ABSTRACT
Association is the basic unit of plant community classification. Exploring the distribution of plant associations can help improve our understanding of biodiversity conservation. Different associations depend on different habitats and studying the association level is important for ecological restoration, regional ecological protection, regulating the ecological balance, and maintaining biodiversity. However, previous studies have only focused on suitable distribution areas for species and not on the distribution of plant associations. Larix gmelinii is a sensitive and abundant species that occurs along the southern margin of the Eurasian boreal forests, and its distribution is closely related to permafrost. In this study, 420 original plots of L. gmelinii forests were investigated. We used a Maxent model and the ArcGIS software to project the potential geographical distribution of L. gmelinii associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. We used the multi-classification logistic regression analysis method to obtain the response of the suitable area change for the L. gmelinii alliance and associations to climate change under different climate scenarios. Results revealed that temperature is the most crucial factor affecting the distribution of L. gmelinii forests and most of its associations under different climate scenarios. Suitable areas for each association type are shrinking by varying degrees, especially due to habitat loss at high altitudes in special terrains. Different L. gmelinii associations should have different management measures based on the site conditions, composition structure, growth, development, and renewal succession trends. Subsequent research should consider data on biological factors to obtain more accurate prediction results.
ABSTRACT
The relationship between the structure and function of forest ecosystems is the main intere-sts in the research area of forest ecology and management. However, over complex terrains in particular, these studies had been challenged as uneasy tasks due to the limitations in the forest survey and measurement techniques and other supporting technologies. Chinese Academy of Sciences (CAS) funded "Multi-Tower LiDAR/ECFlux Platform for Monitoring the Structure and Function of Secondary Forest Ecosystems" (Multi-Tower Platform, MTP) as a field station network corner-stone research infrastructure project, which was completed by Qingyuan Forest CERN (Chinese Ecosystem Research Network). In a distinctively-bounded and monitored-outlet watershed, the MTP was integrated by light detection and ranging (LiDAR) scanners, eddy covariance (EC) flux instrument systems, whole- and sub-watershed hydrology station network, long-term forest plot arrays, and live data center. Using LiDAR scanning, the MTP can get cloud data for holographic information on canopy structure. The EC-flux instrument system and hydrology station network along with forest plot arrays could ensure the reliability of water and carbon observations over this complex terrain, which allows to verify the studies on flux measurement technologies and methods, as well as to understand the processes of ecohydrology and CO2 exchange between forest ecosystem and the atmosphere. Further, we can also assess the primary ecosystem services, including water conservation and carbon sequestration. All the data from "tower-station" were streamed through wireless network, which would facilitate data monitoring, management, and sharing. There are three tasks of MTP team: 1) defining innovative methods and descriptors to quantify three-dimensional forest structure; 2) developing theories and techniques to measure CO2/H2O fluxes and other trace gases over complex terrains; 3) understanding the relationship between structure and function of forest ecosystems, providing information and rationales for forest management practices to assure broad and sustainable benefits from forests.
