Landscape Distribution Pattern of Subalpine Color-leaved Forests and the Influence of Topographic Factors in Western Sichuan

Several microbiological indicators of soil quality present high sensitivity, but little is known about the influence of topographic factors on them. This work aimed to evaluate variability of biological indicators of soil quality across a hillslope under native forest and the influence of topographic factors on them. Four positions on a hillslope were evaluated. Activity of the enzymes β-glucosidase, acid phosphatase, urease and fluorescein diacetate (FDA) hydrolysis were determined, as well as basal and substrate-induced respiration, and density of microorganisms: total bacteria, total fungi, actinobacteria, phosphate solubilizers, ammonifiers, native rhizobia, free-living N2-fixing bacteria, spores of arbuscular mycorrhizal fungi and percentage of root colonization by arbuscular mycorrhizal fungi. Activity and density of microorganisms were correlated with topographic factors. The relation of these factors to the variations of the evaluated indicators was determined using the random forest algorithm. Microbiological indicators varied according to the hillslope positions. The indicators urease, basal respiration, spore density, mycorrhizal colonization, total bacteria and fungi, phosphate solubilizers, and free-living N2-fixing bacteria detected in JNFB and FAM culture medium did not vary with terrain attributes and were therefore more indicated in cases of topographic variations. This and future studies can help to select the best microbiological indicators for different conditions.

In Geophysics, topographic factors are observations that can be directly measured, but they are often ignored to simplify the model. Studying the coseismic deformation caused by earthquakes helps accurately determine the epicenter's parameterization. It provides a reference for the reasonable layout of coseismic observation stations and GNSS observation stations. After the Mw7.8 earthquake in Nepal in 2015, GCMT, USGS, GFZ, CPPT, and other institutions released their epicenter parameter. However, according to their parameters, the coseismic displacements simulated by the spectral-element method are quite different from the GNSS observations. Firstly, this paper inverts the geometric parameters of the seismogenic fault with Nepal’s coseismic GNSS displacement. The spectral-element method determines the source's location and depth under the heterogeneous terrain and outputs the source parameters. Among the results of many studies, the surface source is more consistent with the generation mechanism of large earthquakes. Secondly, this paper calculates the fault slip distribution of this earthquake using SDM (Steepest Descent Method) based on GNSS and InSAR data, which is divided into 1500 subfaults, and the moment tensor of each subfault is calculated. This paper investigates the distribution characteristics of the coseismic deformation field of the 2015 Mw 7.8 earthquake in Nepal under three different models. The results show that the influence of topographic factors is ~ 20%, and the influence of heterogeneous factors is ~ 10%. This paper concludes that the influence of topographic factors is much more significant than that of heterogeneous factors, and the influence of both should be addressed in coseismic deformation calculations.

Spatial relationships between NDVI and topographic factors at multiple scales in a watershed of the Minjiang River, China

Soil salinization is a global problem, which threatens agricultural productivity and sustainability, especially in arid and semi-arid regions. Soil salinity and moisture are important factors affecting agricultural production in arid regions. However, few studies have considered the influence of topographic factors on the spatial distribution patterns of soil salinity and moisture. This research aims to explore the spatial distribution characteristics and its influencing factors of soil salinity and moisture in the oasis farmland of arid areas. In this paper, GIS and geostatistics methods were applied to analyze the spatial distribution characteristics and variability of soil salinity and moisture, and then the corresponding proxy variables were used to quantitatively study the influence factors by using the geographical detector model. The results showed the coefficients of the variation of soil salinity and moisture to be 71.25% and 31.89%, respectively. There was moderate spatial autocorrelation of soil salinity and moisture. Soil salinity in the southwest was higher than in the northeast, and soil moisture in the northwest and southeast were lower than in the center and the northeast edge. The main influencing factors were available phosphorus, roughness of terrain, alkaline nitrogen, available potassium, and elevation. Combined action of topographic factors and soil nutrients has a major influence on the spatial distribution of soil salinity and moisture. Therefore, developing a suitable fertilizer regime under different topographic conditions could be an effective way to promote the sustainability of oasis agriculture in arid areas.

