Resolving trade‐offs between economic development and biodiversity conservation needs is crucial in currently developing countries and in particularly sensitive systems harboring high biodiversity. Yet, such a task is challenging because human activities have complex effects on biodiversity. We assessed the effects of intense economic development on Hainan Island (southern China) on different components of biodiversity. This highly biodiverse tropical island has undergone extensive economic development and conversion of forest to agriculture and urban area. We identified 3 main transformation areas (low, medium, and high transformation) based on land‐use, local‐climate, and economic changes across 145 grids (10 × 10 km), and estimated changes in avian biodive6rsity from 1998 to 2013. We recorded ongoing taxonomic biotic homogenization throughout the island. Differences between traditional and directional alpha diversity decreased by 5%. Phylogenetically clustering increased by 0.5 points (W = 7928, p < 0.01), and functional overdispersion increased by 1 point (W = 16,411, p < 0.01). Initial taxonomic, phylogenetic, and functional scores correlated negatively with changes in these scores across all transformation areas (all ps < 0.01). At the local scale, economic and environmental indicators showed complex and divergent effects across transformation areas and biodiversity components. These effects were only partially ameliorated in an ecological function conservation area in the mountainous central part of the island. We found complex effects of economic development on different biodiversity dimensions in different areas with different land uses and protection regimes and between local and regional spatial scales. Profound ecosystem damage associated with economic development was partially averted, probably due to enhanced biodiversity conservation policies and law enforcement, but not without regional‐scale biotic homogenization and local‐scale biodiversity loss.

The COVID‐19 pandemic has strongly disrupted academic activities, particularly in disciplines with a strong empirical component among other reasons by limiting our mobility. It is thus essential to assess emergency remote teaching plans by surveying learners’ opinions and perceptions during these unusual circumstances. To achieve this aim, we conducted a survey during the spring semester of 2021 in an environmental science program to ascertain learners’ perceptions on online and onsite learning activities in ecology‐based modules. We were particularly interested not only in comparing the performance of these two types of activities but also in understanding the role played by learners’ perceptions about nature in shaping this pattern. Environmental science programs are rather heterogeneous from a conceptual point of view and, thus, learners may also be more diverse than in traditional ecology programs, which may affect their interest for ecology‐based modules. We assessed connectedness to nature by computing the reduced version of the Nature Relatedness Scale. Here, we found that online activities systematically obtained significantly lower scores than onsite activities regardless of the wording employed, and that altruistic behaviors were prevalent among learners. Interestingly, scores for both onsite and online activities were strongly influenced by learners’ connectedness to nature, as learners with a stronger connection to nature gave higher scores to both types of activities. Our results suggest that an effort to improve the efficacy of remote learning activities should be the focus of research about teaching methodologies in predominantly empirical scientific disciplines.

The Green Peafowl (Pavo muticus) is vulnerable to anthropogenic pressures and has undergone an extensive decline through much of its range in Southeast Asia. However, little is known about the changing distribution of Green Peafowl in China through historical periods. We described a 5000–6000 years distribution change of Green Peafowl in China by using historical archives. We examined the present distributions of Green Peafowl by using camera traps and transect surveys and predicted the suitable habitat to support future conservation planning for this species. Although Green Peafowl was once widely distributed across China, the species experienced a southward range retreat over the past 5000–6000 years and is now restricted to a small part of Yunnan. The results of prediction from maximum entropy modeling (MaxEnt) showed that the size of suitable habitat of Green Peafowl in Yunnan was 17,132 km2. The suitable habitat concentrated in nine prefectures of Yunnan and Pu’er, Chuxiong, and Yuxi accounted for 48.64%, 27.39% and 15.83%, respectively. These results suggest that central Yunnan can cover most of the current larger and more contiguous populations of Green Peafowl in China and should be protected. Moreover, some areas in southern Yunnan, such as Xishuangbanna, can be a candidate for reestablishing populations, given that the species disappeared in this region less than 20 years ago and has a large remaining habitat.