An Enhanced Multiview Transformer for Population Density Estimation Using Cellular Mobility Data in Smart City

This paper addresses the problem of predicting population density leveraging cellular station data.As wireless communication devices are commonly used,cellular station data has become integral for estimating population figures and studying their movement,thereby implying significant contributions to urban planning.However,existing research grapples with issues pertinent to preprocessing base station data and the modeling of population prediction.To address this,we propose methodologies for preprocessing cellular station data to eliminate any irregular or redundant data.The preprocessing reveals a distinct cyclical characteristic and high-frequency variation in population shift.Further,we devise a multi-view enhancement model grounded on the Transformer(MVformer),targeting the improvement of the accuracy of extended time-series population predictions.Comparative experiments,conducted on the above-mentioned population dataset using four alternate Transformer-based models,indicate that our proposedMVformer model enhances prediction accuracy by approximately 30%for both univariate and multivariate time-series prediction assignments.The performance of this model in tasks pertaining to population prediction exhibits commendable results.

Effects of mepiquat chloride and plant population density on leaf photosynthesis and carbohydrate metabolism in upland cotton

Background Mepiquat chloride(MC)application and plant population density(PPD)increasing are required for modern cotton production.However,their interactive effects on leaf physiology and carbohydrate metabolism remain obscure.This study aimed to examine whether and how MC and PPD affect the leaf morpho-physiological characteristics,and thus final cotton yield.PPD of three levels(D1:2.25 plants·m^(-2),D2:4.5 plants·m^(-2),and D3:6.75 plants·m^(-2))and MC dosage of two levels(MC0:0 g·ha^(-2),MC1:82.5 g·ha^(-2))were combined to create six treatments.The dynamics of nonstructual carbohydrate concentration,carbon metabolism-related enzyme activity,and photosynthetic attributes in cotton leaves were examined during reproductive growth in 2019 and 2020.Results Among six treatments,the high PPD of 6.75 plants·m^(-2)combined with MC application(MC1D3)exhibited the greatest seed cotton yield and biological yield.The sucrose,hexose,starch,and total nonstructural carbohydrate(TNC)concentrations peaked at the first flowering(FF)stage and then declined to a minimum at the first boll opening(FBO)stage.Compared with other treatments,MC1D3 improved starch and TNC concentration by 5.4%~88.4%,7.8%~52.0% in 2019,and by 14.6%~55.9%,13.5%~39.7% in 2020 at the FF stage,respectively.Additionally,MC1D3 produced higher transformation rates of starch and TNC from the FF to FBO stages,indicating greater carbon production and utilization efficiency.MC1D3 displayed the maximal specific leaf weight(SLW)at the FBO stage,and the highest chlorophyll a(Chl a),Chl b,and Chl a+b concentration at the mid-late growth phase in both years.The Rubisco activity with MC1D3 was 2.6%~53.2% higher at the flowering and boll setting stages in both years,and 2.4%~52.7% higher at the FBO stage in 2020 than those in other treatments.These results provided a explanation of higher leaf senescence-resistant ability in MC1D3.Conclusion Increasing PPD coupled with MC application improves cotton yield by enhancing leaf carbohydrate production and utilization efficiency and delaying leaf senescence.

Overwintering parasitism is positively associated with population density in diapausing larvae of Chilo suppressalis

The suppression of overwintering population is essential in integrated pest management,but little is known about the biological mortality factors that reduce the overwintering density of Chilo suppressalis.Here,we examine the parasitism of overwintering larvae,and assume that key parasitoids strengthen the over-wintering population suppression.The natural parasitism incidence and related dominant parasitoids in overwintering larvae were investigated in two successive winters,in 2015-2016 and 2016-2017.Parasitism rates were also assessed in larvae collected from 15 different counties in 2016.The results showed that the parasitism incidence and dominant parasitoids in overwintering C.suppressalis larvae were significantly different for different sampling dates and sites.Overwintering larvae of C.suppressalis were mainly parasitized by Cotesia chilonis,and less often by Eriborus sinicus and Microgaster russata.Regression analysis indicated that the natural incidence of parasites in overwintering C.suppressalis larvae was positively correlated with the over-wintering larval density.The current work provides support for overwintering pest management strategies by showing the effectiveness of parasitoid communities as a bio-mortality factor for suppressing overwintering density.