In China, the successive government has implemented ambitious programs and policies to reverse the decline in forest cover. As an essential source of freshwater and an ecological barrier for Beijing, Zhangjiakou City has implemented several forest expansion strategies. Topographic conditions in this mountainous area have generated spatially heterogeneous afforestation outcomes. Quantifying the impact of these conditions on implemented forest programs could improve ecological restoration strategies of Chinese mountain areas. Using remotely sensed data from the Landsat 5 Thematic Mapper and the Landsat 8 Operational Land Imager, we generated land cover data to identify forest cover changes in Zhangjiakou City in 1989, 2000, and 2015. Forest cover data, topographic information (elevation, slope, aspect, land relief, and terrain niches), and spatial statistical models (geographically weighted regression [GWR]) were used to analyze re- and afforestation over 2 periods (1989–2000 and 2000–2015). The results show that forest cover in Zhangjiakou City increased by one third from 1989 to 2015. The rate of afforestation from 2000 to 2015 was 4 times the rate observed between 1989 and 2000. A trend toward gradual afforestation of higher-elevation and gentler-slope areas and land relief and terrain niche zones was observed between the 2 periods. Expansion mostly occurred in grasslands, arable lands, and unused lands. Elevation, slope, and land relief were the dominant topographic factors influencing forest cover change. Such factors influenced afforestation directly through their effect on microclimates and local biophysical conditions and indirectly by limiting the geographic area where forest programs could be implemented. Terrain niche was also an important predictor of forest cover change under complex topographic conditions. The GWR results indicate heterogeneous forest cover change processes across the study area. Our analysis could guide the implementation of effective forest expansion programs and policies, particularly for degraded mountain ecosystems.

Exploring suitable topographical factor conditions for vegetation growth in Wanhuigou catchment on the Loess Plateau, China: A new perspective for ecological protection and restoration

Topography affects the soil conditions and bacterial communities along a restoration gradient on Loess-Plateau

Soil nutrition is a key factor influencing species composition in a community, but it has clearly scale‐dependent heterogeneity. In the present study, geostatistics methods and canonical correspondence analysis (CCA) were used to detect: (i) the variation range of soil spatial heterogeneity; (ii) the influence of topographic factors on the distribution of soil nutrition; and (iii) the relationships between soil chemical properties and species in the community. In all, 23 soil variables were measured, including total N and organic C, Al, Ba, Ca, Cr, Cu, Fe, Ga, Li, Mg, Mn, Na, NH4‐N, Ni, NO3‐N, Pb, pH, P, Sr, Ti, V, and Zn. Semi‐variograms of these variables were calculated and mapped. All indices showed autocorrelations, with ranges between 29 and 200 m. When the sample method was larger than these distances, spatial autocorrelations were avoided. The distribution patterns of Ca, Cr, Ga, K, Mg, organic C, P, Pb, and pH, and total N were related to the microtopography and the distribution of these compounds was clumped in water catchments area. The CCA method was used to investigate the relationship between plant species and soil properties in this community. Fagus engleriana Seem., Lindera obtusiloba Bl. Mus., and Acer griseum (Franch.) Pax were correlated with organic C, available N, and P.(Managing editor: Ya‐Qin Han)

Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data

An approach to predicting future stand composition using standard ecological methods and multiple regression analysis is presented. A composition index value for each of 54 undisturbed, compositionally stable, mature stands was obtained by multiplying the importance value (relative basal area) of a species by its adaptation value and summing for all species in a stand. Adaptation values ranging from 1-10 were assigned based on the position of species maximum basal area values along a stand basal area gradient. Three multiple linear regression models were developed for predicting stand CI from effective soil depth, percent stone, available soil water, slope position, aspect and distance to the opposing slope. The models, which accounted for 90-97 % of the variation, were validated using data from seven compositionally stable stands not used in model development. The models closely predicted compositional change in a disturbed stand for which 48 years of permanent plot data were available. Successional trends were examined in six additional stands disturbed 50-70 years ago. In most stands, predicted stand composition closely coincided with the presence of established understory stems. The most substantial changes were found on N slopes and stream terraces where Quercus alba and Q rubra stands are being replaced by Acer saccharum and other mesophytic hardwoods. When applied to broad ridges that were once farmed, the models predicted that under presettlement site conditions (i.e., uneroded forest soil), stands were dominated primarily by Q. alba with small amounts of Q. stellata and Q. velutina. On sites where erosion has reduced soil depth to 25 and 15 cm, it was projected that stands would be dominated by Q stellata and Q. marilandica, and by Juniperus virginiana, respectively. A biological interpretation of the site-vegetation relationships, identified by the models is based on soil water storage and the influence of topographic factors on evapotranspiration loss. INTRODUCTION The successional process has been investigated for many years, yet there is no currently acceptable method for predicting potential forest composition given specific site conditions. Succession is defined here as the systematic temporal replacement of a forest community composed of relatively shade-intolerant species by one in which more shade-tolerant species dominate to form a compositionally stable community. Usually stands of early successional species develop after moderate to severe cutting, fire, wind, disease or insect attack which removes the overstory canopy and permits more lightdemanding species to invade and dominate sites where they normally are excluded. Considerable research has concentrated on community dynamics with a view toward predicting the species mix in compositionally stable (climax) forest. Stephens and Waggoner (1970, 1980) developed transition probability values that permitted anticipation of species change in forest composition, whereas Leak (1970) predicted successional change by birth and death simulation. In both studies, predictions were based upon systematic sampling over a long period. Stout et al. (1975) constructed multispecies models that indicated trends toward certain forest species (e.g, Acer saccharum). Goff (1968), Goff and Zedler (1972), Zedler and Goff (1973) and Auclair and Goff (1974) used several size association and stratification analyses to determine species succession vectors, replacement potential and forest trends. Botkin et al. (1972a, 1972b) developed a computer-generated model JABOWA) which simulated forest composition changes using Monte Carlo techniques to decide births and deaths over any selected period; this

On October 7, 2014, a Ms 6.6 earthquake occurred in Jinggu County, Yunnan Province, China, causing some casualties and property damage. A database of landslides was created based on high-resolution satellite images taken before and after the earthquake. The results show that this event triggered at least 441 coseismic landslides, with a total area of 1.08 km2, distributed in the VII-VIII intensity zone, with an area of about 2160.86 km2. The total volume of these landslides is estimated to be 9.4×106 m3 according to the area-volume formula. The point density, area percentage, and volume density of the landslides in the study area are 0.20 km−2, 0.05%, and 0.004 m, respectively. The comprehensive results show that the Jinggu earthquake landslides are mostly relatively small-scale and develop in a wide range. We consider the influence of topographic factors and river systems on coseismic landslide distribution using landslide number density (LND) and land area percentage (LAP). It indicated that LND and LAP generally increase as the elevation and distance to watershed decrease and slope angle increases and are relatively larger in southeast-facing and concave slopes. This detailed coseismic landslide database for the Jinggu earthquake is essential for the subsequent regional risk assessment.

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley’s K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning.

On the influence of topographic factors upon the oxygen consumption rate in sill basins of fjords

Influence of topographic factors on community parameters in tropical deciduous forests of Eastern India

Exploring the spatial and temporal dynamics of vegetation cover in different regions of China and its topographic effect is crucial for maintaining the ecological environment and preventing soil erosion. Based on the MODIS NDVI data from 2000 to 2023, the vegetation cover of China for 24 years was calculated by using the pixel binary model. The spatial and temporal trends of vegetation cover in different regions of China and the influence of topographic factors on the spatial distribution of vegetation cover were investigated by dividing the study area into seven typical climate zones. The results showed that： ① From 2000 to 2023, the vegetation cover in China showed a fluctuating upward trend, with a growth rate of 0.207%·a-1 and a basic pattern of "low in the northwest, high in the southeast, and spatially differentiated in the central part of the country." The proportion of areas with improved vegetation cover over the years was 46.7%, with a risk of continuous degradation in local areas. ② With the increase in altitude, the trend of vegetation cover changes in various climatic zones was not the same. With the increase in slope, the vegetation cover of the climatic zones showed a fluctuating upward trend, and the proportion of vegetation cover of different slope direction was relatively stable. ③ The vegetation cover in the same climatic zone had a significant difference in the response to the topographic factors, and the experiment showed that topographic factors had a significant influence on the vegetation cover. The experiment showed that the influence of terrain factors on vegetation cover was as follows： elevation > slope > slope direction. The study of the spatial differentiation of vegetation and the driving law of topography in typical climatic zones can provide scientific basis for the improvement of China's ecological environment.