Natural Vegetation Types Research Articles

Cell-level coupling of a mechanistic model to cellular automata for improving land simulation

ABSTRACT The land use and land cover change (LUCC) process is crucial for climate and environmental change studies. Cellular automata (CA) models based on machine learning techniques have commonly been used to simulate LUCC. However, conventional CA models can only capture the historical relationship between driving forces and LUCC through statistics. Climate change significantly affects LUCC, especially natural vegetation. The statistical relationship between driving forces and LUCC may change with the climate. Furthermore, the existing coupled models of CA and mechanistic models are only loosely coupled in terms of the quantity of land demand provided by mechanistic models, which denotes that mechanistic models do not directly guide CA models in simulating spatial land dynamics. Thus, herein, a novel model that couples Lund Potsdam Jena (LPJ), a mechanistic model, and CA at the cell level is proposed to consider the mechanisms and statistics in LUCC simulations. The proposed coupled model (LPJ-FLUS) is validated by comparison with two historical LUCC simulations in China from 2001 to 2010 and 2015. The results show that the proposed coupled model affords higher simulation accuracy, especially on natural vegetation, compared to the two conventional CA models. The overall Figure of Merit value of the LPJ-FLUS model in the historical LUCC simulations is about 5% higher than that of the conventional CA model, reaching 23.37%, and is even 8% higher for some natural vegetation types. The proposed model is employed to predict the future LUCC under two SSP-RCP scenarios in China from 2015 to 2100. The simulation results show that the proposed model effectively combines the strengths of LPJ and CA, retaining the high spatial resolution of CA while representing the spatial possibilities of LUCC under different future climate scenarios assessed by LPJ. The quantitative validation results show that the simulation results of the LPJ-FLUS model are more spatially correlated with the LPJ model than those of conventional CA models. The proposed LPJ-FLUS model is a valuable attempt toward tightly coupling mechanistic and CA models at the cell level. Additionally, it has promising potential for high spatial resolution LUCC simulations and environmental impact analysis under future extreme climate scenarios.

THE STRENGTHS AND LIMITATIONS OF VEGETATION MAPS FOR DETECTING CONSERVATION PERFORMANCE IN NAPA COUNTY'S NATURAL VEGETATION AND AGRICULTURAL LANDS

We report the second edition of Napa County's vegetation map using California's Manual of Vegetation classification system and aerial imagery from 2016. It covers 2053.54 km2, increases polygon resolution by 23.8%, contains 35,244 polygons, and has 71 landcover types, 60 of which are dominated by natural vegetation. It has an overall error rate of 2.6%, includes canopy density measures for 24 vegetation types, and contains explicit measures of structures in the Wildland Urban Interface (WUI). We compared the new map to the one based on 1993 imagery to ask how effective Napa county's agricultural preservation and conservation regulations have been at preventing conversion of natural vegetation across the county and of agricultural lands within and beyond the county's Agricultural Preserve, established in 1968. We examined net change and change detected using a transition matrix, to seek concealed landcover conversion. The net change shows small increases in Agriculture and Urban extents. However, the transition matrix found substantial Urban expansion into Agriculture, 12.9 km2 overall and 226.9 ha (2.24%) within the Agricultural Preserve; and 30 km2 of agricultural expansion into natural vegetation, including 595 ha of high conservation-value oak woodlands. Due to increased map resolution in the 2016 map, we identified stands of natural vegetation (Oak Woodlands, Grassland, and Chaparral) in areas previously mapped as Agriculture and Urban, as well as Oak Woodlands in areas previously mapped as other vegetation types. Their inclusion in net measures of landcover change substantially obscures actual loss in natural vegetation types and agricultural lands. The net loss for Oak Woodlands is 191 ha, but the transition matrix identifies 782 ha converted to urban or agriculture, which suggests only moderate performance for the county's conservation measures. We also found rates of vegetation change in wildfire-burned areas three times higher than in unburned areas. Conversion of agricultural lands to urban was about 2.3% in the Agricultural Preserve, but 6.3% beyond, showing that county zoning slowed urban expansion. We found changes in spatial resolution and mapping details between vegetation map editions made net measures of landcover change inaccurate, and that transition matrix-analyses provided more accurate accounting and identification of mapping methods errors.

