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Canopy cover is an important parameter in forest ecosystems and has diverse applications in a wide variety of fields. However, estimation of forest canopy cover from high spatial resolution images ...

Forests provide vital ecosystem services such as soil and water conservation, climate regulation, and carbon storage. Large-scale afforestation programs are being attempted in many countries to improve environmental conditions in deteriorated or unfavorable locations. China's Three Northern Protected Forest Program (TNSFP), accounting for 42.40 % of China's total land area, is the world's largest afforestation program to date. The TNSFP has continued providing critical ecosystem services to humans over 73 years (1978-2050) with a total investment of CNY 93.3 billion. To facilitate understanding of the TNSFP's contribution, the effects of the TNSFP for last 43 years were comprehensively evaluated by using integrated review of structured literature, bibliometric analysis, and thematic analysis. We incorporated and expanded the direct ecosystem services evidence of the TNSFP from wind and sand control, soil erosion control and carbon sequestration to indirect economic benefits, e.g. increasing crop yield and promoting economic development. We found that over the past 40 years of TNSFP construction, wind and sand hazards and soil erosion in China's Three-North areas have been effectively controlled, and forest carbon sequestration, grain production and economic output have steadily increased. The ecosystem services provided by the TNSFP are highly consistent with the thrust of the UN Sustainable Development Goals, and the TNSFP has contributed to the realization of SDG2, SDG8, SDG13, and SDG15. Although achieving tremendous ecological, economic, and social benefits, the TNSFP still has knowledge gaps in its scientific basis. And the limited local engagement and insufficient investment highly hinder the TNSFP from playing its multiple functions. We suggest several urgent actions and directions to address these limitations. This review could help researchers gain insight into key areas of ecological restoration in the TNSFP, providing a reference for future research in the TNSFP construction in China and other regions of the world embarking on similar journeys.

Precise determination of vegetation type is important in remote sensing of the ecological environment. Many studies have explored ecosystem structure on explicit spatial scales using specific remot...

Magnetotactic bacteria (MTB) rely on magnetotaxis to effectively reach their preferred living habitats, whereas experimental investigation of magnetotactic advantage in stable sediment is currently lacking. We studied two wild type MTB (cocci and rod-shaped M. bavaricum) in sedimentary environment under exposure to geomagnetic field in the laboratory, zero field and an alternating field whose polarity was switched every 24 hours. The mean concentration of M. bavaricum dropped by ~50% during 6 months in zero field, with no clear temporal trend suggesting an extinction. Cell numbers recovered to initial values within ~1.5 months after the Earth’s field was reset. Cocci displayed a larger temporal variability with no evident population changes in zero field. The alternating field experiment produced a moderate decrease of M. bavaricum concentrations and nearby extinction of cocci, confirming the active role of magnetotaxis in sediment and might point to a different magnetotactic mechanism for M. bavaricum which possibly benefited them to survive field reversals in geological periods. Our findings provide a first quantification of magnetotaxis advantage in sedimentary environment.

Laterite is ubiquitous in India and has been extensively studied. However, it is still controversial with respect to its origin, definition, classification, and implications in paleoclimate, tectonic history and topography evolution. Of those, the origin of laterite, either in situ weathering of protoliths or weathering of allochthonous input, is the most critical to address. The ca. 25-m-thick laterite (duricrust) capping the Deccan Plateau is conventionally hypothesized to derive from in situ weathering of the topmost basalt. However, this thick laterite lacks upward progressive weathering which is characteristic of lateritic profile. Instead, it displays: 1) homogeneity in weathering intensity through the duricrust; 2) a clear unconformable contact of laterite with red clay, which together suggests that this thick laterite is genetically unrelated to in situ weathering of the topmost basalt. Lines of evidence in mineralogy, granularity, and geochemistry proved the disconnection between this laterite and basalt, and in contrast, indicated its correlation to aeolian accumulation. In this study the laterite together with the red clay was proposed to derive from aeolian dust accumulation and weathering since 65 Ma within context of Indian plate drifting across the equator from southern to northern hemisphere.