A new approach on seismic mortality estimations based on average population density

This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the popu- lation density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.

Long-term monitoring data reveal effects of age,population density,and environmental aspects on hatching success of Common Cranes(Grus grus)

Facing climate and land use change,a species’ability to successfully adapt to changing environments is crucial for its survival.Extensive drainage and intensification of agriculture and forestry set wetlands and associated species at risk of population declines.The population of Common Cranes(Grus grus)has experienced considerable fluctuations over the last century.Despite increasing population numbers,hatching success seemed to have decreased over the last years.The aim of this study was to identify factors influencing hatching success and nest survival of Common Cranes based on analyses of long-term individual-based monitoring data from northeastern Germany and evaluate the species ability to adapt to changing environments.Hatching success decreased over the course of the study period from 0.75 to 0.55.Surprisingly,nest survival and hatching success did not vary across different nesting habitats,whereas factors such as female age,timing of nest initiation and breeding pair density were found to have significant effects on hatching success.Older females showed higher hatching success,even though the proportion of unhatched eggs was highest in females aged 20 years or older.Early nest initiation had a positive effect on hatching success.Water levels are more favorable early in the nesting season,whereas increasing evaporation with time causes water levels to decrease,granting easier access for predators.Independently of female age,hatching success decreased with increasing numbers of breeding pairs within a 2-km radius around a nesting site.High population densities intensify competition for resources and promote intraspecific interactions,affecting reproductive outcome negatively.This study gives first insights into mechanisms behind population regulation in Common Cranes,highlighting the importance of population dynamics and individual features.We suggest to further investigate density dependent effects including landscape and habitat features as well as reproductive success in terms of chick survival,since successfully raising juveniles is crucial for a species survival.

Experimental study of the interspecific competition between two sibling marine herbivorous rotifers in relation to food availability and initial population density

Our laboratory study concerns the competitive interaction between two marine rotifer species Bra- chionus plicatilis and Brachionus rotundiformis at five algal （ Nannochloropsis salina） concentrations （0.4＊106 to 32.4x106 cells/ml） and at four initial inoculation densities （numerically, 100% B. pli- catilis; 75% B. plicatilis and 25% B. rotundiforrnis, 50% each of the two species; 25% B. plicatilis and 75% B. rotundiformis and 100% B. rotundiforrnis. The initial biomass varied as 0.33 and 0.22 #g/ml for B. plicatilis and B. rotundiformis respectively. Experiments were performed at （25±1）C. Population densities were enumerated and the medium was changed daily up to 8 d in the ex- periment. At the lowest food level tested, B. rotundiformis formed superior competitor than B. plicatilis, regardless of starting inoculation density. Generally when the food concentrations in- creased, B. plicatilis showed a greater increase in biomass than B. rotundiforrnis. B. rotundiformis formed the largest in population growth, regardless of increasing food concentrations. When grown alone, B. plicatilis reached peak abundances of （1.311 5±0.028） and （137.5±0.014） μg/ml at low and high food densities respectively. The corresponding values of B. rotundiformis were 0.724 5±0.016 and 18.15±0.021. The adverse effects of B. rotundiforrnis on the peak abundances of B. plicatilis were observed at the lowest food level and higher initial density. The rate of population growth in controls varied from （0.792±0.162） to （1.482±0.132） ttm/d for B. plicatilis and （0.445~0.041） to （0.856±0.012） μm/d for B. rotundiformis, depending on food level. When both species were intro- duced together, low food levels favoured higher abundance of B. rotundiforrnis than B. plicatilis, suggesting that increased population density of the smaller B. rotundiforrnis was more successfull than larger B. plicatilis in brackish waters. Our work reveals that available food （type and quan- tity） along with starting inoculation density had significant effect on the interspecific competition between marine sibling rotifer species in zooplankton community structure.

