Dynamics of leaf litter humidity, depth and quantity: two restoration strategies failed to mimic ground microhabitat conditions of a low montane and premontane forest in Costa Rica
*Dirección para correspondencia
Abstract Little is known about how restoration strategies affect aspects like leaf litter’s quantity, depth and humidity. I analyzed leaf litter’s quantity, depth and humidity yearly patterns in a primary tropical lower montane wet forest and two restored areas: a 15 year old secondary forest (unassisted restoration) and a 40 year old Cupressus ]]>
plantation (natural understory). The three habitats are located in the Río Macho Forest Reserve, Costa Rica. Twenty litter samples were taken every three months (April 2009-April 2010) in each habitat; humidity was measured in 439g samples (average), depth and quantity were measured in five points inside 50x50cm plots. None of the restoration strategies reproduced the primary forest leaf litter humidity, depth and quantity yearly patterns. Primary forest leaf litter humidity was higher and more stable (x=73.2), followed by secondary forest (x=63.3) and cypress plantation (x=52.9) (Kruskall-Wallis=77.93, n=232, p=0.00). In the ]]>
the leaf litter’s structure in different ecosystems though the year.
Key words: restoration strategies evaluation, leaf litter humidity, leaf litter quantity, leaf litter depth, leaf litterstructural complexity. Resumen
Poco se sabe acerca de cómo las estrategias de restauración afectan aspectos como la cantidad, profundidad y humedad de la hojarasca. Se analizaron estas variables en un bosque tropical húmedo montano bajo, considerado bosque primario y dos áreas restauradas: un bosque secundario de 15 años (restauración natural) y una plantación de Cupressus lusitanica de 40 ]]>
Palabras clave: evaluación de estrategias de restauración, humedad de hojarasca, cantidad ]]>
Tropical forests have undergone extensive deforestation throughout the world (Geist & Lambin 2002, Quesada et al. 2009, FAO 2010), increasing the need to develop scientific restoration efforts. The selected restoration strategy will ]]>
In Costa Rica all restoration strategies leave understory to natural ecological succession (or “unassisted restoration”), but the canopy establishment follows three ]]>
et al. 2008, Sampaio et al. 2008, Quesada et al. 2009, Barrientos & Monge 2010, Cole et al. 2010, Castellanos-Barliza & León 2011). More complex ]]>
et al. 2008) are not common in Costa Rica. Restoration strategy selection in Costa Rica is a consequence of political and economic national strategies (Jiménez 2005, Murillo 2005). Nevertheless, the application of a restoration strategy should take into account ]]>
Selection of a restoration strategy impacts micro and macro-scale elements, such as soil temperature, litter quality, soil respiration rates, nitrogen availability, microbial biomass, faunal community composition, among others, that ]]>
et al. 2009a). Therefore, technical analysis of restoration strategies require multi-disciplinary and ecosystem level studies. However, to achieve such knowledge it is important to understand the dynamics of several phenomena: understory composition; forest temperature and moisture; litter production, structure, humidity, and decomposition rates; soil erosion, plant dispersion, etc. In Costa Rica the study of these phenomena was started by L.A. Fournier in the 20th century (Fournier & Camacho de Castro 1973, Fournier & Herrera ]]>
One of the basic components of a tropical forest is the litter that accumulates on the ground, it constitutes an essential part of nutrient cycling (Wardle 2002, Álvarez-Sánchez & Harmon 2003, Ayres et al. 2009a, Castellanos-Barliza & León 2011). The vegetation that is chosen in a restoration program will define temperature and soil ]]>
et al. 2007). It also defines: soil physical and chemical properties (Ayres et al. 2009a); understory plant species composition; litter composition coming from the canopy and understory; leaf litter nutrients, production and decaying rate (Mosquera
