Assessing the effects of drought on rainfed maize water footprints based on remote sensing approaches.

BACKGROUND: Drought affects the characteristics of water use during crop production and so quantitatively evaluating the impacts is important. However, it remains unclear how crop water use responds to drought. To address this gap, water footprint (WF) and standardized precipitation evapotranspiration index (SPEI) were calculated by remote sensing approaches to assess the effects of drought on crop water use. Rainfed maize is the most important crop in Jilin Province, and its growth and water use are more susceptible to drought. The present study explored not only the impact of growing season drought on the maize WF values in Jilin Province, but also the response of WF values to drought at different time scales. RESULTS: Spatially, 72.94% of the WFblue pixels showed a non-significant increase, and the WFgreen in 68% pixels decreased significantly, being mainly concentrated in the middle region. Furthermore, the pixels affected by monthly time scale drought were mainly in the middle region, whereas the pixels affected by annual time scale drought were mainly in the western region. CONCLUSION: Drought not only affected on the source and structure of agricultural water consumption, but also had different effects on WF values at different time scale. These effects had obvious spatial differences. The present study systematically explored the effects of drought on the WF values for rainfed maize in different climate regions and a consideration of these effects could provide valuable information on rainfed maize growth and the agricultural water use response to a changing climate. © 2023 Society of Chemical Industry.

Identification of light nonaqueous phase liquid groundwater contamination source based on empirical mode decomposition and deep learning.

The simulation optimization method was used to the identification of light nonaqueous phase liquid (LNAPL) groundwater contamination source (GCS) with the help of a hypothetical case in this study. When applying the simulation optimization method to identify GCS, it was a common technical means to establish surrogate model for the simulation model to participate in the iterative calculation to reduce the calculation load and calculation time. However, it was difficult for a single modeling method to establish surrogate model with high accuracy for the LNAPL contamination multiphase flow simulation model (MFSM). To give full play to advantages of single surrogate model and improve the accuracy of the surrogate model to the MFSM, a combination of deep belief neural network (DBNN) and long short-term memory (LSTM) neural network was used to establish artificial intelligence ensemble surrogate model (AIESM) for the MFSM. At the same time, to reduce the influence of noise in observed concentrations on the accuracy of the identification results, empirical mode decomposition (EMD) and wavelet analysis methods were used to denoise the observed concentrations, and their noise reduction effects were compared. The observed concentrations with better noise reduction effect and the observed concentrations without denoising were used to construct the objective function, and constraints of the optimization model were determined meanwhile. Then, the objective function and the constraints were integrated to build the optimization model to identify GCS and simulation model parameters. Applying the AIESM instead of the MFSM to embed in the optimization model and participate in the iterative calculation. Finally, the genetic algorithm (GA) was used to solve the optimization model to obtain the identification results of GCS and simulation model parameters. The results showed that compared with the single DBNN and LSTM surrogate models, AIESM obtained the highest accuracy and could replace the MFSM to participate in the iterative calculation, thereby reducing the calculation load and calculation time by more than 99%. Comparing with the wavelet analysis, EMD could reduce the noise in the concentrations more effectively, improved the accuracy of the approximated concentrations to the actual values, and increased the accuracy of the GCSs identification results by 1.45%.

Comparative analysis of groundwater contaminant sources identification based on simulation optimization and ensemble Kalman filter.

The location and release history of groundwater contaminant sources (GCSs) are usually unknown after groundwater contamination is detected, thereby greatly hindering the design of contamination remediation schemes and contamination risk assessments. Many previous studies have used prior information such as the observed contaminant concentrations (OCC) to obtain information of GCSs, and various methods have been proposed for identifying GCSs, including simulation optimization (S/O) and ensemble Kalman filter (EnKF) methods. For the first time, the present study compared the suitability of the S/O and EnKF methods for GCSs identification based on two case studies by specifically considering the calculation time and effectiveness of GCS identification. The results showed that EnKF could reduce the calculation time required by more than 62% compared with S/O. However, the time saved did not compensate for the poor accuracy of the GCSs identification results. When the simulated contaminant concentrations (SCC) were used for GCSs identification, the MRE of the identification results with the S/O and EnKF methods were 2.79% and 5.09% in case one, respectively, and were 4.75% and 6.72% in case two. When the OCC were used for GCSs identification, the MRE of the identification results with the S/O and EnKF methods were 27.77% and 110.74% in case one, respectively, and 27.53% and 60.61% in case two. The identification results obtained using the EnKF method were not credible and the superior performance of the S/O method was obvious, thereby indicating that the EnKF method is much less suitable for actual GCSs identification compared with the S/O method.