A back to the future approach to climate change refines Neogene records of paleoclimatic cooling and drying as future climate states for a warming world. Near Alcoota station in central Australia is a late Miocene fossil mammal site for Alcoota (10 Ma) and Ongeva (8 Ma) local faunas. The Alcoota fauna includes the largest known land bird (Dromornis stirtoni) and early diprotodontid (Kolopsis torus), but the geologically younger Ongeva fauna has a larger diprotodontid (Zygomaturus gilli). These faunas are evolutionary predecessors of Australian Pleistocene megafauna. Calcareous paleosols recorded a marked turn toward aridity compared with underlying thick lateritic duricrusts which lack fossils. Laterites of likely middle Miocene age are evidence of wet (>1100 mm mean annual precipitation) tropical (>17 °C mean annual temperature) paleoclimates, but these were deeply eroded and redeposited by the time of the late Miocene mammals. A succession of 19 paleosols of 5 pedotypes were recognized in the 19 m thick section, with shallow calcareous nodule (Bk) horizons as evidence of mean annual precipitation ranges from 100 to 400 mm, and mean annual range of precipitation of 50 mm, very similar to the modern climate of Alcoota (296 mm precipitation with 56 mm difference between wet and dry month). This was neither a rainforest nor monsoonal paleoclimate, and vegetation inferred from paleosols was open woodland and gallery woodland similar to that of today. Central Australia was not covered by monsoon rainforest during the late Miocene and its paleoclimatic history of Neogene desertification matches well that of other parts of the world.

Providing vegetation type information with accurate surface distribution is one of the important tasks of remote sensing of the ecological environment. Many studies have explored ecosystem structure information at specific spatial scales based on specific remote sensing data, but it is still rare to extract vegetation information at various landscape levels from a variety of remote sensing data. Based on Gaofen-1 satellite (GF-1) Wide-Field-View (WFV) data (16 m), Ziyuan-3 satellite (ZY-3) and airborne LiDAR data, this study comparatively analyzed the four levels of vegetation information by using the geographic object-based image analysis method (GEOBIA) on the typical natural secondary forest in Northeast China. The four levels of vegetation information include vegetation/non-vegetation (L1), vegetation type (L2), forest type (L3) and canopy and canopy gap (L4). The results showed that vegetation height and density provided by airborne LiDAR data could extract vegetation features and categories more effectively than the spectral information provided by GF-1 and ZY-3 images. Only 0.5 m LiDAR data can extract four levels of vegetation information (L1&ndash, L4), and from L1 to L4, the total accuracy of the classification decreased orderly 98%, 93%, 80% and 69%. Comparing with 2.1 m ZY-3, the total classification accuracy of L1, L2 and L3 extracted by 2.1 m LiDAR data increased by 3%, 17% and 43%, respectively. At the vegetation/non-vegetation level, the spatial resolution of data plays a leading role, and the data types used at the vegetation type and forest type level become the main influencing factors. This study will provide reference for data selection and mapping strategies for hierarchical multi-scale vegetation type extraction.