An Assessment of the Marine Mammal Abundance and Population Density within the Ghanaian Offshore Construction Areas

The Gulf of Guinea region enjoined with the unique characteristics of the Guinea surface and underwater currents driving the upwelling season, besets the ecological importance of the area amidst growing offshore development. Though several attempts are being made to identify the various cetacean species inhabiting the area, little to no progress is made to under the animal population, their behaviour and distribution in the face of the growing threat. The study hence attempts to develop cetacean population and distribution estimation within Ghana’s offshore construction sites in the time frame of field development while emphasizing the effects of operations on animal behaviour and habitats, purpose at providing an understanding with the general behaviour of these mammals peculiar to the area and too what level the impact of change is having on distribution trends. The study finds the upwelling tends to suggest, strong animal presence in the area during feeding. Short-fin pilot whales were a dominant cetacean feature within the observed cetacean population estimated to have 160 (CV = 0.3728) presence. Findings suggest the strong biological importance, BIA (habitat, feeding and breeding), as well as operations drawing on animal curiosity, heightened animal vulnerability. Further studies are required to understand the temporal and spatial distributions patterns, while efforts are needed to ensure protected areas are established, animal surveillance and conservative attitudes are encouraged.

Spatiotemporal dynamics of population density in China using nighttime light and geographic weighted regression method

The distribution and dynamic changes of regional or national population data with long time series are very important for regional planning,resource allocation,government decision-making,disaster assessment,ecological protection,and other sustainability research.However,the existing population datasets such as LandScan and WorldPop all provide data from 2000 with limited time series,while GHS-POP only utilizes land use data with limited accuracy.In view of the limited remote sensing images of long time series,it is necessary to combine existing multi-source remote sensing data for population spatialization research.In this research,we developed a nighttime light desaturation index(NTLDI).Through the cross-sensor calibration model based on an autoencoder convolutional neural network,the NTLDl was calibrated with the same period Visible Infrared Imaging Radiometer Suite Day/Night Band(VIRS-DNB)data.Then,the geographically weighted regression method is used to determine the population density of China from 1990 to 2020 based on the long time series NTL.Furthermore,the change characteristics and the driving factors of China's population spatial distribution are analyzed.The large-scale,long-term population spatialization results obtained in this study are of great significance in government planning and decision-making,disaster assessment,resource allocation,and other aspects.

The change in population density from 2000 to 2010 and its influencing factors in China at the county scale

Studying the change in population distribution and density can provide important basis for regional development and planning. The spatial patterns and driving factors of the change in population density in China were not clear yet. Therefore, using the population census data in 2000 and 2010, this study firstly analyzed the change of population density in China and divided the change in all 2353 counties into 4 types, consisting of rapid increase, slow increase, slow decrease and rapid decrease. Subsequently, based on the partial least square （PLS） regression method, we recognized the significant factors （among 11 natural and social-economic factors） impacting population density change for the whole country and counties with different types of population change. The results showed that： （1） compared to the population density in 2000, in 2010, the population density in most of the counties （over 60%） increased by 21 persons per km2 on average, while the population density in other counties decreased by 13 persons per km2. Of all the 2353 counties, 860 and 589 counties respectively showed rapid and slow increase in population density, while 458 and 446 coun- ties showed slow and rapid decrease in population density, respectively. （2） Among the 11 factors, social-economic factors impacted population density change more significantly than natural factors. The higher economic development level, better medical condition and stronger communication capability were the main pull factors of population increase. The dense population density was the main push factor of population decrease. These conclusions clarified the spatial pattern of population change and its influencing factors in China over the past 10 years and could provide helpful reference for the future population planning.