Suitable chemical fertilizer reduction mitigates the water footprint of maize production: evidence from Northeast China.

Long-term excessive use of chemical fertilizer has led to water environmental degradation. Reducing chemical fertilizer use in crop production has become a consensus, and the effects of chemical fertilizer reduction on yield, water consumption and water environment urgently need to be explored. A field experiment including four fertilization treatments: normal fertilizer application (NFA), 15%, 30% and 45% fertilizer reduction (FR) was conducted and the water footprint (WF) was used as an indicator to explore how the chemical fertilizer reduction affected the maize WF. The results showed that the blue, green and total WFs of maize in the 45% FR and NFA treatments were larger than those in the 30% FR and 15% FR treatments in 2018 and 2019. The grey WFs of maize in the NFA treatment were the highest in 2018 and 2019, exhibiting a trend that the grey WFs in the NFA treatment >15% FR treatment >30% FR treatment >45% FR treatment in 2018 and those in the NFA treatment >45% FR treatment >30% FR treatment >15% FR treatment in 2019. The optimal treatment was the 15-30% FR compared with the current fertilization, in which the total WF of maize can be minimized and the maize yield can be maximized at the same time. Precipitation had a wide-ranging impact on the yield and WF of maize, especially the amount, intensity and interval of rainfall, which had an evident impact on the grey WF. This study is expected to provide a data foundation for reducing chemical fertilizer and improving water and fertilizer use efficiency in maize production.

Effects of exogenous N and endogenous nutrients on alpine tundra litter decomposition in an area of high nitrogen deposition.

The effects of N deposition on the C and N cycles via altered litter decomposition rates are an important aspect of global environmental change. The Changbai Mountain region experienced a high N deposition (2.7 g·m-2·year-1 in 2015) and corresponding expansion of Deyeuxia purpurea into the alpine tundra, resulting in changes in endogenous nutrients. However, the relative contributions of the N deposition and endogenous litter nutrients to litter decompositions remain unclear. Therefore, a 5-year N addition and 2-year litter decomposition experiments were conducted. Exogenous N reduced the remaining litter mass of Rhododendron aureum at the early stage (30-240 d) by promoting soluble sugar release, and increased it at the late stage (360-720 d) by suppressing lignin release and decreasing soil microbial community and enzyme activity. A higher proportion of D. purpurea litter (representing higher N, lower lignin, and C:N ratio) decreased remaining litter mass and increased net N release. Exogenous N decreased decomposition rate from 0.32 to 0.21 and net N release from 34% to 24%, whereas litter compositions increased decomposition rates from 0.32 to 0.69 and net litter N release from 34% to 69%. Endogenous litter nutrients directly explained 62% and 40% of the litter decomposition and net N release variables, respectively, whereas exogenous N indirectly explained 12% and 9%, respectively. Thus, we infer that the reductions in C and N storage following D. purpurea expansion may offset the increases of C and N storage under N deposition and the expansion of D. purpurea has a potential long-term negative impact on the ability of tundra plants to sequester C and N in the alpine tundra of the Changbai Mountains. These findings highlight how shifting plant expansion, through changes endogenous nutrients, can influence tundra litter decomposition and C and N storage responses to N deposition.

Multi-source data-based spatial variations of blue and green water footprints for rice production in Jilin Province, China.

Rice production consumes more water than the production of other crop species due to the specific growth requirements of this species. Accurately accounting for water consumption during rice production and analyzing the spatio-temporal changes in water consumption are thus necessary. Using the water footprint (WF) as an indicator and combining data from multi-sources, this paper explored the regional differences in rice WFs in Jilin Province at a spatial resolution of 1 km. The results showed that the blue WF was always larger than the green WF, and the total, green and blue WFs were lowest during the humid year. The pixels with high values of total, green and blue WFs were mainly distributed in the eastern region of Jilin Province. Compared with the traditional estimation of the WF based on the data of administrative regions, RS techniques can overcome the administrative boundary and provide near real-time data concerning specific agricultural parameters to extract more accurate results for WF models. The combination of RS data and statistical, observational, and survey data can thus overcome the limitations of weather conditions affecting RS, reduce the incorporation of parameters, and estimate WFs quickly and accurately. This study provides a framework to evaluate crop WFs with multi-source data.