et al. 2007, Scherer-Lorenzen et al. 2007, Hättenschwiler et al. 2008, Vivanco & Austin 2008); organism diversity (Vasconcelos 1999, Naranjo-García 2003, Doblas 2007, Sánchez et al. 2007, Bonilla et al. 2008, Castro-Díez et al. 2008, Ayres et al. ]]>
et al. 2008, Castro-Díez et al. 2008). Many studies have been performed on ]]>
et al. 2008), decomposition rates (Álvarez-Sánchez & Harmon 2003, Castro-Díez et al. 2008, Ayres et al. 2009b, c), nutrient release (Ayres et al. 2009a, Castellanos-Barliza & León 2011) and on litter organism diversity and its impact on decomposition rates (Fournier & Herrera de Fournier 1978, Barrientos 2000, Palacios-Vargas
et al. 2007, Ayres et al. 2009a). Despite the large number of species that inhabit the leaf litter, few studies have been done on its structural properties, dynamics and relation with organisms. A high diversity of angiosperms is characteristic of tropical forests and allows the establishment of a ]]>
et al. 2000, Ayres et al. 2009a, Ayres et al. 2009b). To my knowledge, no leaf litter structural complexity hypotheses or indexes have been built. Future ecologic work on this matter should consider plant species diversity, litter quantity, vertical space covered (depth), accumulation and decomposition rate, ]]>
A more complex litter layer has more species and organisms, probably because it provides more area to hide from predators, feed and lay eggs (Barrientos 2000, Sabo et al. 2005, Palacios-Vargas et al. ]]>
et al. 2008). In addition, the amount of litter defines the amount and rate of the interactions in the different trophic levels (Sabo et al. 2005). But contrary to what could be expected, Ayres et al. (2009c) found that litter decomposes more rapidly near the plant that produces it. This is probably the result of specialization by decomposers. ]]>
Litter also retains soil humidity longer than bare soil (Anderson 1990), allowing water to percolate instead of rapidly evaporating. Litter makes forest humidity more stable by keeping water (Díaz-Fernández et al. 2006, Ruiz et al. 2009), and prevents rain’s direct impact on the soil, reducing erosion (Di Stefano & Fournier 2005).
Rainfall and litter humidity are key factors in a complex interplay of processes. There is a negative relationship between litterfall and rainfall (Mosquera et al. 2007), witch at least in some tropical forests can be attributed to the presence of deciduous plants (Fournier & Camacho de Castro 1973). However, rainfall is crucial for litter decay (Cornejo
et al. 1994, Castellanos-Barliza & León 2011) and correlates with microbial biomass (Schimel et al. 1999) and abundance of other organisms (Bonilla et al. 2008). Litter humidity affects the community living under, in and on the litter, because in many cases species migrate vertically in order to achieve optimal environmental conditions (Barrientos 2000, Naranjo-García 2003, Doblas 2007). Another important finding is that extreme drought and occasional rewetting ]]>
et al. 1999). Litter humidity is affected by rainfall, litter composition and canopy cover, as well as by type, thickness and permeability of the soil (Álvarez-Sánchez & Harmon 2003, Díaz Fernández
et al. 2006, Sampaio et al. 2008). All these factors are modified with deforestation and establishment of a different flora community (Vasconcelos & Laurance 2005, Bonilla et al. 2008); therefore, any restoration process should consider these factors. However, litter humidity has been studied almost exclusively in relation to forest fires in temperate regions and lowland tropical dry forests (Odiwe & Muoghalu 2003, Dezzeo & Chacón 2006, Ruiz et ]]>
. 2009). The effect of different restoration strategies on humidity, structure, temperature, species composition and nutrient release of forest litter has not been analysed. This study analysed three variables that are important to understand leaf litter complexity and general patterns that affect biodiversity in the forests (leaf litter humidity, depth and quantity) in a primary forest, a secondary forest and a plantation.