集成生态系统服务与生物多样性的系统保护规划

PDF HTML阅读 XML下载 导出引用 引用提醒 集成生态系统服务与生物多样性的系统保护规划 DOI: 10.5846/stxb202112023396 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（32071650，31670539）；云南省中青年学术和技术带头人后备人才项目（202105AC160070）；云南大学研究生科研创新基金项目（2021Y039） Systematic conservation planning by integrating ecosystem services and biodiversity Author: Affiliation: Fund Project: The National Natural Science Foundation of China (grants 32071650, 31670539); Young and Middle-aged Academic and Technical Leaders Reserve Talent Program of Yunnan Province (202105AC160070); Graduate Research innovation project of Yunnan University (2021Y039). 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:生物多样性和生态系统服务的保护与可持续管理是当今世界面临的重大挑战之一，但如何判识与优化集成生态系统服务与生物多样性保护对象的保护优先区网络，相关研究还很有限。针对"三江并流"区，选取珍稀濒危与特有动植物物种和自然植被类型作为生物多样性保护对象，以调节服务（碳存储、固碳和土壤保持）、文化服务（自然游憩）和供给服务（水源供给）为生态系统服务保护对象。应用系统保护规划方法，首先判识出单一生物多样性和生态系统服务保护优先区；然后，分析这些保护优先区间的相关关系，并选择与生物多样性正相关的生态系统服务类型，判识集成生态系统服务与生物多样性的保护优先区；最后，评估了集成生态系统服务与生物多样性保护优先区在六类已建保护地中的保护状况。结果表明：（1）"三江并流"区多情景规划得到的生物多样性与生态系统服务保护优先区之间均呈正相关关系；（2）与分别针对生态系统服务和生物多样性的规划情景相比，集成生态系统服务与生物多样性保护优先区能够同时对两类保护对象提供最高的保护覆盖率；（3）集成生态系统服务和生物多样性保护优先区占研究区总面积的48.9%，其已建保护地覆盖率为32.5%，说明现有保护地体系仍存在保护空缺。 Abstract:Conservation and sustainable management of biodiversity and ecosystem services are one of the major challenges faced by the world today. However, there is still limited research on how to identify and optimize the portfolio of priority conservation areas (PCAs) that integrate ecosystem services and biodiversity as conservation targets. Using the Three Parallel Rivers Region (TPRR) as a case, this study selected representative conservation features for both biodiversity and ecosystem services; biodiversity conservation features included the rare, endangered and endemic plant and animal species and natural vegetation types; ecosystem-service conservation features included regulation services (carbon storage, carbon sequestration and soil retention), cultural services (natural recreation) and supply services (water supply). We firstly identified the individual portfolio of PCAs for biodiversity and each type of ecosystem services by applying a systematic conservation planning approach, respectively. Then, we analyzed the relationship between these different portfolios of PCAs. We identified the PCAs by integrating biodiversity and ecosystem services that had a portfolio of PCAs being positively correlated with biodiversity PCAs. Finally, we assessed the conservation status of the integrated PCAs within six categories of the existing protected areas. The results showed that:(1) there was a positive relationship between different portfolios of the PCAs identified for biodiversity and each type of ecosystem service in TPRR; (2) In comparison with planning scenarios for ecosystem services and biodiversity separately, the PCAs integrating ecosystem services and biodiversity could simultaneously provide the highest coverage for all biodiversity features and ecosystem services; (3) The PCAs integrating ecosystem services and biodiversity covered 48.9% of the study area, and received 32.5% coverage from the protected areas, indicating that conservation gaps still existed in the existing protected-area system. 参考文献 相似文献 引证文献