Non-Structural Carbohydrate Storage Strategy Explains the Spatial Distribution of Treeline Species.

Environmental factors that drive carbon storage are often used as an explanation for alpine treeline formation. However, different tree species respond differently to environmental changes, which challenges our understanding of treeline formation and shifts. Therefore, we selected Picea jezoensis and Betula ermanii, the two treeline species naturally occurring in Changbai Mountain in China, and measured the concentration of non-structural carbohydrates (NSC), soluble sugars and starch in one-year-old leaves, shoots, stems and fine roots at different elevations. We found that compared with P. jezoensis, the NSC and soluble sugars concentrations of leaves and shoots of B. ermanii were higher than those of P. jezoensis, while the starch concentration of all the tissues were lower. Moreover, the concentration of NSC, soluble sugars and starch in the leaves of B. ermanii decreased with elevation. In addition, the starch concentration of B. ermanii shoots, stems and fine roots remained at a high level regardless of whether the soluble sugars concentration decreased. Whereas the concentrations of soluble sugars and starch in one-year-old leaves, shoots and stems of P. jezoensis responded similarly changes with elevation. These findings demonstrate that compared with P. jezoensis, B. ermanii has a higher soluble sugars/starch ratio, and its shoots, stems and fine roots actively store NSC to adapt to the harsh environment, which is one of the reasons that B. ermanii can be distributed at higher altitudes.

Soil Mesofauna Respond to the Upward Expansion of Deyeuxia purpurea in the Alpine Tundra of the Changbai Mountains, China.

Deyeuxia purpurea, a low-altitude species, has been expanding upwards into alpine tundra, and this upward expansion is causing serious ecological consequences. However, few studies have been performed regarding its effects on soil faunal communities. We examine how the upward expansion of D. purpurea affects the abundance, richness, and diversity of soil mesofauna, and evaluate how different taxa of soil mesofauna respond to the upward expansion of D. purpurea in the alpine tundra of Changbai Mountains, northeast China. A total of 128 soil mesofaunal samples were collected from four treatments, namely high upward expansion (HU), medium upward expansion (MU), low upward expansion (LU), and native plant habitats (NP). The results revealed that the abundance of soil mesofauna was increased with the rise of D. purpurea upward expansion, and the taxonomic composition varied with the different levels of D. purpurea upward expansion in the alpine tundra of the Changbai Mountains. No unique taxa were collected in the native plant habitats, and the upward expansion of D. purpurea promoted the colonization of predatory invertebrates. Isotomidae and Gamasida responded positively to the herbaceous plant upward expansion, and thus they were considered to be a positive indicator of upward expansion. Hypogastruridae and Enchytraeidae responded relatively negatively, while Oribatida, Actinedida, and Pseudachorutidae had ambivalent responses to the upward expansion. Overall, the abundance of soil mesofauna can indicate the levels of the upward expansion of D. purpurea. Soil mesofaunal guild characteristics were altered by the upward expansion. The different taxa of soil mesofauna responded to herbaceous plants' upward expansion to various degrees. Therefore, this study provide evidence supporting the fact that the abundance of soil mesofauna can indicate the levels of upward expansion of D. purpurea, but the responses of soil mesofauna to the upward expansion of D. purpurea differ among their taxa.

Vegetation Heterogeneity Effects on Soil Macro-Arthropods in an Alpine Tundra of the Changbai Mountains, China.

The harsh environmental conditions in alpine tundra exert a significant influence on soil macro-arthropod communities, yet few studies have been performed regarding the effects of vegetation heterogeneity on these communities. In order to better understand this question, a total of 96 soil macro-arthropod samples were collected from four habitats in the Changbai Mountains in China, namely, the Vaccinium uliginosum habitat, Sanguisorba sitchensis habitat, Rhododendron aureum habitat, and Deyeuxia angustifolia habitat. The results revealed that the taxonomic composition of the soil macro-arthropods varied among the habitats, and that dissimilarities existed in these communities. The abundance, richness and diversity in the D. angustifolia habitat were all at their maximum during the sampling period. The vegetation heterogeneity affected the different taxa of the soil macro-arthropods at various levels. In addition, the vegetation heterogeneity had direct effects not only on soil macro-arthropod communities, but also indirectly impacted the abundance, richness and diversity by altering the soil fertility and soil texture. Overall, our results provide experimental evidence that vegetation heterogeneity can promote the abundance, richness and diversity of soil macro-arthropods, yet the responses of soil macro-arthropods to vegetation heterogeneity differed among their taxa.

