Integration of InVEST-habitat quality model with landscape pattern indexes to assess mountain plant biodiversity change: A case study of Bailongjiang watershed in Gansu Province

Journal of Geographical Sciences - Mountains in western China, hosted rich biodiversity and millions of people and inhabitant with vital ecosystem services, had experienced the most serious...     

Detection of crossover time scales in multifractal detrended fluctuation analysis

Fractal is employed in this paper as a scale-based method for the identification of the scaling behavior of time series. Many spatial and temporal processes exhibiting complex multi(mono)-scaling behaviors are fractals. One of the important concepts in fractals is crossover time scale(s) that separates distinct regimes having different fractal scaling behaviors. A common method is multifractal detrended fluctuation analysis (MF-DFA). The detection of crossover time scale(s) is, however, relatively subjective since it has been made without rigorous statistical procedures and has generally been determined by eye balling or subjective observation. Crossover time scales such determined may be spurious and problematic. It may not reflect the genuine underlying scaling behavior of a time series. The purpose of this paper is to propose a statistical procedure to model complex fractal scaling behaviors and reliably identify the crossover time scales under MF-DFA. The scaling-identification regression model, grounded on a solid statistical foundation, is first proposed to describe multi-scaling behaviors of fractals. Through the regression analysis and statistical inference, we can (1) identify the crossover time scales that cannot be detected by eye-balling observation, (2) determine the number and locations of the genuine crossover time scales, (3) give confidence intervals for the crossover time scales, and (4) establish the statistically significant regression model depicting the underlying scaling behavior of a time series. To substantive our argument, the regression model is applied to analyze the multi-scaling behaviors of avian-influenza outbreaks, water consumption, daily mean temperature, and rainfall of Hong Kong. Through the proposed model, we can have a deeper understanding of fractals in general and a statistical approach to identify multi-scaling behavior under MF-DFA in particular.     

Understanding land use and cover change impacts on run‐off and sediment load at flood events on the Loess Plateau,China

The Loess Plateau has been experiencing large‐scale land use and cover changes (LUCCs) over the past 50 years. It is well known about the significant decreasing trend of annual streamflow and sediment load in the catchments in this area. However, how surface run‐off and sediment load behaved in response to LUCC at flood events remained a research question. We investigated 371 flood events from 1963 to 2011 in a typical medium‐sized catchment within the Plateau in order to understand how LUCC affected the surface run‐off generation and sediment load and their behaviours based on the analysis of return periods. The results showed that the mean annual surface run‐off and sediment load from flood events accounted for 49.6% and 91.8% of their mean annual totals. The reduction of surface run‐off and associated sediment yield in floods explained about 85.0% and 89.2% of declines in the total annual streamflow and sediment load, respectively. The occurrences of flood events and peak sediment concentrations greater than 500 kg/m³ showed a significantly downward trend, yet the counterclockwise loop events still dominated the flood event processes in the catchment. The results suggest that LUCC over the past 50 years resulted in significant changes in the water balance components and associated soil erosion and sediment transportation in the catchment. This was achieved mainly by reducing surface run‐off and sediment yield during floods with return period of less than 5 years. Run‐off–sediment load behaviour during the extreme events with greater than 10‐year return periods has not changed. Outcomes from this study are useful in understanding the eco‐hydrological processes and assisting the sustainable catchment management and land use planning on the Loess Plateau, and the methodologies are general and applicable to similar areas worldwide.