VEGETATION MAPPING AND DEVELOPMENT OF A METHOD FOR THE VEGETATION TYPIFICATION IN THE ARABIAN PENINSULA

The study aims to generate vegetation mapping for the study area's existing vegetation and apply a vegetation typification approach that can be used to identify the vegetation structure of any region in the Arabian Peninsula. To highlight the plant diversity and the vegetation communities for nature conservation purposes, a case study in Albaha region, Saudi Arabia is presented, in which the natural vegetation communities and vegetation types of one of the Important Plant Species Areas (IPSA) of Saudi Arabia is evaluated. In an area of 167.6 km2, 97 samples, each with 20X20 m were laid out covering the whole ecological zones of the study area. Data on flora, vegetation cover and topography were gathered from each sample site using Braun-Blanquet method. ITC approach of vegetation typification according to three dimensions (trees, shrubs, and herbs) is applied to identify the structures of each vegetation type. The results showed 319 plant species belonging to 228 genera and 75 families. These species were analyzed and classified into three plant communities and 14 different vegetation types using multivariate analysis program (MVSP) software. Using the percentage of trees, shrubs and herbs, the three-dimensional graphics of vegetation structure presented in this study can be used to determine the vegetation structure of any region in the Arabian Peninsula.

Topography and its Impact on the Distribution of Cover Belts of Natural Intentions in the Qardagh Region

This page researches to analyze the relationship between the topography and the natural vegetation in the Qardagh region, since the topography has a direct impact on the elements of climate, precipitation and temperatures. this determines the density and type of natural vegetation. The narrow plains and therefore the temperatures and the amount of rain differ between its different regions, which led to the diversity of the natural vegetation and in order to reach the objectives of the research, we divided the research into four sections. Natural vegetation. In the third and fourth sections, we studied the types of natural vegetation and natural vegetation belts according to the height from the surface of the earth. In conclusion, we concluded that the natural vegetation belts differ with different terrain in terms of quantity and type, and we used in this research Excel software (GIS & RS).

Twenty‐two years of vegetation succession on the constructed Danish island Peberholm

Peberholm is a constructed Danish island in the Øresund strait. It was primarily constructed by calcareous clay from the sea floor, and is traversed by a highway and a railway. Being constructed from material without a seed bank, Peberholm constituted a good opportunity to study primary succession in an anthropogenic context. In this study, data from a survey of the vascular plant community of Peberholm was studied. The data span over a 22 year‐period, between 1999 and 2020. The development of the flora was analysed with regards to indicators for environmental factors and vegetation types, as well as occurrence of alien species or species of conservation concern. Peberholm experienced a rapid succession during its first five years. The effects of the initial ground disturbance quickly wore off, resulting in a relative decline in plant communities associated with ruderal land. These highly anthropogenic habitats were replaced with grasslands. The shrubification also began early on. The rapid initial changes were then replaced with a much slower but also more continuous change, resulting in the development of both more natural grasslands and an increased shrubification. Although several rare or threatened species colonized Peberholm from the beginning, the conservation value of the flora on a whole increased during the succession process of forming more natural vegetation types. The succession process demonstrated at Peberholm has more in common with the succession at urban soils than with naturally occurring primary succession.

Biological-based and remote sensing techniques to link vegetative and reproductive development and assess pollen emission in Mediterranean grasses

Connecting the signals of the vegetative and reproductive cycles of plants using large-scale phenological techniques is not always an easy task, and this complexity increases considerably when analysing the plant life cycle in grasses, due to the ubiquity and diversity of this taxonomic family. This work integrates remote sensing techniques (NDVI from satellite remote sensing data and greenness from near-surface imagery) and biological-based techniques (airborne pollen monitoring and field observations and sampling) to analyse phenological patterns and productivity in grass-dominated vegetation types. We aim to answer two main applied and unanswered questions; i) how are the specific phases of vegetative and reproductive cycles in grasses linked at the species and plant community level? and ii) which grass-dominant habitats are the major contributors of grass pollen emission to the atmosphere at the plant community level? The multi-scale integration and validation of large-scale methods such as satellite remote sensing data and aerobiological monitoring using high-resolution or field phenological techniques is recommended. The results clearly support the hypothesis that the highest rates of grass pollen emission are successively produced when the major grass-dominated vegetation types go through the final phases of vegetative development during their biological senescence or equivalent phases. At the plant community level, natural and semi-natural grass-dominated vegetation types, rather than grass cropland habitats, constitute the major sources of pollen emission. The major contributors to the grass pollen emission at the species level are also identified. Finally, a positive relationship between year-to-year primary productivity (measured as annual sum or maximum NDVI) and pollen production (measured as airborne pollen intensity) was observed at the community level. This is a very timely study, as the availability of remote sensing data is increasing interest in generating enhanced forecasting model of allergenic airborne pollen.