Background: To understand the theory of forest cycle and reveal the relationship between forest gaps and forest structure, species composition and biodiversity, we need to study the spatial structure of forest gaps. However, the complexity of natural secondary forest structure makes it difficult to quantify the spatial structure characteristics of gaps in large areas by field measurement. In this study, aerial orthophotos, and light detection and ranging (LiDAR), were used as data sources. The experimental area was Maoer Mountain Forest Farm, a typical natural secondary forest in northeastern China, and we used the investigation data of forest resources as reference material. We extracted 1343 forest gaps by manual digitization combined with canopy height model correction. The spatial characteristics of the extracted gaps were quantified from the spatial characteristics (area, shape complexity index), spatial heterogeneity (gap height diversity index) and spatial distribution characteristics (Clark–Evans index) of individual gaps.Results: In the three types of natural secondary forest, the frequency distribution of gap area showed a negative exponential distribution: 90% of the gap area was less than 100 m2. As forests aged, the proportion of gap area decreased from young forest to near-mature forest, and increased from near-mature forest to over-mature forest. The maximum frequency range of shape index changed from 1.2 to 1.4 for young forest, middle age forest and near-mature forest; and which is from 1.4 to 1.6 for mature forest and over-mature forest. The gap height diversity index increased from young forest to near-mature forest, decreased when the forest was mature and increased when it was over-mature. The spatial pattern of forest gaps was mainly random. The proportion of random distribution increased from young forest to middle-aged forest, decreased from near-mature forest to mature forest and increased from over-mature forest.Conclusions: Most of the gaps in the natural secondary forest were small and medium-sized; the shapes were complex; the internal spatial heterogeneity was high; and the gaps were mostly randomly distributed. Use of aerial orthophoto and canopy height model sets was efficient and reliable in quantifying the spatial characteristics of forest gaps, and can replace the time-consuming (and usually field-based) measurement of their subjective spatial characteristics.

Canopy closure (CC) is an important parameter in forest ecosystems and has diverse applications in a wide variety of fields. Canopy closure estimation models, using a combination of measured data and remote sensing data, can largely replace traditional survey methods for CC. However, it is difficult to estimate the forest CC based on high spatial resolution remote sensing images. This study used China Gaofen-1 satellite (GF-1) images, and selected China&rsquo, s north temperate Wangyedian Forest Farm (WYD) and subtropical Gaofeng Forest Farm (GF) as experimental areas. A parametric model (multiple linear regression (MLR)), non-parametric model (random forest (RF)), and semi-parametric model (generalized additive model (GAM)) were developed. The ability of the three models to estimate the CC of plantations based on high spatial resolution remote sensing GF-1 images and their performance in the two experimental areas was analyzed and compared. The results showed that the decision coefficient (R2), root mean square error (RMSE), and relative root mean square error (rRMSE) values of the parametric model (MLR), semi-parametric model (GAM), and non-parametric model (RF) for the WYD forest ranged from 0.45 to 0.69, 0.0632 to 0.0953, and 9.98% to 15.05%, respectively, and in the GF forest the R2, RMSE, and rRMSE values ranged from 0.40 to 0.59, 0.0967 to 0.1152, and 16.73% to 19.93%, respectively. The best model in the two study areas was the GAM and the worst was the RF. The accuracy of the three models established in the WYD was higher than that in the GF area. The RMSE and rRMSE values for the MLR, GAM, and RF established using high spatial resolution GF-1 remote sensing images in the two test areas were within the scope of existing studies, indicating the three CC estimation models achieved satisfactory results.

Object-based classification differentiates forest gaps from canopies at large regional scale by using remote sensing data. To study the segmentation and classification processes of object-based forest gaps classification at a regional scale, we sampled a natural secondary forest in northeast China at Maoershan Experimental Forest Farm. Airborne light detection and ranging (LiDAR; 3.7 points/m2) data were collected as the original data source and the canopy height model (CHM) and topographic dataset were extracted from the LiDAR data. The accuracy of object-based forest gaps classification depends on previous segmentation. Thus our first step was to define 10 different scale parameters in CHM image segmentation. After image segmentation, the machine learning classification method was used to classify three kinds of object classes, namely, forest gaps, tree canopies, and others. The common support vector machine (SVM) classifier with the radial basis function kernel (RBF) was first adopted to test the effect of classification features (vegetation height features and some typical topographic features) on forest gap classification. Then the different classifiers (KNN, Bayes, decision tree, and SVM with linear kernel) were further adopted to compare the effect of classifiers on machine learning forest gaps classification. Segmentation accuracy and classification accuracy were evaluated by using Moller’s method and confusion metrics, respectively. The scale parameter had a significant effect on object-based forest gap segmentation and classification. Classification accuracies at different scales revealed that there were two optimal scales (10 and 20) that provided similar accuracy, with the scale of 10 yielding slightly greater accuracy than 20. The accuracy of the classification by using combination of height features and SVM classifier with linear kernel was 91% at the optimal scale parameter of 10, and it was highest comparing with other classification classifiers, such as SVM RBF (90%), Decision Tree (90%), Bayes (90%), or KNN (87%). The classifiers had no significant effect on forest gap classification, but the fewer parameters in the classifier equation and higher speed of operation probably lead to a higher accuracy of final classifications. Our results confirm that object-based classification can extract forest gaps at a large regional scale with appropriate classification features and classifiers using LiDAR data. We note, however, that final satisfaction of forest gap classification depends on the determination of optimal scale (s) of segmentation.