Spatio-Temporal Changes of Population Density and Urbanization Pattern in China(2000–2010)

Population distribution and their temporal variation are a direct proxy of urbanization. This study evaluates the population density variation of China between 2000 and 2010 at the township level by using the data of the fi fth and sixth national population censuses. The urbanization patterns of China in 2000 and 2010 are depicted based on the population densities at various levels and the urbanization process of China between 2000 and 2010 is then analyzed through a comparative approach. It also tries to visualize the population density dynamics and urbanization pattern variations of China at the township level.

Education Universalization,Rural School Participation,and Population Density

In many developing countries,low population density may be a major reason for low school participation in rural areas,and the problem is likely to worsen with rapid urbanization.However,few studies have investigated empirically the role of population density in rural education,especially the moderating effect of population density on the outcomes of education policies.This study aims to fill this gap in the literature.From 1999 through the early 2000s,China launched a set of major nationwide policies aimed at universalizing 9-year compulsory education in rural areas.Using difference-in-differences and triple difference strategies,we show that the policies significantly increased the probability of junior high school enrollment of rural children and,more importantly,these policies were more effective in densely populated regions.These findings confirm the imporance of population density to rural education.

Power-law multi-wave model for COVID-19 propagation in countries with nonuniform population density

Background: The purpose of our study is to develop a quite precise mathematical model which describes epidemics spread in a country with non-uniform population density. This model gives explanation of quite long duration of the peak of a respiratory infection such as the coronavirus disease 2019 (COVID-19).Methods: The theory of kinetic equations and fractal analysis are used in our mathematical model. According to our model, COVID-19 spreading takes the form of several spatio-temporal waves developing almost independently and simultaneously in areas with different population density. The intensity of each wave is described by a power-law dependence. The parameters of the dependence are determined by real statistical data at the initial stage of the disease spread.Results: The results of the model simulation were verified using statistical data for the Republic of Belarus. Based on the developed model, a forecast calculation was made at the end of May, 2020. It was shown that the epidemiological situation in the Republic of Belarus is well described by three waves, which spread respectively in large cities with the highest population density (the first wave), in medium-sized cities with a population of 50−200 thousands people (the second wave), in small towns and rural areas (the third wave). It was shown that a new wave inside a subpopulation with a lower density was born 20−25 days after the appearance of the previous wave. Comparison with actual data several months later showed that the accuracy of forecasting the total number of cases for a period of 3 months for total population in the proposed approach was approximately 3%.Conclusions: The high accuracy mathematical model is proposed. It describes the development of a respiratory epidemic in a country non-uniform population density without quarantine. The model is useful for predicting the development of possible epidemics in the future. An accurate forecast allows to correctly allocating available resources to effectively withstand the epidemic.

Understanding Urban Vitality from the Economic and Human Activities Perspective:A Case Study of Chongqing,China

The literature on urban vitality tends to focus on the built environment.This paper argues that some important processes in shaping vitality may be overlooked without examining the intensity and diversity of economic and human activities.Using newly developed spatial big data and adopting the methods of multi-indicator measurement and spatial analysis methods,we analyzed the pattern of urban vitality in Chongqing,a provincial city in western China and,on this basis,evaluated the creation and maintenance of urban vitality from the economic and human activities perspective.Our findings indicate that the impacts of economic and human activities are positive and significant.Among the three intensity and diversity indicators,economic intensity and population density show an effect on urban vitality stronger than that of economic diversity.However,economic diversity has the strongest superposition or interactive effect,and is thus an important foundation dynamic.The positive effect of population density on urban vitality is largely a result of Chongqing’s jobs-housing balance.The case of Chongqing highlights the importance of topographic features,historical inheritance,large-scale migration,and cultural activities in shaping the distinctive vitality pattern of a city.This study contends that the creation and maintenance of urban vitality can not be fully explained without incorporating the impacts of economic and human activities.It contributes to a comprehensive measurement of urban vitality and enriches its connotations.