Changes in soil C–N–P stoichiometry after 20 years of typical artificial vegetation restoration in semiarid continental climate zones

Vegetation restoration is one of the principal strategies for ecosystem recovery in degraded land of fragile regions, which is an important driving factor for soil fertility and elemental circulation. While the relationship between revegetation and soil C–N–P stoichiometry remains unclear. To evaluate the relationships between vegetation restoration and soil C–N–P stoichiometry, the distribution of soil C, N, and P within 0–30 cm soil depth under five typical artificial restored vegetation types on the Loess Plateau was analyzed and the influencing factors were evaluated. The results showed that soil C, N, and P contents were relatively lower at the study site than the mean values for topsoil in China. Compared with other vegetation types (Populus simonii Carr., Pinus tabuliformis Carr., and Caragana korshinskii Kom.), Medicago Sativa L. and Stipa bungeana Trin. helped improve soil fertility better; the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents within the 0–30 cm soil layer respectively maximized under Stipa bungeana Trin. (3.30 g kg−1), Medicago Sativa L. (0.34 g kg−1), and Medicago Sativa L. (0.41 g kg−1). The values of soil C/N, C/P, and N/P for the five vegetation types were 9.50–11.85, 15.36–21.47, and 1.29–1.90, respectively. The contents of SOC and TN under the five vegetation types were significantly (P < 0.001) affected by soil depth and vegetation type (P < 0.001) and decreased with increasing soil depth. However, the TP content was significantly (P < 0.001) affected by vegetation type and not by soil depth. Considering the better adaptability of native species, native herb vegetation types should be considered first for ecological restoration in semiarid continental climate zones.

The origin and evolution of open habitats in North America inferred by Bayesian deep learning models

Some of the most extensive terrestrial biomes today consist of open vegetation, including temperate grasslands and tropical savannas. These biomes originated relatively recently in Earth’s history, likely replacing forested habitats in the second half of the Cenozoic. However, the timing of their origination and expansion remains disputed. Here, we present a Bayesian deep learning model that utilizes information from fossil evidence, geologic models, and paleoclimatic proxies to reconstruct paleovegetation, placing the emergence of open habitats in North America at around 23 million years ago. By the time of the onset of the Quaternary glacial cycles, open habitats were covering more than 30% of North America and were expanding at peak rates, to eventually become the most prominent natural vegetation type today. Our entirely data-driven approach demonstrates how deep learning can harness unexplored signals from complex data sets to provide insights into the evolution of Earth’s biomes in time and space.

THE MAIN NON-TIMBER FOREST PRODUCTS FROM ALBA COUNTY

Non-timber forest products have a lot of other terms which are more or less synonyms like „natural products, wild products”. Non-timber forest products (NTFP) represent a category of products which are provide of wild plants and animals from the forest or from any other natural vegetation types. Around the world humans harvested NTFP from the oldest time. The most common types of NTFP at global level are forest fruits, medicinal plants, fauna of hunting interest and edible mushrooms. Romania has a high potential regarding the harvesting of these types of products due to big diversity of forest and forest site conditions. The aim of this study was to highlight the most important non-timber products from Alba county. First of all was made a selection of most common non-timber products and then were realized a ranking using a set of 19 criteria. The study conclusion was that the most important NTFP from Alba county are honey and hazelnuts follow by golden Chanterelles (Cantharellus cibarius) and Christmas tree.

Evolution and Climate Drivers of NDVI of Natural Vegetation during the Growing Season in the Arid Region of Northwest China

Vegetation plays an important role in linking water, atmosphere, and soil. The dynamic change in vegetation is an important indicator for the regulation of the terrestrial carbon balance and climate change. This study applied trend analysis, detrended correlation analysis, and the Hierarchical Partitioning Algorithm (HPA) to GIMMS NDVI3g data, meteorological data, and natural vegetation types for the period 1983 to 2015 to analyze the temporal and spatial changes in NDVI during the growing season and its driving factors in the arid region of northwestern China. The results showed that: (1) the growing season length (GSL) was delayed, with a regional trend of 8 d/33 a, due to a significant advancement in the start of the growing season (SOS, −7 d/33 a) and an insignificant delay to the end of growing season (EOS, 2 d/33 a). (2) The regional change in NDVI was mainly driven by temperature and precipitation, contributing to variations in NDVI of forest of 36% and 15%, respectively, and in the NDVI of grassland, of 35% and 21%, respectively. In particular, changes to forested land and medium-coverage grassland (Mgra) were closely related to temperature and precipitation, respectively. (3) The spatial distribution of the mean NDVI of forest was closely related with precipitation, temperature, and solar radiation, with these meteorological variables explaining 20%, 15%, and 10% of the variation in NDVI, respectively. Precipitation and solar radiation explained 29% and 17% of the variation in the NDVI of grassland, respectively. The study reveals the spatial–temporal evolution and driving mechanism of the NDVI of natural vegetation in the arid region of Northwest China, which can provide theoretical and data support for regional vegetation restoration and conservation.

