Lina Koyama

Natural 15 N Abundance of Plants and Soil N in a Temperate Coniferous Forest

Measurement of nitrogen isotopic composition (δ15N) of plants and soil nitrogen might allow the characteristics of N transformation in an ecosystem to be detected. We tested the measurement of δ15N for its ability to provide a picture of N dynamics at the ecosystem level by doing a simple comparison of δ15N between soil N pools and plants, and by using an existing model. δ15N of plants and soil N was measured together with foliar nitrate reductase activity (NRA) and the foliar NO3– pool at two sites with different nitrification rates in a temperature forest in Japan. δ15N of plants was similar to that of soil NO3– in the high-nitrification site. Because of high foliar NRA and the large foliar NO3– pool at this site, we concluded that plant δ15N indicated a great reliance of plants on soil NO3– there. However, many δ15N of soil N overlapped each other at the other site, and δ15N could not provide definitive evidence of the N source. The existing model was verified by measured δ15N of soil inorganic N and it explained the variations of plant δ15N between the two sites in the context of relative importance of nitrification, but more information about isotopic fractionations during plant N uptake is required for quantitative discussions about the plant N source. The model applied here can provide a basis to compare δ15N signatures from different ecosystems and to understand N dynamics.

Winter climate change in plant–soil systems: summary of recent findings and future perspectives

The winter climate is changing in many parts of the world, and it is predicted that winter climate change will modify the structure and function of plant–soil systems. An understanding of these changes and their consequences in terrestrial ecosystems requires knowledge of the linkage between above- and below-ground components as well as the species interactions found in plant–soil systems, which have important implications for biogeochemical cycles. However, winter climate-change studies have focused on only a part of the ecosystem or ecological process. We summarize here recent findings related to the effects of winter climate and its changes on soil nitrogen (N) dynamics, greenhouse gas (N2O) emissions from the soil, N use by individual plants, vegetation development, and interactions between vegetation and pollinators to generate an integrative understanding of the response of the plant–soil system to winter climate change. This review indicates that the net effects on plants, soil microbes, pollinators, and the associated biogeochemical cycles are balanced among several processes and are highly variable depending on the context, such as the target species/functional group, original winter condition of the habitat, and type of climate change. The consequences of winter climate change for species interactions among plants, associated animals, and biogeochemical cycles are largely unknown. For further research, a large-scale comparative study to measure ecosystem-level functions is important, especially in less-cold ecosystems.

Seasonal changes in nitrate use by three woody species: the importance of the leaf-expansion period

Seasonal changes in plant NO3−-N use were investigated by measuring leaf nitrate reductase activity (NRA), leaf N concentration, and leaf expansion in one evergreen woody species (Quercus glauca Thunb.) and two deciduous woody species [Acer palmatum Thunb. and Zelkova serrata (Thunb.) Makino]. Leaf N concentration was highest at the beginning of leaf expansion and decreased during the expansion process to a steady state at the point of full leaf expansion in all species. The leaf NRA of all species was very low at the beginning of leaf expansion, followed by a rapid increase and subsequent decrease. The highest leaf NRA was observed in the middle of the leaf-expansion period, and the lowest leaf NRA occurred in summer for all species. Significant positive correlations were detected between leaf NRA and leaf expansion rates, while leaf N concentrations were negatively correlated with leaf area. In the evergreen Q. glauca, the N concentration in current buds increased before leaves opened; concurrently, the N concentration in 1-year-old leaves decreased by 25%. Our results show that the leaf-expansion period is the most important period for NO3−-N assimilation by broadleaf tree species, and that decreases in leaf N concentration through the leaf-expansion period are at least partly compensated for by newly assimilated NO3−-N in current leaves.

Monitoring of post-fire forest recovery under different restoration modes based on time series Landsat data

Abstract Forest fire is a common disturbance factor, especially in boreal forests. The detection of forest disturbance and monitoring of post-fire forest recovery are crucial to both ecological research and forest management. The Greater Hinggan Mountain area of China is rich in forest resources, but also has a high incidence of forest fires. After the most serious forest fire in the history of P. R. China, three restoration modes were adopted for local forest recovery, namely artificial regeneration, natural regeneration and artificial promotion. In this study, based on time series Landsat data, we proposed to detect the disturbance and monitor the post-fire forest recovery under the three restoration modes. Disturbance Index (DI) was proven to be an effective approach for the detection and monitoring. The results indicated that the forest under natural regeneration achieved a totally different recovery process with those under the other two modes. In combination with the field survey data analysis, the availability of different remote sensing indices and applicability of the three restoration modes were evaluated and compared. It could provide significant suggestions for local post-fire forest management.