The Changbai Alpine Shrub Tundra Will Be Replaced by Herbaceous Tundra under Global Climate Change.

Significant replacement of shrub species by herbaceous species has been observed in the Changbai alpine tundra zone, China, since the 1990s. This study used plot surveys to analyze variations in the spatial distribution of dominant plants and to ascertain the changing mechanisms of dominant species in the alpine tundra zone. We found that the two previously dominant shrubs, Rhododendron chrysanthum and Vaccinium uliginosum, differed markedly in their distribution characteristics. The former had the highest abundance and the lowest coefficient of variation, skewness, and kurtosis, and the latter showed the opposite results, while the six herb species invaded had intermediate values. R. chrysanthum still had a relatively uniform distribution, while the herbaceous species and V. uliginosum had a patch distribution deviating from the normal distribution in the tundra zone. Micro-topography and slope grade had stronger effects on the spatial distribution of the eight plant species than elevation. Herbs tended to easily replace the shrubs on a semi-sunny slope aspect, steep slope, and depression. Overall, the dominance of dwarf shrubs declined, while the herbaceous species have encroached and expanded on the alpine tundra zone and have become co-dominant plant species. Our results suggest that various micro-topographic factors associated with variations in climatic and edaphic conditions determine the spatial distribution of plants in the alpine tundra zone. Future climate warming may cause decreased snow thickness, increased growing season length, and drought stress, which may further promote replacement of the shrubs by herbs, which shows retrogressive vegetation successions in the Changbai alpine tundra zone. Further studies need to focus on the physio-ecological mechanisms underlying the vegetation change and species replacement in the alpine tundra area under global climate change.

Characteristics of the water footprint of rice production under different rainfall years in Jilin Province, China.

BACKGROUND: Rice is a special crop, and its production differs from that of other crops because it requires a thin layer of water coverage for a long period. The calculation of the water footprint of rice production should differ from that of other crops owing to the rice growing process. This study improved the calculation of blue and grey water footprints of rice production and analyzed the variations in the water footprints for rice production under different rainfall years in Jilin Province. RESULTS: In the drought year, the green water footprint was the lowest and the blue water footprint was the highest among the three years, while in the humid year, the green water footprint was the highest and the blue water footprint was not the lowest. The areas with higher water footprints were found in the east and west regions of Jilin Province, while the areas with lower water footprints were found in the middle east and middle regions of Jilin Province. CONCLUSION: Blue water was the primary water resource for rice production, although more precipitation provided the highest green water in the humid year; also, the spatial distributions of water footprints were not the same under different rainfall years. © 2017 Society of Chemical Industry.

CO2 emissions from the 2010 Russian wildfires using GOSAT data.

In the summer of 2010, more than 6 hundred wildfires broke out in western Russia because of an unprecedented intense heat wave that resulted from strong atmospheric blocking. The present study evaluated the CO2 emissions using GOSAT (Greenhouse gases Observing SATellite) data from July 23 to August 18, 2010 for western Russia. The results demonstrated that the GOSAT CAI (Cloud and Aerosol Imager) was well-suited for the identification of smoke plumes and that the GOSAT FTS (Fourier-Transform Spectrometer) TIR (Thermal InfraRed) could be used to calculate the height of the plumes at approximately 800 hPa (1.58 km). Using GOSAT data, we estimated that the 2010 fires in western Russia emitted 255.76 Tg CO2. We also calculated the CO2 emissions by employing the Biomass Burning Model (BBM) for the same study site and obtained a similar result of 261.82-302.48 Tg CO2. The present study proposes a new method for the evaluation of CO2 emissions from a wildfire using remote sensing data, which could be used to improve the knowledge of the burning of biomass at a regional or a continental scale, to reduce the uncertainties in modeling greenhouse gases emissions, and to further understand how wildfires impact the atmospheric carbon cycle and global warming.

Field-based experimental water footprint study of sunflower growth in a semi-arid region of China.