The thick loess-palaeosol sequences of the Chinese Loess Plateau (CLP) are valuable continental archives of paleoclimatic and paleoenvironmental changes since at least the mid-Miocene. The magnetic susceptibility record of loess sequences is frequently used for palaeoclimatic reconstruction. However, the two magnetoclimatological models for the magnetic enhancement of loess-palaeosol sequences—the wind vigour model and the pedogenic model—are still debated, and neither model alone is sufficient to explain the magnetic susceptibility stratigraphy of loess deposits in diverse environments. Loess can be substantially altered by its environment of deposition and the macroscopic characteristics of loess may differ substantially from the well-documented sequences of the CLP, which complicates loess identification and its palaeoclimatic interpretation. In the present study, we summarize the attributes of loess deposits in different environments and review possible approaches for identifying aeolian accumulation. Loess-palaeosol sequences in various climatic contexts, from arid to subhumid, are summarized and categorized and the relationship between the magnetic susceptibility and effective precipitation is evaluated. A model comprising three cases is proposed to interpret the magnetic susceptibility of loess-palaeosol sequences in a variety of different environments. In case A (e.g., the Xinjiang loess, NW China), where physical weathering dominates and pedogenesis is weak, there is no relationship between the magnetic susceptibility and pedogenesis, and here the wind vigour model is applicable. In case B (e.g., the CLP), where, under predominantly oxidizing conditions, the magnetic susceptibility increases with pedogenic intensity, and an oxidizing-pedogenic model is applicable. In case C (e.g., Alaskan and Siberian loess), there is a negative relationship between magnetic susceptibility and pedogenesis due to the dissolution of detrital iron oxides under reducing conditions, and a reduction-pedogenesis model is applicable. In Case C, pedogenesis (or chemical weathering/dissolution) acts to largely obliterate the detrital magnetic susceptibility signal. Hence, contrary to the original interpretation of the magnetic susceptibility of Alaskan and Siberian loess, the wind vigour model is not applicable. Two thresholds of mean annual precipitation between the three cases are proposed, which enable the paleoclimatic interpretation of loess magnetic susceptibility records in different environments.

Late Permian and Triassic red mudstones are widely distributed and exposed in southwestern England. This homogenous, massive mudstone succession has been extensively studied for its palaeoenvironmental potential. However, its origin and palaeoenvironment remain under debate. The Triassic Mercia mudstone was early proposed to be aeolian loessic clay based on collapse nature when wetted or loaded and its similarities with aeolian clay in Quaternary Australia, but lacks experimental confirmation and is not generally accepted. In comparison with aeolian red clay in China, here we confirmed that the Triassic Mercia mudstone, together with the Upper Permian Aylesbeare mudstone, was dominated by aeolian clay. This was based on lines of evidence regarding sedimentary structure, particle grain size, geochemistry, micromorphology, and pedogenic features. The results showed that the Mercia mudstone and the Aylesbeare mudstone had sedimentary structures and grain size distributions that were similar to the aeolian red clay in the Chinese Loess Plateau. The major chemical elements correlated well with the aeolian red clay, with the exception of minor discrepancies in CaO and K2O. The similarity in the rare earth element (REE) distribution of the Mercia mudstone and the Aylesbeare mustone with aeolian red clay inferred their similar origin. Widespread pedogenic features indicated the universal development of palaeovertisols forming in alternating wet/dry climates. It was hypothesised that Permo-Triassic southwestern England was dominated by aeolian dust accumulation in a seasonal wet/dry climate, whereas perennial lakes or longstanding rivers across the study area might not exist.