Materials and methods Research area: The study was carried out in Orosi Valley, Costa Rica, at Reserva Forestal Río Macho. This reserve limits with the Tapantí-Macizo Cerro de la ]]>
Three habitats were selected: a primary forest (or “old growth forest” according to Clark (1996)) near the “El llano” water dam (9°45’56.07” N - 83°
51’47.11” W, 1 640msm), in a tropical lower montane wet forest area with ultisol humult soil; a secondary forest (or “young secondary forest” according to Clark (1996)) left to natural succession for about 15 years (9°45’29.52” N - 83°51’23.27” W, 1 684 msm), in a tropical lower montane wet forest area with ultisol humult soil, and a
Cupressus lusitanica plantation that has been without management for nearly 40 years and therefore has a poorly developed understory dominated by hardwood leaves species (9°47’52” N - 83°51’51” W, 1 309msm). The C. lusitanica plantation ]]>
°. Sampling: Samples were collected ]]>
In each sampling date a 200m randomly selected transect was set at least 10m away from any trail to avoid border effect and away of tree gaps to avoid the effect of direct sun evaporation on litter (Camargo & Kapos 1995). Along each line, ]]>
et al. 2009) and also because this is the time of the day with less rain and where re-humidification by atmospheric water vapour is less important (Pyne et al.1996, Dirks et al. 2010). ]]>
One leaf litter sample (mean 439g, SD=188, min=89, max=1 470) was collected in each 50x50cm plot. In each plot all litter was collected including small branches less than 5mm in diameter, fragmented litter and humus (representing successive decaying stages), only bare soil, living plants, stones and branches bigger than 5mm in diameter were left. Litter samples were kept in a plant oven (60oC) for several days until constant dry weight was reached to apply the formula: Humidity percentage=(wet weight–dry weight)/wet weight*100. ]]>
Litter depth was measured in each plot with a standard millimetric ruler in five independent places of a 50x50cm subplot. Average leaf-litter depth for each plot was calculated. Litter quantity was assessed by the number of hardwood leaves that could be threaded with an ice pick (10cm long, 3.5mm diameter) (five samples were taken for each plot) in a 50x50cm subplot. Cypresses needles were not considered in this methodology as they do not form layers. Leaf layers were analysed because they are useful ]]>
et al. 2007, Eaton et al. 2011). All statistical analyses where performed with Statgraphics Centurion XV. Leaf-litter humidity comparisons were made between habitats and between sampling dates (Kruskal-Wallis ANOVA). Litter abundance and depth were analyzed in ]]>
Results Leaf litter humidity comparison ]]>
Primary forest had the wettest litter (x=73.2, n=77, SD=11.6, min=8, max=87), followed by the secondary forest (x=63.3, n=75, SD=16.8, min=12, max=94) and cypress plantation (x=52.9, n=80, SD=14.6, min=21.3, max=77.6) (Kruskall-Wallis=77.93, n=232, p=0.00). ]]>
Leaf litter humidity according to season Dry season: During January the driest place was the plantation (x=31.1%) followed by the secondary forest (x=48.9%) and the primary forest (x=74.7%) (Kruskall-Wallis=35.75, n=59, p<0.001) (Fig.1). During the April ]]>
Fig. 1).
Wet season: During the July and October samplings the cypress plantation was drier (July x=60.6%, October x=59.9) than the other two habitats (primary forest: July =75.6%, October =79.4%) (secondary forest: July =72.6%, October =77.6%) (July, Kruskall-Wallis=31.68, n=60, p<0.001) (October, Kruskall-Wallis=35.31, n=58, p<0.001) (Fig. 1). Leaf litter humidity yearly pattern according to habitat Primary forest: Litter was drier during the April sampling (Kruskall-Wallis=33.28, n=77, p<0.001), but the difference between the driest and the wettest sampling was of only 15.8% (x max=79.4%, x min=63.6%) (x max=meanmaximum, x min=mean minimum) (Fig. 1). Secondary forest: Litter humidity pattern shows a longer period of low litter humidity than in the primary forest and the C. lussitanica plantation. In this habitat the litter was dryer during the January and April samplings (Kruskall-Wallis=49.16, n=75, p<0.001), and the difference between the driest and the wettest sampling was of 28.7% (x max=77.6%, x min=48.9%) (Fig. 1). Cupressus lusitanica plantation: Litter was driest during the January sampling (Kruskall-Wallis=44.1617, n=80, p<0.001) and the difference between the driest and the wettest sampling was 29.5% (x max=60.6%, x min=31.1%) (Fig.1). The wettest sampling mean (60.6%) in this habitat was even drier than the driest sampling mean in the primary forest (63.6%). Leaf litter depth and quantity in the three studied habitats in a year Thicker litter layer and greater quantity of leaves were associated with greater levels of litter humidity (Litter quantity, Spearman correlation r=0.3, n=232, p=0.000) (r=correlation, n=sample size), (Litter depth, Spearman correlation r=0.27, n=232, p=0.000). The litter depth (Kruskall-Wallis=78.95, n=233, p=0.0) (Fig. 2A) and quantity (Kruskall-Wallis=92.47, n=233, p=0.0) (Fig. 2B) were higher in the primary forest followed by the secondary forest and the cypress plantation. Leaf litter depth and quantity yearly patterns according to habitat Litter quantity pattern in primary (Kruskal-Wallis=31.63, n=78, p<0.001) (Fig. 3) and secondary forest (Kruskal-Wallis=11.79, n=75 p=0.008) (Fig. 3) show that leaf is more abundant in April and decreases until January. A completely different pattern was found in the cypress plantation where October is the sampling with more leaf abundance while April had the fewest (Kruskal-Wallis=7.77, n=80, p=0.0509, marginally significant).