Plant physiological responses to hydrologically mediated changes in nitrogen supply on a boreal forest floodplain: a mechanism explaining the discrepancy in nitrogen demand and supply

A discrepancy between plant demand and soil supply of nitrogen (N) has been observed in early successional stages of riparian vegetation in interior Alaska. We hypothesized that a hydrologically mediated N supply serves as a mechanism to balance this apparent deficiency of plant N supply. To test this hypothesis, we conducted a tracer experiment and measured the activity of nitrate reductase (NRA) over the summer on the early successional floodplain of the Tanana River in interior Alaska. Isotopic data showed that river-/groundwater was an important source of plant water and that hyporheic N could be absorbed by early successional species. Plant NRA generally increased as the growing season progressed, and NO3−-N availability increased. Both Salix interior Rowlee and Populus balsamifera L. used NO3−-N, and the timing of plant NRA relative to river discharge chemistry and soil NO3−-N concentrations, strongly suggest that plant uptake of NO3−-N is coupled to fluvial dynamics. Moreover, this physiological function helps explain the apparent discrepancy between N mineralization and productivity in these riparian ecosystems, and demonstrates that plant N availability in these riparian stands is under significant hydrological control.

Estimation of Vegetation Coverage in Semi-arid Sandy Land Based on Multivariate Statistical Modeling Using Remote Sensing Data

The estimation of vegetation coverage is essential in the monitoring and management of arid and semi-arid sandy lands. But how to estimate vegetation coverage and monitor the environmental change at global and regional scales still remains to be further studied. Here, combined with field vegetation survey, multispectral remote sensing data were used to estimate coverage based on theoretical statistical modeling. First, the remote sensing data were processed and several groups of spectral variables were selected/proposed and calculated, and then statistically correlated to measured vegetation coverage. Both the single- and multiple-variable-based models were established and further analyzed. Among all single-variable-based models, that is based on Normalized Difference Vegetation Index showed the highest R (0.900) and R2 (0.810) as well as lowest standard estimate error (0.128024). Since the multiple-variable-based model using multiple stepwise regression analysis behaved much better, it was determined as the optimal model for local coverage estimation. Finally, the estimation was conducted based on the optimal model and the result was cross-validated. The coefficient of determination used for validation was 0.867 with a root-mean-squared error (RMSE) of 0.101. The large-scale estimation of vegetation coverage using statistical modeling based on remote sensing data can be helpful for the monitoring and controlling of desertification in arid and semi-arid regions. It could serve for regional ecological management which is of great significance.

Mapping a burned forest area from Landsat TM data by multiple methods

Forest fire is one of the dominant disturbances in boreal forests. It is the primary process responsible for organizing the physical and biological attributes of the boreal biome, shaping landscape diversity and influencing biogeochemical cycles. The Greater Hinggan Mountain of China is rich in forest resources while suffers from a high incidence of forest fires simultaneously. In this study, focusing on the most serious forest fire in the history of P. R. China which occurred in this region, we made use of two Landsat-5 TM (Thematic Mapper) images, and proposed to map the overall burned area and burned forest area by multiple methods. During the mapping, the fire perimeter, as well as rivers, roads and urban areas were first extracted and masked visually, and then four indices of Normalized Difference Vegetation Index, Enhanced Vegetation Index, Vegetation Fractional Cover and Disturbance Index were calculated. For each index, the optimal threshold for separating burned from unburned forest area was determined using their histograms. For comparison, threshold segmentation using single-band reflectance was performed, in addition to a Maximum Likelihood Classifier (MLC) based supervised classification of all features and forest area alone; their accuracies were also evaluated and analysed. Among all the methods compared here, mapping by EVI threshold segmentation proved to be optimal by the comparisons of overall accuracy (99.78%) and the kappa coefficient (0.9946). Finally, the calculated burned area and burned forest area were compared with the values from official statistics. Compared with the classical methods used to report official statistics on burned areas, the remote sensing-based mapping is more objective and efficient, less labour- and time-consuming, and more repeatable.

