Early warning signals for landscape connectivity and resilient conservation solutions

Abstract

The ever‐increasing and unprecedented impacts of human activities on natural landscapes are dramatically altering the heterogeneity of habitats and biodiversity. We developed a holistic resilience‐based framework to identify the early warning points of climate‐gradient landscape connectivity; the results offer the first map capable of providing information about landscape connectivity in the coastal provinces of mainland China. The results show that only 24% of natural/seminatural lands retained sufficient connectivity, which is considered to be high‐quality patches for animals to move through temperature gradient corridors. Moreover, the critical junctions, such as the tipping points and early warning points of landscape connectivity, were mainly detected in seminatural lands (forests and grasslands). Increasing connections in these seminatural lands initiated the permeability of landscape connectivity in coastal areas, which are essential for accessing suitable habitats with low temperatures. By connecting fragmented patches into a landscape network, the transition zones in seminatural lands highlight priority locations for ecologists and conservation managers as natural solutions to configure the most effective conservation areas.

Conflict or Coordination? The Spatiotemporal Relationship Between Humans and Nature on the Qinghai‐Tibet Plateau

“…The HAI constructed in this research largely follows the evaluation index systems established by previous studies, encompassing population density, GDP, nighttime light, land cover, and road networks (Huang et al., 2022; Mu et al., 2022; Xu et al., 2016). However, given that grasslands occupy over 60% of the QTP (Li et al., 2019; Zeng et al., 2022), we employed grazing intensity (i.e., the number of grazing livestock per square kilometer) in lieu of previously used pasture area to improve the accuracy of quantifying human activities in grassland ecosystems. Additionally, unlike previous studies that typically assigned equal weights to all indicators, we adopted a different approach based on expert judgment.…”

Human Activity Intensity and Its Spatial-Temporal Evolution in China’s Border Areas

“…This dataset classified the land surface into 22 types using the United Nations Food and Agriculture Organization's (UN FAO) Land Cover Classification System (LCCS). Each land type was scored based on the degree of human activity [44][45][46]. Based on the method of Sanderson et al [18], we assigned a score for each layer ranging from 0 (no human activity) to 10 (maximum human activity) (Table 1).…”

Spatiotemporal evolution and the detection of key drivers in the resilience of cultivated land system in major grain‐producing regions of China

“…The research perspectives mainly include disaster prevention and mitigation (Feofilovs & Romagnoli, 2021), public management (Assefa & Hans‐Rudolf, 2016; Bhagavathula et al, 2021), industrial development (Namvar & Bamdad, 2021), planning guidelines (Krab et al, 2020), and supporting infrastructure construction. Moreover, the research on resilience focuses primarily on qualitative analysis, and the quantitative analysis is insufficient (Chen et al, 2019; Folke, 2016; Hong et al, 2021; Li, Yin, & Li, 2019).…”