Litter depth in ]]>
Fig. 4) and C. lusitanica plantation (Kruskal-Wallis=39.99, n=80, p<0.001) (Fig. 4) had their lowest value during the October sampling, while in the secondary forest all the samples had about the same litter depth values, just slightly lower during April (Kruskal-Wallis=10.68, n=75, p=0.014) (Fig. 4).
Discussion The findings in this research show that leaf litter humidity in primary forest is higher and more stable around the year than in these restoration habitats. Wind, evaporation, ]]>
et al. 2009, Dirks et al. 2010, Smith et al. 2010). In this case, probably the taller and more abundant canopy and understory dicotiledonean foliage cover of the primary forest (personal observation) help keeping the litter`s humidity higher and more stable the year around. The structure (quantity and depth) and species composition of the litter may also help keeping high humidity levels ]]>
The C. lusitanica plantation`s litter humidity is lower than in the primary and secondary forest almost the year around. The only exception is in April when the secondary forest is the driest. Nevertheless, the highest litter’s humidity in the cypress plantation was 60.6% which is lower than the driest sampling mean in the primary forest (63.6%). This can be ]]>
et al. 2009), litter decomposition stage (cypress secondary compounds may delay decomposition rates) (Ruiz et al. 2009), litter composition (mainly cypress needles), a poorly developed understory (personal observation), a more regular canopy structure and a more homogenous foliage cover (Rodriguez & Cordero, unpublished data). ]]>
Secondary forest’s and cypress plantation’s litter gain and lose more humidity than the primary forest’s litter, but during the rainy season, the secondary forest can be almost as humid as the primary forest. The only study known to me that compares angiosperm and gymnosperm litter humidity was made by Díaz-Fernández et al. (2006). This study shows that both kinds are able to keep the same humidity, the only exception are grasses, which are able to keep twice as much. Therefore, the wider ]]>
et al. 2006). The grass abundance in the secondary forest may be a result of occasional cattle activity in the ]]>
It is interesting that litter quantity and litter depth have the same general pattern: primary forest has the highest values, followed by the secondary forest; the cypress plantation has the smallest litter quantity and the shallower litter. Nevertheless, the patterns around the year in the three habitats are different. ]]>
In the primary and secondary forest litter quantity had its highest values during the April samplings. This pattern matches the inverse relation between litter productivity and rainfall found by other researchers (Di Stefano & Fournier 2005, Mosquera et al. 2007, Sánchez et al. 2007). The three studied habitats are within tropical lower montane wet forest and tropical ]]>
et al. 1994, Monedero & González 1995, Aerts 1997, Powers et al. 2009, Smith et al. 2010, Eaton et al. 2011, Salinas et al. 2011); experimental studies on this topic are ]]>
The primary forest and cypress plantation showed a litter’s depth pattern that has the lowest values in October, while April and January have the highest values. As the studied areas have steep slopes, it would be reasonable to think that some litter is flown downhill by heavy rains, but it is not the case ]]>
Litter depth patterns found in this study are different to litter quantity patterns, because describe different aspects of the litter’s structure and they should not be considered equivalents. ]]>
It is reasonable to expect that less litter humidity correlated with less litter quantity and depth, but as shown in this research the relation between them is much more complex. Therefore litter humidity, depth and quantity must be analyzed in relation with understory and canopy foliage cover and composition, and with soil features. In fact litter humidity presents a continuum with soil and understory, therefore many litter dwellers migrate between these strata to achieve better humidity conditions (Naranjo-García 2003, Doblas 2007, Ayres
et al. 2009a). Complementary research is being conducted on terrestrial molluscs in these plots, showing that their abundance and size distribution is strongly correlated with these factors (Barrientos, unpublished data). It would also be interesting to analyse regeneration patterns in relation to litter humidity and structure. The selection of a given ]]>
Acknowledgment Andrés Monge, Danyi Prieto and FabianAraya gave field assistance and Junior Pérez helped with literature search. I am especially grateful to Esteban ]]>
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*Correspondencia:
Zaidett Barrientos: Laboratorio de Ecología Urbana, UNED, 2050 San José, Costa Rica. zbarrientos@uned.ac.cr
1. Laboratorio de Ecología Urbana, UNED, 2050 San José, Costa Rica; zbarrientos@uned.ac.cr
Received 02-VI-2011. Corrected 14-I-2012. Accepted 17-II-2012.