Effects of native vegetation on winter thermal performance on extensive green roofs in two different areas (Tokyo and Ishikawa) in Japan

Vegetation plays a key role in many of the ecosystem services provided by green roofs. Green roofs reduce the amount of heat flux through the building envelope but most existing research has focused on hot season cooling functions and not on cold season benefits which can also result in building energy savings. This study examined the effect of different types of native vegetation on heat flux during winter conditions in two locations with different climates in Japan. We established replicated trays (modular green roof system; n = 5 per treatment) with five monoculture treatments and one plant species mixture treatment and an unplanted control treatment on rooftops in Ishikawa and Tokyo. Each tray was fitted with a heat flux sensor at its base and heat flux values were logged every 30 min from December 2015 to March 2016. There were no significant differences in heat flux between the sites for the unplanted controls, indicating that the tray and soil behaved similarly at both sites, however, the relative impact of the different vegetation types was not consistent across the sites. The Tokyo location had more sun and less snow and plants that had relatively low heat flux in Ishikawa showed the opposite pattern in Tokyo. This is consistent with other studies that suggest that in winter conditions with frequent sunny conditions, plants can result in lower energy savings than unplanted controls. Thus, this result addressed the importance of selecting plants in consideration of climate to optimize energy saving with green roofs.

Assessment of butterfly diversity status and conservation issues in Agartala urban localities of Tripura, North East, India

Urbanization leads to a great impact on biodiversity and butterflies (Lepidoptera) are commonly used as a bioindicator species for impact assessment throughout the globe. In order to attain the present status knowledge and conservation issues of butterflies in different impact zones across natural and semi-natural vegetation types, ecopark, residential area, commercial hub etc. in different urban localities of Agartala city, Tripura a random field study was conducted for two years. A total of 76 butterfly species belonging to 6 families and 51 genera were recorded with seasonal variation in their abundance. The family Nymphalidae was dominant in terms of species composition with 28 species and Riodinidae was least one with only single representative. This is the first urban butterfly study in Tripura highlighting present diversity status with some conservation issues like anthropogenic stress, mitigation measures etc. The present report may be useful for environmental impact assessment study in future developmental activities in the study area.

SOIL LOSS ESTIMATION BY USING GIS AND RUSLE APPROACHES IN SOUTH ETHIOPIA, NORTHERN-BILATE (BOYO LAKE AREA) WATERSHED

Soil erosion in Ethiopia exacerbates land degradation, desertification, the decline in productivity, and drought and affects farmers' livelihoods. Therefore, this study aimed to estimate annual soil loss in southern Ethiopia, North-Bilate watershed. For this purpose, the land-based ETM image was divided into seven classes using Erda's Imagine 10.5. Soil, topography, and precipitation data were also obtained from various sources and analyzed in Arc GIS 10.8. Accordingly, five factors (soil erosivity, erodibility, topography, cover management, and support practice) were calculated in ArcGIS 10.8 using the RUSLE model to estimate annual soil loss. As a result, 537035.13 ha (96.1%) and 16521.21 ha (3.1%) of the watershed showed very little and little water erosion, respectively. As can be seen, about 99% of the watershed area had a lower (0.64.73 t/ha/year) risk of soil erosion, while the remaining 1% of the watershed area had a moderate to extreme soil erosion state; which remove a large amount (64.73 1500 t/ha/year) of a clay soil from the riverbanks and muddy areas, mainly from upstream of the Bilate River (the largest in the watershed); due to the maximum slope length and steepness and the rapid flow of water. In conclusion, areas with higher rainfall intensity, active human intervention, lots of sandy soil content, sloppy topography, and thinner soil depth are collectively degraded and prone to erosion. Therefore, such vulnerable areas should mitigate their risk by using organized soil and water conservation techniques to conserve the watershed's total land resources. Physical measures such as terracing and dams should be implemented. In addition, to preserve and increase the biodiversity of the study area, the planting of various types of native vegetation and plantation tree species should be carried out with a viable afforestation and reforestation program.