Incident solar radiation is one of the major sources of energy for driving biological and physical processes on earth. In this paper, simple conversion factors are designed to determine how the four landforms (i.e. plain, plateau, hill and mountain) will affect incident solar radiation at one month intervals using the ArcGIS tool appropriate for regional solar radiation analysis. A comparison is made between simulation results and those measurements taken in actual radiation stations, providing a correlation R 2 of 0.9063. Results indicate first, that if the ratio of the monthly mean of the DEM-based regional solar radiation to the monthly mean of the hypothesis DEM-based regional solar radiation is defined as the conversion factor (R) of the solar radiation and the ArcGIS tool for regional solar radiation analysis is employed, then the computation can be simplified and the impact of terrain factors on incident solar radiation can be correctly represented. Secondly, with each of the four landforms, R varies according to the season, slope gradient and aspect; the season induces more impacts than the terrain factors; R increases first and then decreases when the aspect changes clockwise, but decreases continuously with an increase in slope grade; R varies in a complex way in the case of mountains, especially for grade-five slopes. Thirdly, R increases initially and then decreases in a sinusoidal manner with an increase in aspect under the influence of slope gradient during the winter; R varies in a linear and somewhat symmetric manner (monotone increasing, monotone decreasing and stable) with the increase in slope gradient and under the influence of the aspect. These results are helpful in studying the impact of terrain factors of different landforms on incident solar radiation on the landscape scale using the simple conversion factors.

Magnetotactic bacteria (MTB) orient and migrate along geomagnetic field lines in a process known as magnetotaxis, while their swimming direction is determined by flagella rotation (clockwise or counterclockwise) in response to surrounding chemical conditions, i.e., chemotaxis. The combination of magnetotaxis and chemotaxis (magneto-chemotaxis) is expected to govern MTB behaviors and vertical distribution in chemically stratified sediment. Magneto-aerotaxis is a process in which oxygen concentration determines MTB swimming direction. However, direct validation of magneto-aerotaxis in sediment, where MTB primarily occur, has been limited to date. Such validation is crucial because low alignment degree and complex chemical conditions in sediment are not comparable to those in the aqueous environment. Herein, specifically designed experiments were conducted to investigate the effects of oxygen conditions on two wild-type MTB in sediment, rod-shaped Candidatus Magnetobacterium bavaricum ( M. bavaricum ) and unspecified cocci collected from Chiemsee, a freshwater lake in southern Germany. In the first experiment, oxygen gradient development and MTB vertical distribution were closely monitored during reformation of new sediment stratification. The MTB population peaked immediately below the sediment-water interface, which was likely because of magneto-aerotaxis. However, there were no observable changes in oxic-anoxic interface (OAI), and MTB distribution later extended to greater depth, indicating other driving mechanisms. A second experiment was conducted to determine if north-seeking (NS) MTB become south-seeking (SS) when moved into anoxic conditions; however, this conversion was not detected during oxygen concentration reduction. The magneto-aerotaxis of the two examined MTB were not directly validated. Long-term stable anoxic conditions led to MTB distribution downward, which is consistent with the distribution under normal oxygen conditions, indicating MTB adaptation to the environment. These findings indicate that oxygen conditions likely play a role in MTB behaviors and vertical distribution in sediment, but that they do not act as directly influencing or critical factors.

