1990. The checkerboard score and species distributions. Oecologia
724
85,74–79
725
726
Wang, S., Ruan, H., Wang, B., 2009. Effects of soil microarthropods on plant litter
727
decomposition across an elevation gradient in the Wuyi Mountains. Soil Biol. Biochem.
728
41, 891-897.
729
730
731
Wardle, D.A. 2002. Communities and Ecosystems: Linking the Aboveground and
Belowground Components. Princeton University Press, Princeton.
732
733
734
Wardle, D.A., Yeates, G.W., Barker, G.M., Bonner, K.I., 2006. The influence of plant litter
diversity on decomposer abundance and diversity. Soil Biol. Biochem. 38, 1052-1062
735
736
737
Wardle, D.A., 2006. The influence of biotic interactions on soil biodiversity. Ecol. Lett. 9,
870-886.
738
739
Wardle, D.A., Bardgett, R.D., Klironomos, J. N., Setala, H., Van der Putten, W. H., Wall,
740
D.H., 2004. Ecological linkages between aboveground and belowground biota. Science
741
304, 1629-1633.
742
743
744
Winemiller, K.O., Pianka, E.R., 1990. Organization in natural assemblages of desert lizards
and tropical fishes. Ecol. Monog. 60, 27-55.
745
27