1,721,160 research outputs found
Replication Data for: Restoration concessions: a second lease on life for beleaguered tropical forests?
No full textFull description of business model
Replication Data for Ecology of a fig ant–plant
No full textMutualistic interactions are embedded in networks of interactions that affect the benefits accruing to the mutualistic partners. Figs and their pollinating wasps are engaged in an obligate mutualism in which the fig is dependent on the fig pollinator for pollination services and the pollinator is dependent on fig ovules for brood sites. This mutualism is exploited by non-pollinating fig wasps that utilise the same ovules, but do not provide a pollination service. Most non-pollinating wasps oviposit from outside the inflorescence (syconium), where they are vulnerable to ant predation. Ficus schwarzii is exposed to high densities of non-pollinating wasps, but Philidris sp. ants patrolling the syconia prevent them from ovipositing. Philidris rarely catch wasps, but the fig encourages the patrolling by providing a reward through extra-floral nectaries on the surface of syconia. Moreover, the reward is apparently only produced during the phase when parasitoids are ovipositing. An ant-exclusion experiment demonstrated that, in the absence of ants, syconia were heavily attacked and many aborted as a consequence. Philidris was normally rare on the figs during the receptive phase or at the time of day when wasp offspring are emerging, so predation on pollinators was limited. However, Myrmicaria sp. ants, which only occurred on three trees, preyed substantially on pollinating as well as non-pollinating wasps. F. schwarzii occurs in small clusters of trees and has an exceptionally rapid crop turnover. These factors appear to promote high densities of non-pollinating wasps and, as a consequence, may have led to both a high incidence of ants on trees and increased selective pressure on fig traits that increase the payoffs of the fig–ant interaction for the fig. The fig receives no direct benefit from the reward it provides, but protects pollinating wasps that will disperse its pollen
Fig. 3 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
No full textFig. 3. Stingless bee species accumulation at traps in the six Virgin Jungle Reserves.Published as part of Salim, Hannah M. W., Dzulkiply, Ahmad Dzamir, Harrison, Rhett D., Fletcher, Christine & Kassim, Abd Rahman, 2012, Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia, pp. 213-219 in Raffles Bulletin of Zoology 60 (1) on page 216, DOI: 10.5281/zenodo.534723
Environmental and geographic factors driving dung beetle (Coleoptera: Scarabaeidae: Scarabaeinae) diversity in the dipterocarp forests of Peninsular Malaysia
No full textDoll, Hannah M., Butod, Elizabeth, Harrison, Rhett D., Fletcher, Christine, Kassim, Abd Rahman, Ibrahim, Shamsudin, Potts, Matthew D. (2014): Environmental and geographic factors driving dung beetle (Coleoptera: Scarabaeidae: Scarabaeinae) diversity in the dipterocarp forests of Peninsular Malaysia. Raffles Bulletin of Zoology 62: 549-560, DOI: http://doi.org/10.5281/zenodo.535447
Fig. 2 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
No full textFig. 2. Sampling design for one set of three transects. Three sets of three 300-m sampling transects were established at each Virgin Jungle Reserve. Transects ran parallel to each other with approximately 500 m between them. Nine baiting points were established along each transect.Published as part of Salim, Hannah M. W., Dzulkiply, Ahmad Dzamir, Harrison, Rhett D., Fletcher, Christine & Kassim, Abd Rahman, 2012, Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia, pp. 213-219 in Raffles Bulletin of Zoology 60 (1) on page 216, DOI: 10.5281/zenodo.534723
Mapping Leaf Area Index in subtropical upland ecosystems using RapidEye imagery and the randomForest algorithm
No full textCanopy leaf area, frequently quantified by the Leaf Area Index (LAI), serves as the dominant control over primary production, energy exchange, transpiration, and other physiological attributes related to ecosystem processes. Maps depicting the spatial distribution of LAI across the landscape are of particularly high value for a better understanding of ecosystem dynamics and processes, especially over large and remote areas. Moreover, LAI maps have the potential to be used by process models describing energy and mass exchanges in the biosphere/atmosphere system. In this article we assess the applicability of the RapidEye satellite system, whose sensor is optimized towards vegetation analyses, for mapping LAI along a disturbance gradient, ranging from heavily disturbed shrub land to mature mountain rainforest. By incorporating image texture features into the analysis, we aim at assessing the potential quality improvement of LAI maps and the reduction of uncertainties associated with LAI maps compared to maps based on Vegetation Indexes (VI) solely. We identified 22 out of the 59 image features as being relevant for predicting LAI. Among these, especially VIs were ranked high. In particular, the two VIs using RapidEye’s RED-EDGE band stand out as the top two predictor variables. Nevertheless, map accuracy as quantified by the mean absolute error obtained from a 10-fold cross validation (MAE_CV) increased significantly if VIs and texture features are combined (MAE_CV = 0.56), compared to maps based on VIs only (MAE_CV = 0.62). We placed special emphasis on the uncertainties associated with the resulting map addressing that map users often treat uncertainty statements only in a pro-forma manner. Therefore, the LAI map was complemented with a map depicting the spatial distribution of the goodness-of-fit of the model, quantified by the mean absolute error (MAE), used for predictive mapping. From this an area weighted MAE (= 0.35) was calculated and compared to the unweighted MAE of 0.29. Mapping was done using randomForest, a widely used statistical modeling technique for predictive biological mapping