[1] The widespread occurrence of magnetotactic bacteria (MTB) in several types of marine and freshwater sediment, and the role of fossil magnetosomes (magnetofossils) as main remanent magnetization carriers therein, has important paleomagnetic and paleoenvironmental implications. Despite numerous studies on MTB biology and on magnetofossil preservation in geological records, no detailed information is yet available on how magnetotaxis (i.e., the ability to navigate along magnetic field lines) is performed in sedimentary environments, and on how magnetofossils possibly record the Earth magnetic field. We provide for the first time experimental evidence for these processes. MTB living in sediment are poorly aligned with the geomagnetic field, contrary to what is observed in water. This can explain the seemingly excessive magnetic moment of most MTB. The observed alignment is sufficient for supporting magnetotaxis across the typical thickness of chemical gradients. Experiments with magnetofossil-rich sediment suggest that a natural remanent magnetization (NRM) is acquired by magnetofossils in the so-called benthic mixed layer, where natural MTB populations usually occur. The acquired NRM is proportional to the applied field at least up to ∼160 µT, and its intensity is compatible with values observed in nature for same sediment types. Therefore, if fossil magnetosome chains are not subjected to further alteration by early diagenetic processes, they can provide useful relative paleointensities. We propose a preliminary model to explain early stages of magnetofossil NRM acquisition as the result of a dynamic equilibrium between magnetic torques and randomizing forces due to sediment mixing.

Controversial hairpin-shaped trace fossils (Myxomitodes stirlingensis) and discoid fossils (Cyclomedusa davidi) are here reinterpreted in a reassessment of sedimentology and paleosols of the 1.9 ± 0.1 Ga Stirling Range Formation of Western Australia. Paleosols in the Stirling Range Formation were recognized from complex cracking patterns (peds and cutans), chemical and mineralogical zonation (soil horizons), and poikiloblastic crystals (desert roses). Redox profiles of the paleosols are evidence of well-drained profiles of a coastal plain under a low oxygen (433 ± 116 ppmv) and carbon dioxide (564 ± 64 ppmv) atmosphere. Gypsum pseudomorphs in paleosols that are deeply weathered chemically, represent a persistence of acid sulfate weathering, better known in Archean paleosols before the Great Oxidation event at 2.45 Ga. Chemical composition of the paleosols is evidence of a humid (1478 ± 182 mm mean annual precipitation) temperate (11.3 ± 0.5 °C mean annual temperature) paleoclimate. Their paleoenvironmental setting was a coastal plain on a passive tectonic margin. Megafossils were found on paleosols of western red sandstones of the Stirling Range Formation, not in gray shales and sandstones of marine facies to the east. Trace fossils (Myxomitodes stirlingensis) and discoid fossils are both found at the surface of well drained paleosols, and so were not metazoan trails, nor sea jellies. Myxomitodes was more likely a grex (“slug”) trail of soil slime molds, and the Cyclomedusa discoids, were probably microbial colonies. Pervasive microfilamentous structures in the paleosol surface are additional evidence of Paleoproterozoic microbial earth ecosystems.

For the phenomenon of low image contrast usually appearing in scanning electron microscope images, a low contrast microscopic image enhancement algorithm based on multi-technology fusion was proposed, in which the high frequency and low frequency components of images are separated to avoid the increased image noise, while the images was strengthened. Furthermore, the low contrast microscopic image enhancement was realized combining with Sobel operator, LoG operator and improved contrast limited adaptive histogram equalization method. Experimental results show that the proposed method highlights the image edges and details effectively, which can expand the dynamic grayscale range of image, increase the image contrast and entropy so lay the foundation for the microscopic image analysis and identification.

Magnetotactic bacteria (MTB) use passive alignment with the Earth magnetic field as a mean to increase their navigation efficiency in horizontally stratified environments through what is known as magneto-aerotaxis (M-A). Current M-A models have been derived from MTB observations in aqueous environments, where a >80% alignment with inclined magnetic field lines produces a one-dimensional search for optimal living conditions. However, the mean magnetic alignment of MTB in their most widespread living environment, i.e. sediment, has been recently found to be