The forest succession model FORDYN is developed based on TREEDEV model. TREEDEV is a process-based tree growth model, that calculates tree growth based on carbon and nitrogen balance, and is calculated using on the photo-production of leaves, respiration, nitrogen content of all organisms and that in soil, and other losses due to respiration, litter and renewal of stems, branches, leaves and roots. In the FORDYN model succession is divided into three phases called early, middle and late succession, and the transition between these three succession phases is distinguished by a difference in leaf area index. As a verification of the model we used the characteristics and available data of a monsoon evergreen broad-leaved forest in Dinghushan Biosphere Reserve (DHS-BR). The model was validated with natural forest data. In addition, a sensitivity analysis was performed in which 30 independent variables were varied and analyzed in connection with their influence on 16 dependent variables describing forest conditions. The simulation results describe the changes in total biomass, carbon and nitrogen change in plant–litter–soil system of an undisturbed monsoon evergreen broad-leaved forest during succession. We compared these findings with simulation in which different logging management strategies were used. The results show that having a longer logging cycle, delaying the first logging time and a smaller logging fraction the scenario can contribute to a sustainable forest development, while still having a positive economic yield. 相似文献
Reproductive success within populations often varies with the timing of breeding, typically declining over the season. This
variation is usually attributed to seasonal changes in resource availability and/or differences in the quality or experience
of breeders. In colonial species, the timing of breeding may be of particular importance because the costs and benefits of
colonial breeding are likely to vary over the season and also with colony size. In this study, we examine the relationship
between timing of breeding and reproductive performance (clutch size and nest success) both within and between variable sized
colonies (n = 18) of fairy martins, Petrochelidon ariel. In four of these colonies, we also experimentally delayed laying in selected nests to disentangle the effects of laying
date and individual quality/experience on reproductive success. Within colonies, later laying birds produced smaller clutches,
but only in larger colonies. The general seasonal decline in nest success was also more pronounced in larger colonies. Late
laying birds were generally smaller than earlier laying birds, but morphological differences were also related to colony size,
suggesting optimal colony size also varies with phenotype. Experimentally delayed clutches were larger than concurrently produced
non-delayed clutches, but only in larger colonies. Similarly, delayed clutches were more likely to produce fledglings, particularly
later in the season and in larger colonies. We suggest that the reduced performance of late breeding pairs in larger colonies
resulted primarily from inexperienced/low quality birds preferring to settle in larger colonies, possibly exacerbated by an
increase in the costs of coloniality (e.g., resource depletion and ectoparasite infestations) with date and colony size. These
findings highlight the importance of phenotype-related differences in settlement decisions and reproductive performance to
an improved understanding of colonial breeding and variation in colony size. 相似文献
Soil fertility is conventionally evaluated by soil properties such as C, N, and P contents. Evaluation of soil fertility is
now becoming a routine work for soil management and crop production. However, laboratory-analysis based determination of soil
properties is time and cost consuming, which is not suitable for precision agriculture. Here, infrared spectroscopy (IR) appears
as an alternative and fast technique to measure soil fertility. The IR transmission method is generally used in soil qualitative
analysis, while the IR reflectance can be used in soil quantitative analysis, and most of soil-related research is focused
on reflectance spectroscopy. Infrared reflectance spectra, including diffuse reflectance spectra and total attenuated reflectance
spectra, are involved in soil quantitative analysis. We observe an excellent performance of predicting soil C and N contents
using IR spectra. Moreover, in most of cases the predictions of the contents of soil P, K, Ca, Mg, S, and some other microelements
are satisfactory. Soil water, soil clays, and soil microbes can also be characterized and evaluated using IR spectroscopy.
In recent years, a new method named infrared photoacoustic spectra was applied in soil analysis. Infrared-photoacoustic spectra
is indeed more convenient for sample pretreatment and spectra recording, and the recorded soil spectra contain more useful
information versus conventional reflectance spectroscopy. Though currently the application of infrared photoacoustic spectroscopy
in soil analysis is limited, it appears promising to measure soil fertility. The application of infrared spectroscopy in soil
fertility is largely dependent on spectra pretreatment and multivariate calibration due to strong interferences in the spectra.
Partial least square (PLS) and artificial neural network (ANN) are two widely used mathematical tools in the prediction of
soil properties, and more mathematical tools combined models will benefit the prediction performance. To make full use of
soil infrared spectra, soil spectra library construction is needed in future, and a standard procedure should be first decided
in the construction. Based on soil infrared spectra library soil fertility can be fast evaluated combining suitable mathematical
model, which will play an important role in the sustainable agriculture. 相似文献
Recent studies have expanded the interests about microbial community and function following the rapid development of high-throughput sequencing techniques in the freshwater ecosystem. In this study, we aimed to attain a deep understanding of microbial community structure and potential nitrogen metabolism in Hulun Lake, a shallow hypereutrophic steppe lake in the Mongolian Plateau in China. The result demonstrated that cyanobacteria were the most dominant phylum. Network analysis showed both intra- and inter-phylum co-occurrence were pervasive, and there were modular structures in the microbial assemblages. The cluster dominated by proteobacteria was mainly negatively connected to the cluster dominated by both proteobacteria and actinobacteria. Cyanobacteria were tightly clustered together and positively connected to these two clusters. The major nitrogen metabolism pathways were glutamine synthetase–glutamate synthase and assimilatory nitrate reduction, indicating the nitrogen was mainly retained in the lake by microbial uptake. Cyanobacteria contributed 43.25% gene reads involved in the overall nitrogen metabolism but mainly contributed to assimilatory nitrate reduction and nitrogen fixation, aggravating the lake eutrophication. This study adds to our knowledge of microbial assemblages and nitrogen metabolism in the shallow hypereutrophic lake and provided an insight understanding for the purposes of lake ecosystem’s protection and efficient management in the Mongolian Plateau.