Enhanced structural complexity index: An improved index for describing forest structural complexity
No full textThe horizontal distribution of stems, stand density and the differentiation of tree dimensions are among the most important aspects of stand structure. An increasing complexity of stand structure is often linked to a higher number of species and to greater ecological stability. For quantification, the Structural Complexity Index (SCI) describes structural complexity by means of an area ratio of the surface that is generated by connecting the tree tops of neighbouring trees to form triangles to the surface that is covered by all triangles if projected on a flat plane. Here, we propose two ecologically relevant modifications of the SCI: The degree of mingling of tree attributes, quantified by a vector ruggedness measure, and a stem density term. We investigate how these two modifications influence index values. Data come from forest inventory field plots sampled along a disturbance gradient from heavily disturbed shrub land, through secondary regrowth to mature montane rainforest stands in Mengsong, Xishuangbanna,Yunnan,China. An application is described linking structural complexity, as described by the SCI and its modified versions, to changes in species composition of insect communities. The results of this study show that the Enhanced Structural Complexity Index (ESCI) can serve as a valuable tool for forest managers and ecologists for describing the structural complexity of forest stands and is particularly valuable for natural forests with a high degree of structural complexity
Scale-dependent relationships between soil organic carbon stocks, land-use types and biophysical characteristics in a tropical montane landscape
No full textReplication Data for Correct calculation of CO2 efflux using a closed-chamber linked to a non-dispersive infrared gas analyzer
No full text1.Improved understanding of the carbon (C) cycle is essential to model future climates and how this may feedback to affect greenhouse gas fluxes.
2.We summarize previous work quantifying respiration rates of organic substrates and briefly discuss how advances in technology, specifically the use of chambers linked to a non-dispersive infrared gas analyzer (NDIR), can be applied to assess carbon dynamics from short-term field measurements. This technology hastens measurement and is relatively inexpensive, enabling researchers to increase replication and investigate temporal and spatial variation.
3.We describe the theory behind calculations of CO2 efflux released through organic substrates, when using a closed-chamber linked to a NDIR. These methods can in principle be extended to any chamber-based measurement of gas fluxes, including partially closed chambers as used for soil surface CO2, nitrous oxide or methane effluxes and stem CO2 respiration, although additional assumptions may apply.
4.We show that incorrect application of formulae in some earlier studies resulted in either under- or over-estimation of CO2 effluxes. Of the studies, we reviewed measuring the respiration of woody debris, leaf litter or woody stems using closed chambers linked to a NDIR, only 22% (11 of 51) provided the equations used to calculate CO2 efflux, and 72% (8 of 11) of those provided contained basic errors. Using our data on the decomposition of woody debris as an example, we found that such mistakes resulted in anywhere from 8% underestimation to 22% overestimation of CO2 efflux. The errors varied among studies and hence may limit understanding of the factors affecting emissions of CO2 and our ability to incorporate this knowledge into global carbon models.
5.We provide formulae for the correct calculation of respiration rates in future studies using closed chambers and thus provide a basis for comparative studies of factors affecting CO2 efflux from woody debris, leaf litter and other substrates. Ultimately, this will contribute to improved parameterization of forest respiration
Replication Data for Proximity to the host is an important characteristic for selection of the first support in lianas
No full textLianas depend on support to reach optimal growing conditions. They can infest trees unevenly, and host selection may depend on functional characteristics of the potential hosts, such as growth rate, bark type or tree architecture. In this context we hypothesized that (1) simple proximity to the rooting point of the liana is the overriding property predicting the probability of selection as the host; (2) the distance to the host decreases with increasing stem density in the surrounding community; (3) host distance becomes more variable with liana age (~diameter), as some larger lianas probably have already lost their first host, whereas small lianas should use the nearest available stem to climb; and (iv) liana infestation of plant families is proportional to family abundance
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