النمذجة المكانية لأقاليم الملائمة الزراعية في قضاء هيت

The research aims to the modeling of agricultural suitability regions in Heet district, so the problem of the research was to determine the general reality by modeling the spatial analysis of the regions of agricultural suitability in Heet district. There are three types of agricultural viability, including: first type of high quality, which has an area of 3380 Acres, the second region is average validity, which has an area of 2920 Acres, and the third region is low validity, which has an area of (280) Acres. The study consists of three sections, the first section includes the natural factors in the study area, including topography and climate, combining its elements, water resources, types of soil and natural vegetation. As for the second section, it includes the human factors in the study area, represented by the population, its numbers and the labor force, with reference to agricultural holdings, transportation methods, irrigation methods, agricultural mechanization, and the number of pumps and wells in the study area. While the third section deals with the most important areas suitable for agriculture in Hit district, leading to the realization of cartographic models showing the most important regions suitable for agriculture, in addition to the most important conclusions and recommendations within this study.

Differentiation of natural scrub communities of the Cotoneastro-Amelanchieretum group in Central Europe.

Most of Central European rocky scrub communities formed by Cotoneaster integerrimus, Juniperus communis and Amelanchier ovalis are included in the association Cotoneastro-Amelanchieretum (= Junipero-Cotoneasteretum). However, this leads to the creation of syntaxon whose internal diversity is so great that it seems necessary to examine validity of its existence in the current form. This diversity entails species composition, habitat requirements and geographical distribution. Therefore, we posed the following objectives: i) to investigate the variability of species composition of the rocky scrub; (ii) to determine if there are ecological differences between the communities distinguished by species variability; (iii) to determine the geographical ranges of individual syntaxa. Altogether we analyzed 387 phytosociological relevés from Central Europe. Vegetation types of rocky scrubs were identified using the unsupervised K-means algorithm and detrended correspondence analysis. Mean Ellenberg’s indicator values were applied to identify the environmental gradients shaping the plant communities. Obtained results confirmed the validity of dividing this broadly defined syntaxon into six distinct vegetation units. In order to present the studied communities in a broader context, we included into our analyses other rocky scrub with the occurrence of Cotoneaster sp. and A. ovalis, which formed the remaining three clusters. The observed differences in species composition were further supported by significant differences in soil reaction, temperature and continentality between the syntaxa. Moreover, the distinguished communities differed among one another in geographical range. Our study provides a new typology of the selected type of natural rocky scrub vegetation in Central Europe which involves environmental aspects, hence better reflects community-habitat relationships. This study also indicates a need for further revision of the classification of other types of natural scrub communities. Such classification should be based on modern data analysis methods and should primarily focus on lower vegetation units at pan-European scale.

Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes.

The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and processes that couple vegetation and climate. Dynamic global vegetation models (DGVMs) have been widely applied to describe the distribution of vegetation types and their future dynamics in response to climate change. As a process‐based approach, it partly relies on hard‐coded climate thresholds to constrain the distribution of vegetation. What thresholds to implement in DGVMs and how to replace them with more process‐based descriptions remain among the major challenges. In this study, we employ machine learning using decision trees to extract large‐scale relationships between the global distribution of vegetation and climatic characteristics from remotely sensed vegetation and climate data. We analyse how the dominant vegetation types are linked to climate extremes as compared to seasonally or annually averaged climatic conditions. The results show that climate extremes allow us to describe the distribution and eco‐climatological space of the vegetation types more accurately than the averaged climate variables, especially those types which occupy small territories in a relatively homogeneous ecological space. Future predicted vegetation changes using both climate extremes and averaged climate variables are less prominent than that predicted by averaged climate variables and are in better agreement with those of DGVMs, further indicating the importance of climate extremes in determining geographic distributions of different vegetation types. We found that the temperature thresholds for vegetation types (e.g. grass and open shrubland) in cold environments vary with moisture conditions. The coldest daily maximum temperature (extreme cold day) is particularly important for separating many different vegetation types. These findings highlight the need for a more explicit representation of the impacts of climate extremes on vegetation in DGVMs.