BACKGROUND: Field-scale changes in the water footprint during crop growth play an important role in formulating sustainable water utilisation strategies. This study aimed to explore field-scale variation in the water footprint of growing sunflowers in the western Jilin Province, China, during a 3-year field experiment. The goals of this study were to (1) determine the components of the 'blue' and 'green' water footprints for sunflowers sown with water, and (2) analyse variations in water footprints and soil water balance under different combinations of temperature and precipitation. Specific actions could be adopted to maintain sustainable agricultural water utilisation in the semi-arid region based on this study. RESULTS: The green, blue, and grey water footprints accounted for 93.7-94.7%, 0.4-0.5%, and 4.9-5.8%, respectively, of the water footprint of growing sunflowers. The green water footprint for effective precipitation during the growing season accounted for 58.8% in a normal drought year but 48.2% in an extreme drought year. When the effective precipitation during the growing season could not meet the green water use, a moisture deficit arose. This increase in the moisture deficit can have a significant impact on soil water balance. CONCLUSION: Green water was the primary water source for sunflower growth in the study area, where a scarcity of irrigation water during sunflower growth damaged the soil water balance, particularly in years with continuous drought. The combination of temperature and precipitation effected the growing environment, leading to differences in yield and water footprint. The field experiments in this area may benefit from further water footprint studies at the global, national and regional scale. © 2016 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The long-term effects of planting and harvesting on secondary forest dynamics under climate change in northeastern China.

Unlike the virgin forest in the Changbaishan Nature Reserve in northeastern China, little research on a landscape scale has been conducted on secondary forests in the region under conditions of a warming climate. This research was undertaken in the upper Hun River region where the vegetation is representative of the typical secondary forest of northeastern China. The spatially explicit forest landscape model LANDIS was utilized to simulate the responses of forest restoration dynamics to anthropogenic disturbance (planting and harvesting) and evaluate the difference of the restoration process under continuation of current climatic conditions and climate warming. The results showed that: (1) The interaction of planting and harvesting has organizational scale effects on the forest. The combination of planting and harvesting policies has significant effects on the overall forest but not on individual species. (2) The area expansion of the historically dominant species Pinus koraiensis is less under climate warming than under continuation of current climatic conditions. These suggests that we should carefully take historically dominant species as the main focus for forest restoration, especially when they are near their natural distribution boundary, because they are probably less capable of successfully adapting to climate change.

Spatial pattern characteristics of water footprint for maize production in Northeast China.

BACKGROUND: Water footprint (WF) methodology is essential for quantifying total water consumption of crop production and making efficient water management policies. This study calculated the green, blue, grey and total WFs of maize production in Northeast China from 1998 to 2012 and compared the values of the provinces. This study also analyzed the spatial variation and structure characteristics of the WFs at the prefecture level. RESULTS: The annual average WF of maize production was 1029 m(3) per ton, which was 51% green, 21% blue and 28% grey. The WF of maize production was highest in Liaoning Province, moderate in Heilongjiang Province and lowest in Jilin Province. The spatial differences of the WFs calculated for the 36 major maize production prefectures were significant in Northeast China. There was a moderate positive spatial autocorrelation among prefectures that had similar WFs. Local indicator of spatial autocorrelation index (LISA) analysis identified prefectures with higher WFs in the southeast region of Liaoning Province and the southwest region of Heilongjiang Province and prefectures with lower WFs in the middle of Jilin Province. CONCLUSION: Spatial differences in the WF of maize production were caused mainly by variations in climate conditions, soil quality, irrigation facilities and maize yield. The spatial distribution of WFs can help provide a scientific basis for optimizing maize production distribution and then formulate strategies to reduce the WF of maize production.

Nitrogen deposition but not climate warming promotes Deyeuxia angustifolia encroachment in alpine tundra of the Changbai Mountains, Northeast China.