Socio-economic vulnerability level in the Jeneberang watershed in Gowa Regency,South Sulawesi Province,Indonesia

Jeneberang watershed is vital,particularly for people living in Gowa Regency(South Sulawesi Province,Indonesia),who benefit from its many advantages.Landslides and floods occur every year in the Jeneberang watershed,so it is imperative to understand the socio-economic vulnerability of this region.This research aims to identify the vulnerability level of the Jeneberang watershed so that the government can prioritize areas with high vulnerability level and formulate effective strategies to reduce these the vulnerability.Specifically,this study was conducted in 12 districts located in the Jeneberang watershed.The primary data were collected from questionnaires completed by community members,community leaders,and various stakeholders,and the secondary data were from the Landsat satellite imagery in 2020,the Badan Push Statistic of Gowa Regency,and some governmental agencies.The socio-economic vulnerability variables were determined using the Multiple Criteria Decision Analysis(MCDA)method,and each variable was weighted and analyzed using the Geographical Information System(GIS).The study reveals that the levels of socio-economic vulnerability are affected by variables such as population density,vulnerable groups(disabled people,elderly people,and young people),road network and settlement,percentage of poor people,and productive land area in the Jeneberang watershed.Moreover,all of the 12 districts in the Jeneberang watershed are included in the medium vulnerability level,with the mean percentage of socio-economic vulnerability around 50.92%.The socio-economic vulnerability of Bajeng,Pallangga,and Somba Opu districts is categorized at high level,the socio-economic vulnerability of Bungaya,Parangloe,and Tombolo Pao districts is classified as medium level,and the remaining 6 districts(Barombong,Bontolempangan,Bontomarannu,Manuju,Parigi,and Tinggimoncong)are ranked as low socio-economic vulnerability.This study can help policy-makers to formulate strategy that contributes to the protection of biodiversity and sustainable development of the Jeneberang watershed,while improving disaster resilience and preparedness of the watershed.

Nutrient deficiency limits population development,yield formation,and nutrient uptake of direct sown winter oilseed rape

Direct-sowing establishment method has great significance in improving winter oilseed rape（Brassica napus L.） production and guaranteeing edible oil security in China. However, nutrient responses on direct sown winter oilseed rape（DOR） performance and population development dynamic are still not well understood. Therefore, five on-farm experiments were conducted in the reaches of the Yangtze River（RYR） to determine the effects of nitrogen（N）, phosphorus（P）, and potassium（K） deficiencies on population density, dry matter production, nutrient uptake, seed yield, and yield components of DOR plants. Four fertilization treatments included the balanced NPK application treatment（NPK, 180 kg N, 39.3 kg P, 100 kg K, and 1.8 kg borax ha–1） and three nutrient deficiency treatments based on the NPK treatment, i.e., –N, –P, and –K. The results indicated that DOR population density declined gradually throughout the growing season, especially at over-wintering and pod-development stages. Nutrient deficiency decreased nutrient concentration in DOR plants, limited dry matter production and nutrient uptake, and thereby exacerbated density reduction during plants growth. The poor individual growth and reduced population density together decreased seed yield in the nutrient deficiency treatment. Averaged across all the experiments, seed yield reduced 61% by N deficiency, 38.3% by P deficiency, and 14.4% by K deficiency. The negative effects of nutrient deficiency on DOR performances followed the order of –N–P–K, and the effects were various among different nutrient deficiencies. Although N deficiency improved DOR emergence, but it seriously limited dry matter production and nutrient uptake, which in turn led to substantial plants death and therefore resulted in a very low harvested density. The P deficiency significantly reduced initial density, limited plants growth, and exacerbated density reduction. The K deficiency mainly decreased individual growth and yield, but did not affect density dynamic. Our results highlighted the importance of balanced NPK application in DOR production, suggesting that management strategy of these nutrients should be comprehensively considered with an aim to build an appropriate population structure with balanced plant density and individual growth.