Nitrate is an important nitrogen source for Arctic tundra plants

Significance How terrestrial plants use N and respond to soil N loading is central to evaluating and predicting changing ecosystem structure and function with climate warming and N pollution. Here, evidence from NO3− in plant tissues has uncovered the uptake and assimilation of soil NO3− by Arctic tundra plants, which has long been assumed negligible. Soil NO3− contributed about one-third of the bulk N used by tundra plants of northern Alaska. Accordingly, the importance of soil NO3− for tundra plants should be considered in future studies on N and C cycling in Arctic ecosystems where C sequestration is strongly determined by N availability. Plant nitrogen (N) use is a key component of the N cycle in terrestrial ecosystems. The supply of N to plants affects community species composition and ecosystem processes such as photosynthesis and carbon (C) accumulation. However, the availabilities and relative importance of different N forms to plants are not well understood. While nitrate (NO3−) is a major N form used by plants worldwide, it is discounted as a N source for Arctic tundra plants because of extremely low NO3− concentrations in Arctic tundra soils, undetectable soil nitrification, and plant-tissue NO3− that is typically below detection limits. Here we reexamine NO3− use by tundra plants using a sensitive denitrifier method to analyze plant-tissue NO3−. Soil-derived NO3− was detected in tundra plant tissues, and tundra plants took up soil NO3− at comparable rates to plants from relatively NO3−-rich ecosystems in other biomes. Nitrate assimilation determined by 15N enrichments of leaf NO3− relative to soil NO3− accounted for 4 to 52% (as estimated by a Bayesian isotope-mixing model) of species-specific total leaf N of Alaskan tundra plants. Our finding that in situ soil NO3− availability for tundra plants is high has important implications for Arctic ecosystems, not only in determining species compositions, but also in determining the loss of N from soils via leaching and denitrification. Plant N uptake and soil N losses can strongly influence C uptake and accumulation in tundra soils. Accordingly, this evidence of NO3− availability in tundra soils is crucial for predicting C storage in tundra.

Nitrate-use traits of understory plants as potential regulators of vegetation distribution on a slope in a Japanese cedar plantation

Background and aimsPlant physiological traits and their relation to soil N availability was investigated as regulators of the distribution of understory shrub species along a slope in a Japanese cedar (Cryptomeria japonica) plantation in central Japan.MethodsAt the study site, previous studies demonstrated that both net and gross soil nitrification rates are high on the lower slope and there are dramatic declines in different sections of the slope gradient. We examined the distributions of understory plant species and their nitrate (NO3−-N) use traits, and compared the results with the soil traits.ResultsOur results show that boundaries between different dominant understory species correspond to boundaries between different soil types. Leucosceptrum stellipilum occurs on soil with high net and gross nitrification rates. Hydrangea hirta is dominant on soil with high net and low gross nitrification rates. Pieris japonica occurs on soil with very low net and gross nitrification rates. Dominant understory species have species-specific physiological traits in their use of NO3−-N. Pieris japonica lacks the capacity to use NO3−-N as a N source, but other species do use NO3−-N. Lindera triloba, whose distribution is unrelated to soil NO3−-N availability, changes the extent to which it uses NO3−-N in response to soil NO3−-N availability.ConclusionsOur results indicate that differences in the physiological capabilities and adaptabilities of plant species in using NO3−-N as a N source regulate their distribution ranges. The identity of the major form of available soil N is therefore an environmental factor that influences plant distributions.

Extraction of burned forest area in the Greater Hinggan Mountain of China based on Landsat TM data

Forest fire is a dominant disturbance regime in boreal forests. The Greater Hinggan Mountain of China is rich in forest resources, but also in a high incidence of forest fires. Aiming the most serious forest fire since the founding of China which happened on May 6th, 1987 in this area, based on two scene Landsat-5 TM images, we proposed to extract the burnt area and burned forest area in this study. During the extraction, the fire perimeter as well as the rivers, roads and building area were first extracted and masked out by visual interpretation, then four indexes of NDVI, EVI, VFC and DI were calculated and their optimal thresholds for separating burned and unburned forest area were determined according to their histograms and extraction accuracies. The extraction by EVI threshold segmentation was proved to be the optimal one based on the comparison of overall accuracy (99.78%) and kappa coefficient (0.9946). Finally the extracted burnt area and burned forest area were compared with values from official statistics. The remote sensing based extraction which are more objective and efficient, less labor-consuming and repeatable appeared to be more reliable.