Vegetation mapping of the Dzharylhach Island (Ukraine)

Abstract Dzharylhach Island is the largest one in the Black Sea. It is the part of the “Dzharylhatskyi” National Nature Park, which located in the Southern Ukraine. A 1 : 10000 scale vegetation map of Dzharylhach Island has been developed. The main unit for mapping is a complex of associations. In total 28 of such complexes were identified. The map shows the territorial differentiation of vegetation. It has also been used to reconstruct the island vegetation changes over the past 90 and 20 years. A comparison of cartographic materials revealed that the predominant processes in vegetation cover are halophytization and xerophytization of communities. The most distributed types of communities on the island are aquatic – Zosteretea, halophytic – Festuco-Puccinellietea and psammophytic – Festucetea vaginatae. Due to specific hydrological and soil conditions, the northern spit and shores of the island represent natural vegetation types only.

Mapping native and non-native vegetation in the Brazilian Cerrado using freely available satellite products

Native vegetation across the Brazilian Cerrado is highly heterogeneous and biodiverse and provides important ecosystem services, including carbon and water balance regulation, however, land-use changes have been extensive. Conservation and restoration of native vegetation is essential and could be facilitated by detailed landcover maps. Here, across a large case study region in Goiás State, Brazil (1.1 Mha), we produced physiognomy level maps of native vegetation (n = 8) and other landcover types (n = 5). Seven different classification schemes using different combinations of input satellite imagery were used, with a Random Forest classifier and 2-stage approach implemented within Google Earth Engine. Overall classification accuracies ranged from 88.6–92.6% for native and non-native vegetation at the formation level (stage-1), and 70.7–77.9% for native vegetation at the physiognomy level (stage-2), across the seven different classifications schemes. The differences in classification accuracy resulting from varying the input imagery combination and quality control procedures used were small. However, a combination of seasonal Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (surface reflectance) imagery resulted in the most accurate classification at a spatial resolution of 20 m. Classification accuracies when using Landsat-8 imagery were marginally lower, but still reasonable. Quality control procedures that account for vegetation burning when selecting vegetation reference data may also improve classification accuracy for some native vegetation types. Detailed landcover maps, produced using freely available satellite imagery and upscalable techniques, will be important tools for understanding vegetation functioning at the landscape scale and for implementing restoration projects.

Changes in vegetation and soil properties across 12 years after afforestation in the hilly-gully region of the Loess Plateau

Vegetation restoration is the primary method used to prevent soil erosion and improve the ecological environment. The objective of this study was to explore how vegetation and soil properties changed over time in natural and artificial vegetation types. We conducted vegetation surveys in four permanent plots over 12 years (2007–2018) and measured soil properties in 2007, 2013, and 2016. The results showed that the change in species composition in natural vegetation was a continuous and progressive process. After approximately ten years of natural herb restoration, trees began to appear and formed sparse forests. In artificial vegetation, the species composition of the undergrowth varied under Robinia pseudoacacia forests during restoration years, and was dominated by Poaceae and annual plants that could tolerate shade and drought. Species composition was stable under Caragana korshinskii shrubs, where the undergrowth was dominated by perennial plants that were similar to natural vegetation. In different vegetation types, species richness, diversity, and herb community cover fluctuated, while the succession rate decreased with the number of restoration years. The soil moisture condition was better in natural vegetation than in artificial vegetation, and could be maintained near the stable field capacity. The soil moisture was supplemented to 280 cm in R. pseudoacacia forests and 320 cm in C. korshinskii shrubs in a year with extreme rainfall, but the dry soil layer returned in the following years. Soil nutrients improved over time, especially in artificial vegetation, which appears to be better than natural vegetation. In general, natural vegetation improved plant community and soil properties. Artificial vegetation only improved soil nutrients, but caused soil desiccation which is difficult to recover. Therefore, the natural vegetation restoration model of sparse forest grassland was better than artificial vegetation model.