Multi-Location Investigation of Optimum Planting Density and Boll Distribution of High-Yielding Cotton (G.hirsutum L.) in Hubei Province,China

Cotton yield per unit ground area has stagnated for a dozen years in Hubei Province, China, although a series of new high- yielding varieties have been commercialized. A multi-location investigation was carried out in 2008 and 2009 in 13 counties to determine if increased planting population density （PPD） would break the stagnant yield. The results showed that significant differences among the fields existed in theoretical yield, PPD, and bolls per square meter （BPM）. The lowest yield of 1 641.1 kg ha-I was resulted from the lowest PPD of 1.7 plants m-2 and the lowest BPM of 71.8 bolls m-2, while the highest yield of 2 779.7 kg ha-~ was resulted from the highest PPD of 2.5 plants m-2, and the highest BPM of 129.4 bolls m-z. Plant mapping revealed that boll retention rate （BRR） was maintained over 30 or 40% for the first 17-18 fruiting branches （FBs） and decreased dramatically thereafter, rotten boll rate （RBR） decreased, but open boll rate （OBR） rose first and dropped later with rising FB from the bottom to the top. But BRR, RBR, and OBR were all dropped with the fruiting positions （FPs） extending outwards. The optimum range of plant density would be 2-3 plants m-2 and the proper individual plant structure would be 16-19 FBs with 5-7 FPs for cotton production in Hubei Province.

Topographic and lithologic controls behind mountain depopulation in Zlatibor District(Western Serbia)

Mountain depopulation is a worldwide phenomenon observed in all continents. It has varied socio-economic reasons;among others, the low profitability of traditional agriculture, the better job possibilities and the higher level of services in urban settlements. However, it is often recognized that depopulation is related to natural factors such as elevation, slope or lithology. It is also observed that protected areas are frequently established in depopulated mountain regions. Their primary aim is the conservation of nature, but they may help tourism development as well. Tourism, in turn, may slow down or even reverse the process of depopulation. In this study, we investigate the impact of topographic and lithologic factors, namely of karst settings, on mountain demographic processes and the relationship of protected areas and tourism through the example of the northern part of Zlatibor District(Western Serbia). The study area is characterized by mountains and hills at elevations from 200 to 1600 m a.s.l. Our aim is to find GIS-based statistical relationships between topographic, lithologic factors and demographic characteristics. In this area, mountain depopulation started after WWII, and weproved that this process was strongly controlled by topographic factors. The higher and more dissected the area, the more significant is the decrease of the population and the more advanced is the ageing. As a result, population density contrasts are much more pronounced now than 70 years ago. After WWII, depopulation and ageing became gradually more serious on karstic terrains than on non-karst. However, by using compound topographic and lithologic types, we proved that it is not the effect of karst, but the effect of topography. The flow of population from hills and mountains to valleys and basins are closely related to the restructuring of the economic sectors. At present, for the study area, the development of tourism is unequivocally naturebased and connected to protected areas, namely to Tara National Park, Zlatibor Nature Park and ?argan–Mokra Gora Nature Park. In this paper, we also demonstrate how lithology influences tourism possibilities. The leading role of Zlatibor in tourism development is largely thanks to its favourable position on a main transit route.

Classification of densities and characteristics of curve of population centers in China by GIS

In this paper, with the spatial analysis functions in ArcGIS and the county-level census data of 2000 in China, the population density map was divided and shown by classes, meanwhile, the map system of population distribution and a curve of population centers were formed; in accordance with the geographical proximity principle, the classes of population densities were reclassified and a population density map was obtained which had the spatial clustering characteristic. The multi-layer superposition based on the population density classification shows that the population densities become denser from the Northwest to the Southeast; the multi-layer clustering phenomenon of the Chinese population distribution is obvious, the populations have a water-based characteristic gathering towards the rivers and coastlines. The curve of population centers shows the population densities transit from the high density region to the low one on the whole, while in low-density areas there are relatively dense areas, and in high-density areas there are relatively sparse areas. The reclassification research on the population density map based on the curve of population centers shows that the Chinese population densities can be divided into 9 classes, hereby, the geographical distribution of Chinese population can be divided into 9 type regions： the concentration core zone, high concentration zone, moderate concentration zone, low concentration zone, general transitional zone, relatively sparse area, absolute sparse area, extreme sparse area, and basic no-man＇s land. More than 3/4 of the population of China is concentrated in less than 1/5 of the land area, and more than half of the land area is inhabited by less than 2% of the population, the result reveals a better space law of China＇s population distribution.

