Intensive land-use drives regional-scale homogenization of plant communities

Widespread homogenization in vegetation activities along the elevational gradients across the Himalaya over the past 40 years

Mountainous regions are vital biodiversity hotspots with high heterogeneity, providing essential refugia for vegetation. However, climate change threatens this diversity with the potential homogenization of the distinct environmental conditions at different elevations. Here, we used a time-series (1985-2023) of Normalized Difference Vegetation Index (NDVI) from Landsat archives (30 m) to quantify vegetation changes across an elevation gradient on Himalaya Mountain. Our analysis revealed that over the past 40 years, the Himalayas have experienced widespread greening, accompanied by homogenization of vegetation across elevations. This homogenization, characterized by a reduction in the differences between high and low elevations, can be attributed to two main factors: (1) increased warming and a higher snowmelt rate at high elevations, facilitating rapid changes in high-elevation vegetation activities; and (2) higher anthropogenic disturbance at low and mid elevations, thus inhibiting low-elevation vegetation. These factors have resulted in a reduction of habitat differentiation along the mountain slopes, homogenizing vegetation and potentially threatening the unique biodiversity adapted to specific elevational zones. Our findings emphasize the urgent need for conservation strategies that prioritize the protection of heterogeneous mountain habitats to preserve their rich biodiversity in the face of climate change.

Impacts of landscape patterns on plant species diversity at a global scale

Landscape patterns are important drivers of biodiversity. Owing to differences in vegetation types, sampling methods, diversity measures, spatial scales, and landscape levels, the impact of landscape patterns on biodiversity remains widely debated. Using a global standardized plant community database and land use and land cover maps at 30-m resolution, for the period 1990-2017, we calculated plant species α- and β-diversity, and landscape metrics at patch- and landscape-levels, and discerned the direct and indirect impacts of landscape patterns on plant species diversity based on environmental factors, namely climate, spatial features, and human disturbance. We found that landscape patterns exhibited the main indirect effects, whereas climate factors exhibited dominant direct effects on plant α-diversity via the direct effects of patch patterns and functional traits. With respect to β-diversity, landscape-level patterns exerted more direct than indirect effects. These effects are strongly dependent on scale. Landscape- and patch-level patterns had opposite effects on plant diversity, depending on their composition and spatial structure, demonstrating that their effects could be mediated by one another. The adaptation of plants to landscape patterns is mainly through variations in leaf area, plant height, specific leaf area, stem density, seed biomass, and other seed-dispersal traits, which vary across vegetation types. Our findings highlight the importance of functional traits and diversity in understanding the mechanism by which landscape patterns influence plant species diversity; accordingly, we recommend balancing the spatial structure of patch- and landscape-level patterns to enhance variation in functional traits, and, ultimately, to maintain global plant diversity.

Disentangling direct and indirect drivers of farmland biodiversity at landscape scale

To stop the ongoing decline of farmland biodiversity there are increasing claims for a paradigm shift in agriculture, namely from conserving and restoring farmland biodiversity at field scale (α-diversity) to doing it at landscape scale (γ-diversity). However, knowledge on factors driving farmland γ-diversity is currently limited. Here, we quantified farmland γ-diversity in 123 landscapes and analysed direct and indirect effects of abiotic and land-use factors shaping it using structural equation models. The direction and strength of effects of factors shaping γ-diversity were only partially consistent with what is known about factors shaping α-diversity, and indirect effects were often stronger than direct effects or even opposite. Thus, relationships between factors shaping α-diversity cannot simply be up-scaled to γ-diversity, and also indirect effects should no longer be neglected. Finally, we show that local mitigation measures benefit farmland γ-diversity at landscape scale and are therefore a useful tool for designing biodiversity-friendly landscapes.

Exploring subjective well-being and ecosystem services perception in the agro-pastoral ecotone of northern China

Understanding stakeholders' perceptions about human well-being and ecosystem services is essential for designing efficient public policies and sustainable environmental management that help to improve people's quality of life. Despite the fragile ecosystem and poverty concentration in the agro-pastoral ecotone, research in this field remains scarce. We selected a typical agro-pastoral ecotone, Duolun County, Inner Mongolia, China, to explore how socioeconomic and demographic factors affect subjective well-being and perceptions of ecosystem services through structural equation modelling (SEM) and canonical correspondence analysis (CCA). Our results showed that health had the highest correlation with subjective well-being among the five dimensions, but respondents were least satisfied with it. Formal education had the greatest effect on subjective well-being, followed by age, income, and livelihood. Gender had no effect on subjective well-being. Older respondents with lower formal education who had a lower level of subjective well-being considered supporting and provisioning services more important for well-being. In contrast, younger respondents with higher education levels (mostly jobs not associated with working the land) mainly valued cultural services. Finally, we discussed the factors that influence subjective well-being and perceptions of ecosystem services and their implications for local management decision-making.

