Refine
Year of publication
- 2023 (2) (remove)
Document Type
- Article (2)
Is part of the Bibliography
- yes (2)
Keywords
- Carbon sequestration (1)
- Climate adaptation (1)
- Convolutional neural networks (CNNs) (1)
- Plant communities (1)
- Plant materials (1)
- Remote sensing (1)
- Semi-natural grasslands (1)
- Soils (1)
- Target species (1)
- Unmanned aerial vehicles (UAVs) (1)
Institute
- Fakultät AuL (2) (remove)
Grasslands are ubiquitous globally, and their conservation and restoration are critical to combat both the biodiversity and climate crises. There is increasing interest in implementing effective multifunctional grassland restoration to restore biodiversity concomitant with above- and belowground carbon sequestration, delivery of carbon credits and/or integration with land dedicated to solar panels. Other common multifunctional restoration considerations include improved forage value, erosion control, water management, pollinator services, and wildlife habitat provisioning. In addition, many grasslands are global biodiversity hotspots. Nonetheless, relative to their impact, and as compared to forests, the importance of preservation, conservation, and restoration of grasslands has been widely overlooked due to their subtle physiognomy and underappreciated contributions to human and planetary well-being. Ultimately, the global success of carbon sequestration will depend on more complete and effective grassland ecosystem restoration. In this review, supported by examples from across the Western world, we call for more strenuous and unified development of best practices for grassland restoration in three areas of concern: initial site conditions and site preparation; implementation of restoration measures and management; and social context and sustainability. For each area, we identify the primary challenges to grassland restoration and highlight case studies with proven results to derive successful and generalizable solutions.
Semi-natural grasslands (SNGs) are an essential part of European cultural landscapes. They are an important habitat for many animal and plant species and offer a variety of ecological functions. Diverse plant communities have evolved over time depending on environmental and management factors in grasslands. These different plant communities offer multiple ecosystem services and also have an effect on the forage value of fodder for domestic livestock. However, with increasing intensification in agriculture and the loss of SNGs, the biodiversity of grasslands continues to decline. In this paper, we present a method to spatially classify plant communities in grasslands in order to identify and map plant communities and weed species that occur in a semi-natural meadow. For this, high-resolution multispectral remote sensing data were captured by an unmanned aerial vehicle (UAV) in regular intervals and classified by a convolutional neural network (CNN). As the study area, a heterogeneous semi-natural hay meadow with first- and second-growth vegetation was chosen. Botanical relevés of fixed plots were used as ground truth and independent test data. Accuracies up to 88% on these independent test data were achieved, showing the great potential of the usage of CNNs for plant community mapping in high-resolution UAV data for ecological and agricultural applications.