Natural forests and abandoned agricultural lands are increasingly replaced by monospecific forest plantations that have poor capacity to support biodiversity and ecosystem services. Natural forests harbour plants belonging to different mycorrhiza types that differ in their microbiome and carbon and nutrient cycling properties. Here we describe the MycoPhylo field experiment that encompasses 116 woody plant species from three mycorrhiza types and 237 plots, with plant diversity and mycorrhiza type diversity ranging from one to four and one to three per plot, respectively. The MycoPhylo experiment enables us to test hypotheses about the plant species, species diversity, mycorrhiza type, and mycorrhiza type diversity effects and their phylogenetic context on soil microbial diversity and functioning and soil processes. Alongside with other experiments in the TreeDivNet consortium, MycoPhylo will contribute to our understanding of the tree diversity effects on soil biodiversity and ecosystem functioning across biomes, especially from the mycorrhiza type and phylogenetic conservatism perspectives.

As an important ecosystem type in the coastal zone, mangroves have important ecological functions, such as maintaining coastal biodiversity, preventing wind and consolidating the coast, promoting silt and building land. It is of great significance to understand the protected status of mangroves in the context of climate change and rapid urbanization. Based on the mangrove classification data from remote sensing interpretation, through vacancy analysis, the in-situ protection status of mangroves in China is analyzed. The results show that the total area of mangroves distributed in China is 264 km² (excluding the statistical data of Hong Kong, Macao and Taiwan), of which 61.4% are protected in natural reserves. In terms of the main provinces where mangroves are distributed, the mangrove area distributed in Hainan Province is small but the protection proportion is high, while the mangrove area distributed in Guangxi and Guangdong Province is large but the proportion of protected areas is relatively low. Among the three mangrove types, Rhizophora apiculate-Xylocarpus granatum and Rhizophora stylosa-Bruguiera gymnorrhiza had high proportions (>90%) covered by reserves, but relatively small areas. In contrast, Kandelia candel-Aegiceras corniculatum-Avicennia marina had relatively low reserve coverage (52.6%), but a large area. The study puts forward the key areas of mangrove distribution outside the nature reserve, and suggests that they should be protected by delimiting ecological protection red lines.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

Root turnover is a key process of terrestrial ecosystem carbon cycle, which is of great significance to the study of soil carbon pool changes and global climate change. However, because there are many measurement and calculation methods of root turnover, the results obtained by different methods are quite different, and the current research on root turnover of forest ecosystem on the global regional scale is not sufficient, so the change law of root turnover of global forest ecosystem is still unclear. By collecting literature data and unifying the calculation method of turnover rate, this study integrates the spatial pattern of fine root turnover of five forest types in the world, and obtains the factors affecting fine root turnover of forest ecosystem in combination with soil physical and chemical properties and climate data. The results showed that there were significant differences in fine root turnover rate among different forest types, and it gradually decreased with the increase of latitude; the turnover rate of fine roots in forest ecosystem is positively correlated with annual average temperature and annual average precipitation; fine root turnover rate of forest ecosystem is positively correlated with soil organic carbon content, but negatively correlated with soil pH value. This study provides a scientific basis for revealing the law and mechanism of fine root turnover in forest ecosystem.

Forest is the main carbon sink of terrestrial ecosystem. Due to the unique growth characteristics of plants, the response of their growth status and physiological activities to climate change will affect the carbon cycle process of forest ecosystem. Based on the local scale CO₂ flux and temperature observation data recorded by the FLUXNET registration site and Harvard Forest FLUX observation tower from 2000 to 2012, combined with the phenological model, this paper analyzes the impact of temperature changes on CO₂ flux in temperate forest ecosystems. The results show that: (1) the maximum NEE in 2000–2012 was 298.13 g·m^-2·a^-1, which occurred in 2010. Except in the 2010 and 2011, the annual NEE in other years was negative. (2) NEE, GPP, temperature and phenology models have good fitting effects (R² > 0.8), which shows that the stable period of photosynthesis in temperate mixed forest ecosystem is mainly concentrated in summer, and vegetation growth is the dominant factor of carbon cycle in temperate mixed forest ecosystem. (3) The linear fitting results of the change time points of air temperature (maximum point, minimum point and 0 point date) and the change time points of NEE and GPP (maximum point, minimum point and 0 point date) show that there is a significant positive correlation between air temperature and CO₂ flux (P < 0.01), and the change of air temperature affects the carbon cycle process of temperate mixed forest ecosystem.

The management of Mediterranean mountains need to know whether or not the flora is adapted to respond to fire and, if so, through what mechanisms. Serpentine outcrops constitute particular ecosystems in the Mediterranean Basin, and plants need to make an additional adaptive effort. The objective of this study is to know the response to fire of the main members of the group of serpentine plants, which habit the Spanish Mediterranean ultramafic mountain, to help in their management. For this purpose, monitoring plots were established on a burned ultramafic outcrop, which was affected by fire in August 2012.They were located in the Mediterranean south of the Iberian Peninsula, Andalusia region. The dominant vegetation of this serpentine ecosystem had been studied previously to fire; it was a shrubland composed of endemic serpentinophytes (small shrubs and perennial herbs) included in Digitali laciniatae-Halimietum atriplicifolii plant association (Cisto-Lavanduletea class) in an opened pine forest. The post-fire response of the plants was studied in the stablished burned plots by field works through permanent 200 x 10 m transect methods, consisting on checking whether they were resprouters, seeders, both of them or if they showed no survival response. Additional information about fire related functional traits is provided for the studied taxa from other studies. Of the total of plants studied (23 taxa), 74% acted as resprouters, 30% as seeders, some of which also had the capacity to resprout (13%), and only 9% of the plants did not show any survival strategy. The presence of a resprouting burl was not high (17%), although serpentine small shrubs such as Bupleurum acutifolium and the generalist Teucrium haenseleri had this kind of organ. The herbaceous taxa Sanguisorba verrucosa, Galium boissieranum and Linum carratracense were seen to be resprouters and seeders. The serpentine obligated Ni-accumulator, Alyssum serpyllifolium subsp. malacitanum, did not show any survival strategy in the face of fire and therefore their populations need monitoring after fires. In the studied ecosystems no species had traits that would protect the aerial part of the plant against fire, although most of the species are capable of post-fire generation by below ground buds. Our results show that the ecosystem studied, composed of taxa with a high degree of endemism and some of them threatened, is predominantly adapted to survival after a fire, although their response capacity may be decreased by environmental factors.