Population distribution and threats to sustainable management of selected non-timber forest products in tropical lowland rainforests of south western Nigeria

Uncontrolled harvesting of non-timber forest products （NTFPs） poses a serious risk of extermination to several of these species in Nigeria. Yet, there is a paucity of information on the distribution, population status and sustainable management of NTFPs in most of the tropical lowland rainforests. We, therefore, assessed the population, distribution and threats to sustainable management of NTFPs within the tropical lowland rainforests of Omo and Shasha Forest Reserves, south western Nigeria. Data were obtained through inventory surveys on five top priority species including： bush mango （Irvingia gabonensis （Aubry-Lecomte ex O’Rorke） Baill）, African walnut （Tetracarpidium conophorum （Mull. Arg.） Hutch. ＆ Dalziel syn. Plukenetia conophora）, chew-stick （Massularia acuminata （G. Don） Bullock）, fever bark （Annickia chlorantha Setten ＆ P.J.Maas syn. Enantia chloranta） and bush pepper （Piper guineense Schumach. ＆ Thonn.）. Purposive and stratified random sampling techniques were used for the inventory. Each forest reserve was stratified into three, viz： less disturbed natural forest （for areas that have been rested for at least ten years）, recently disturbed natural forest （for areas that have suffered one form of human perturbation or the other in the last five years）, and plantation forest （for areas carrying forest plantation）. Data were collected from eighteen 10 m × 500 m belt transects located in the above strata. The species were generally fewer in both plantation and recently disturbed natural forest than the less disturbed natural forest, suggesting that forest disturbances （habitat modification） for other uses may have an effect on the occurrence and densities of the NTFPs. Exceptions to this trend were found for P. guineense and T. conophorum, which were fairly common in both plantation and recently disturbed natural forest. Among three tree NTFP species （i.e. I. gabonensis, M. acuminata and A. chlorantha）, only I. gabonensis showed a significant difference in overall DBH size classes for both reserves （t=？2.404; df =21; p=0.026）. Three tree NTFP species in both reserves further showed differences from the regular patterns of distribution of trees. The fairly regular reverse J-shaped size class distribution observed for M. acuminata in the study sites, however, suggests a recuperating population. In general, destructive harvesting of species, logging operations, low population size, narrow distribution ranges and habitat degradation are the major threats to the population of NTFPs in the study area. The implications of our findings for sustainable management of NTFPs in the study area are discussed and recommendations are made for a feasible approach towards enhancing the status of the species.

Experimental study of population density using an optimized random forest model

Random forest model is the mainstream research method used to accurately describe the distribution law and impact mechanism of regional population.We took Shijiazhuang as the research area,with comprehensive zoning based on endowments as the modeling unit,conducted stratified sampling on a hectare grid cell,and systematically carried out incremental selection experiments of population density impact factors,optimizing the population density random forest model throughout the process(zonal modeling,stratified sampling,factor selection,weighted output).The results are as follows:(1)Zonal modeling addresses the issue of confusion in population distribution laws caused by a single model.Sampling on a grid cell not only ensures the quality of training data by avoiding the modifiable areal unit problem(MAUP)but also attempts to mitigate the adverse effects of the ecological fallacy.Stratified sampling ensures the stability of population density label values(target variable)in the training sample.(2)Zonal selection experiments on population density impact factors help identify suitable combinations of factors,leading to a significant improvement in the goodness of fit(R^(2))of the zonal models.(3)Weighted combination output of the population density prediction dataset substantially enhances the model's robustness.(4)The population density dataset exhibits multi-scale superposition characteristics.On a large scale,the population density in plains is higher than that in mountainous areas,while on a small scale,urban areas have higher density compared to rural areas.The optimization scheme for the population density random forest model that we propose offers a unified technical framework for uncovering local population distribution law and the impact mechanisms.