Spatio-temporal monitoring of marsh vegetation phenology and its response to hydro-meteorological factors using CCDC algorithm with optical and SAR images: In case of Honghe National Nature Reserve, China

Woody encroachment induced earlier and extended growing season in boreal wetland ecosystems

Woody plant encroachment (WPE), a widespread ecological phenomenon globally, has significant impacts on ecosystem structure and functions. However, little is known about how WPE affects phenology in wetland ecosystems of middle and high latitudes. Here, we investigated the regional-scale effects of WPE on the start (SOS), peak (POS), end (EOS), and length (GSL) of the growing season in boreal wetland ecosystems, and their underlying mechanisms, using remote sensing dataset during 2001-2016. Our results showed that WPE advanced the annual SOS and POS, while delaying EOS and extending GSL in boreal wetlands with these impacts increasing over time. When boreal wetland ecosystems were fully encroached by woody plants, the SOS and POS were advanced by 12.17 and 5.65 days, respectively, the EOS was postponed by 2.74 days, and the GSL was extended by 15.21 days. We also found that the impacts of WPE on wetland SOS were predominantly attributed to the increased degree of WPE (α), while climatic factors played a more significant role in controlling the POS and EOS responses to WPE. Climate change not only directly influenced phenological responses of wetlands to WPE but also exerted indirect effects by regulating soil moisture and α. Winter precipitation and spring temperature primarily determined the effects of WPE on SOS, while its impacts on POS were mainly controlled by winter precipitation, summer temperature, and precipitation, and the effects on EOS were mainly determined by winter precipitation, summer temperature, and autumn temperature. Our findings offer new insights into the understanding of the interaction between WPE and wetland ecosystems, emphasizing the significance of considering WPE effects to ensure accurate assessments of phenology changes.

Variation in Vegetation Phenology and Its Response to Climate Change in Marshes of Inner Mongolian

Inner Mongolia has a large area of marsh wetland in China, and the marsh in this region is important for maintaining ecological balance. Understanding variations in vegetation phenology of marsh ecosystems and their responses to climatic change is crucial for vegetation conservation of marsh wetlands in Inner Mongolia. Using the climate and NDVI data during 2001-2020, we explored the spatiotemporal changes in the start (SOS), end (EOS), and length (LOS) of vegetation growing season and analyzed the effects of climate change on vegetation phenology in the Inner Mongolia marshes. Results showed that SOS significantly (p < 0.05) advanced by 0.50 days/year, EOS significantly delayed by 0.38 days/year, and thus LOS considerably increased by 0.88 days/year during 2001-2020 in marshes of Inner Mongolia. Warming temperatures in winter and spring could significantly (p < 0.05) advance the SOS, and increased summer and autumn temperatures could delay EOS in Inner Mongolia marshes. We found for the first time that daytime maximum temperature (T_max) and night minimum temperature (T_min) had asymmetric effects on marsh vegetation phenology. Increasing T_max had a stronger advancing effect on SOS than increasing T_min from December to April. The increase of T_min in August could obviously delayed EOS, while increasing T_max in August had no significant effect on EOS. This study highlights that the asymmetric influences of nighttime and daytime temperatures should be taken into account in simulating marsh vegetation phenology in temperate arid and semi-arid regions worldwide, particularly in the context of global asymmetric diurnal warming.

A novel framework for vegetation change characterization from time series landsat images

Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to reconstructing vegetation change history, investigating change properties, and evaluating the ecological effects. However, current remote sensing techniques are primarily focused on break detection but ignore long-term trend analysis. In this study, we proposed a novel framework based on a change detection algorithm and a trend analysis method that could integrate both short-term disturbance detection and long-term trends to comprehensively assess vegetation change. With this framework, we characterized the vegetation changes in Zhejiang Province from 1990 to 2020 using Landsat and landcover data. Benefiting from combining break detection and long-term trend analysis, the framework showcased its capability of capturing a variety of dynamics and trends of vegetation. The results show that the vegetation was browning in the plains while greening in the mountains, and the overall vegetation was gradually greening during the study period. By comparison, detected vegetation disturbances covered 57.71% of the province's land areas (accounting for 66.92% of the vegetated region) which were mainly distributed around the built-up areas, and most disturbances (94%) occurred in forest and cropland. There were two peak timings in the frequency of vegetation disturbances: around 2003 and around 2014, and the proportions of more than twice disturbances in a single location were low. The results illustrate that this framework is promising for the characterization of regional vegetation growth, including long-term trends and short-term features. The proposed framework enlightens a new direction for the continuous monitoring of vegetation dynamics.