Vegetation in the alpine tundra area of the Changbai Mountains, one of two alpine tundra areas in China, has undergone great changes in recent decades. The aggressive herb species Deyeuxia angustifolia (Komarov) Y. L. Chang, a narrow-leaf small reed, was currently encroaching upon the alpine landscape and threatening tundra biota. The alpine tundra of the Changbai Mountains has been experiencing a warmer climate and receiving a high load of atmospheric nitrogen deposition. In this study, we aimed to assess the respective roles of climate warming and atmospheric nitrogen deposition in promoting the upward encroachment of D. angustifolia. We conducted experiments for three years to examine the response of D. angustifolia and a native alpine shrub, Rhododendron chrysanthum, to the conditions in which temperature and nitrogen were increased. Treatments consisting of temperature increase, nitrogen addition, temperature increase combined with nitrogen addition, and controls were conducted on the D. angustifolia communities with three encroachment levels (low, medium, and high levels). Results showed that 1) D. angustifolia grew in response to added nutrients but did not grow well when temperature increased. R. chrysanthum showed negligible responses to the simulated environmental changes. 2) Compared to R. chrysanthum, D. angustifolia could effectively occupy the above-ground space by increasing tillers and growing rapidly by efficiently using nitrogen. The difference in nitrogen uptake abilities between the two species contributed to expansion of D. angustifolia. 3) D. angustifolia encroachment could deeply change the biodiversity of tundra vegetation and may eventually result in the replacement of native biota, especially with nitrogen addition. Our research indicated that nutrient perturbation may be more important than temperature perturbation in promoting D. angustifolia encroachment upon the nutrient- and species-poor alpine tundra ecosystem in the Changbai Mountains.

[Influence of fire disturbance on aboveground deadwood debris carbon storage in Huzhong forest region of Great Xing'an Mountains, Northeast China].

Based on the field inventory data, the aboveground deadwood debris carbon storage under different fire severities was analyzed in Huzhong forest region of Great Xing' an Mountains. The results showed that the fire severity had a significant effect on aboveground deadwood debris carbon storage. The deadwood debris carbon storage was in the order of high-severity > low-severity > unburned in Larix gmelinii stands, and mixed conifer-broadleaf stands ( L. gmelinii and Betula platyphylla), and in the order of high severity > unburned > low-severity in B. platyphylla stands. Fire disturbance significantly changed the component percentage of the deadwood debris carbon storage. The component percentage of snags increased and litter decreased with the increasing fire severity. Logs and stumps did not change significantly with the increasing fire severity. The spatial variation of deadwood debris carbon storage in forests burned with low-severity fire was higher than that in unburned forests. The spatial variation of deadwood debris carbon storage with high-severity fires was lowest. This spatial variation needed to be accounted when calculating forest deadwood debris carbon storage.

Current and potential tree locations in tree line ecotone of Changbai Mountains, Northeast China: the controlling effects of topography.

Tree line ecotone in the Changbai Mountains has undergone large changes in the past decades. Tree locations show variations on the four sides of the mountains, especially on the northern and western sides, which has not been fully explained. Previous studies attributed such variations to the variations in temperature. However, in this study, we hypothesized that topographic controls were responsible for causing the variations in the tree locations in tree line ecotone of the Changbai Mountains. To test the hypothesis, we used IKONOS images and WorldView-1 image to identify the tree locations and developed a logistic regression model using topographical variables to identify the dominant controls of the tree locations. The results showed that aspect, wetness, and slope were dominant controls for tree locations on western side of the mountains, whereas altitude, SPI, and aspect were the dominant factors on northern side. The upmost altitude a tree can currently reach was 2140 m asl on the northern side and 2060 m asl on western side. The model predicted results showed that habitats above the current tree line on the both sides were available for trees. Tree recruitments under the current tree line may take advantage of the available habitats at higher elevations based on the current tree location. Our research confirmed the controlling effects of topography on the tree locations in the tree line ecotone of Changbai Mountains and suggested that it was essential to assess the tree response to topography in the research of tree line ecotone.

[Effects of sampling plot number on tree species distribution prediction under climate change].

Based on the neutral landscapes under different degrees of landscape fragmentation, this paper studied the effects of sampling plot number on the prediction of tree species distribution at landscape scale under climate change. The tree species distribution was predicted by the coupled modeling approach which linked an ecosystem process model with a forest landscape model, and three contingent scenarios and one reference scenario of sampling plot numbers were assumed. The differences between the three scenarios and the reference scenario under different degrees of landscape fragmentation were tested. The results indicated that the effects of sampling plot number on the prediction of tree species distribution depended on the tree species life history attributes. For the generalist species, the prediction of their distribution at landscape scale needed more plots. Except for the extreme specialist, landscape fragmentation degree also affected the effects of sampling plot number on the prediction. With the increase of simulation period, the effects of sampling plot number on the prediction of tree species distribution at landscape scale could be changed. For generalist species, more plots are needed for the long-term simulation.