Does Intensive Land Use Contribute to Energy Efficiency?-Evidence Based on a Spatial Durbin Model

In order to ensure the safety of cultivated land and promote urban productivity, the Chinese government began to promote intensive land use at the legislative level from 2014. At the same time, China faces problems of carbon emissions and energy, so we need to improve energy efficiency. Therefore, this paper aims to verify the spatial effects of intensive land use on energy efficiency of China from 2009 to 2018. We further use an index system to quantify intensive land use and use chain DEA (data envelope analysis) to quantify energy efficiency. This paper finds that: (1) intensive land use can significantly improve energy efficiency. A 1% increase in the level of intensive land use will increase energy efficiency by 1.3%. (2) The intensive use of land in one city will have a negative impact on the energy efficiency of surrounding cities. The reason is that the intensive use of land in a single city may lead to the transfer of energy-consuming industries to surrounding cities. (3) The impact of intensive land use on the energy efficiency of surrounding cities has negative threshold characteristics, and the negative impact will be weakened as the level of integration of the city increases.

Diversity of European habitat types is correlated with geography more than climate and human pressure

Habitat richness, that is, the diversity of ecosystem types, is a complex, spatially explicit aspect of biodiversity, which is affected by bioclimatic, geographic, and anthropogenic variables. The distribution of habitat types is a key component for understanding broad-scale biodiversity and for developing conservation strategies. We used data on the distribution of European Union (EU) habitats to answer the following questions: (i) how do bioclimatic, geographic, and anthropogenic variables affect habitat richness? (ii) Which of those factors is the most important? (iii) How do interactions among these variables influence habitat richness and which combinations produce the strongest interactions? The distribution maps of 222 terrestrial habitat types as defined by the Natura 2000 network were used to calculate habitat richness for the 10 km × 10 km EU grid map. We then investigated how environmental variables affect habitat richness, using generalized linear models, generalized additive models, and boosted regression trees. The main factors associated with habitat richness were geographic variables, with negative relationships observed for both latitude and longitude, and a positive relationship for terrain ruggedness. Bioclimatic variables played a secondary role, with habitat richness increasing slightly with annual mean temperature and overall annual precipitation. We also found an interaction between anthropogenic variables, with the combination of increased landscape fragmentation and increased population density strongly decreasing habitat richness. This is the first attempt to disentangle spatial patterns of habitat richness at the continental scale, as a key tool for protecting biodiversity. The number of European habitats is related to geography more than climate and human pressure, reflecting a major component of biogeographical patterns similar to the drivers observed at the species level. The interaction between anthropogenic variables highlights the need for coordinated, continental-scale management plans for biodiversity conservation.

Effect of planting alien Robinia pseudoacacia trees on homogenization of Central European forest vegetation

Biological homogenization is a process of biodiversity loss driven by the introduction and invasion of widespread species and the extinction of specialized, endemic species. This process has accelerated in recent years due to intensive human activities. We focused our study on large areas of forest vegetation that have not yet been intensively studied. Forest management, especially the planting of alien trees, could play a key role in the homogenization process because alien trees can act as habitat 'transformers' influencing vegetation through creating different environmental conditions. Several types of native forests (hardwood floodplain forests, oak forests, and oak-hornbeam forests) have in many regions been replaced by Robinia pseudoacacia plantations. The huge diversity of native broadleaved deciduous forests in the Pannonian and Carpathian regions, with many local differences and considerable geographical variability, could be exposed to the homogenization process due to the planting of Robinia pseudoacacia. We used 282 paired plots of Robinia pseudoacacia-dominated forests and native forests with a distance of 50-250 m among them under the same environmental conditions to avoid the influence of the variability of local environmental conditions on the forest undergrowth. We found out that the replacement of native forests by plantations of Robinia pseudoacacia plays a crucial role in the homogenization process in forest vegetation by unifying microenvironmental conditions of stands and removing the geographically specified variability of plant communities from previous four classes to single one. The replacement reduced total species pool from 422 to 372 species and supported the occurrence of widespread, generalist plant species in the undergrowth.