Yuan Chi

Impact factors identification of spatial heterogeneity of herbaceous plant diversity on five southern islands of Miaodao Archipelago in North China

Herbaceous plants are widely distributed on islands and where they exhibit spatial heterogeneity. Accurately identifying the impact factors that drive spatial heterogeneity can reveal typical island biodiversity patterns. Five southern islands in the Miaodao Archipelago, North China were studied herein. The spatial distribution of herbaceous plant diversity on these islands was analyzed, and the impact factors and their degree of impact on spatial heterogeneity were identified using CCA ordination and ANOVA. The results reveal 114 herbaceous plant species, belonging to 94 genera from 34 families in the 50 plots sampled. The total species numbers on different islands were significantly positively correlated with island area, and the average α diversity was correlated with human activities, while the β diversity among islands was more affected by island area than mutual distances. Spatial heterogeneity within islands indicated that the diversities were generally high in areas with higher altitude, slope, total nitrogen, total carbon, and canopy density, and lower moisture content, pH, total phosphorus, total potassium, and aspect. Among the environmental factors, pH, canopy density, total K, total P, moisture content, altitude, and slope had significant gross effects, but only canopy density exhibited a significant net effect. Terrain affected diversity by restricting plantation, plantation in turn influenced soil properties and the two together affected diversity. Therefore, plantation was ultimately the fundamental driving factor for spatial heterogeneity in herbaceous plant diversity on the five islands.

Simulating spatial distribution of coastal soil carbon content using a comprehensive land surface factor system based on remote sensing

Surface soil carbon content (SCC) in coastal area is affected by complex factors, and revealing the SCC spatial distribution is considerably significant for judging the quantity of stored carbon and identifying the driving factors of SCC variation. A comprehensive land surface factor system (CLSFS) was established; it utilized the ecological significances of remote sensing data and included four-class factors, namely, spectrum information, ecological indices, spatial location, and land cover. Different simulation algorithms, including single-factor regression (SFR), multiple-factor regression (MFR), partial least squares regression (PLSR), and back propagation neural network (BPNN), were adopted to conduct the surface (0-30cm) SCC mapping in the Yellow River Delta in China, and a 10-fold cross validation approach was used to validate the uncertainty and accuracy of the algorithms. The results indicated that the mean simulated standard deviations were all <0.5g/kg and thus showed a low uncertainty; the mean root mean squared errors based on the simulated and measured SCC were 3.88g/kg (SFR), 3.85g/kg (PLSR), 3.67g/kg (MFR), and 2.78g/kg (BPNN) with the BPNN exhibiting a high accuracy compared to similar studies. The mean SCC was 17.40g/kg in the Yellow River Delta with distinct spatial heterogeneity; in general, the SCC in the alongshore regions, except for estuaries, was low, and that in the west of the study area was high. The mean SCCs in farmland (18.31g/kg) and wetland vegetation (17.98g/kg) were higher than those in water area (16.07g/kg), saltern (15.61g/kg), and bare land (14.71g/kg). Land-sea interaction and human activity jointly affected the SCC spatial distribution. The CLSFS was proven to have good applicability, and can be widely used in simulating the SCC spatial distribution in coastal areas.

Archipelago bird habitat suitability evaluation based on a model of form-structure-function-disturbance

Archipelagos are always the key nodes of bird migration routes, but they exhibit ecological vulnerability and heterogeneity due to their unique natural conditions and various human disturbances. An evaluation of archipelago bird habitat suitability that focuses on archipelago features is essential for island ecosystem conservation under human disturbances and for optimisation of bird migration routes. A form-structure-function-disturbance (FSFD) model for archipelago bird habitat suitability was established, and the spatial distributions of habitat suitability were analysed at the island and grid scales on Miaodao Archipelago, which are important islands in North China. Results indicated that form values were high in islands with large areas and centre position; structure values were high in areas with simple terrain condition and landscape pattern; function values were lower in traffic, building and bare lands than those in plantation and grassland; and disturbance values were closely related to human activities, which were lower in inhabited islands than those in uninhabited islands, and in traffic and building lands than those in other areas. The archipelago bird habitat suitability showed evident spatial heterogeneity. At the island scale, five islands were in status of good suitability, and 27 islands were in status of ordinary suitability; the different suitability levels at the grid scale were ordinary suitability, good suitability, poor suitability and best suitability in the descending order of areas. FSFD were determined by natural and anthropogenic factors, and human disturbance was the major factor that influences the spatial distribution of archipelago bird habitat suitability.

Spatiotemporal heterogeneity of phytoplankton diversity and its relation to water environmental factors in the southern waters of Miaodao Archipelago, China

To study the water quality influenced by the anthropogenic activities and its impact on the phytoplankton diversity in the surface waters of Miaodao Archipelago, the spatiotemporal variations in phytoplankton communities and the environmental properties of the surface waters surrounding the Five Southern Islands of Miaodao Archipelago were investigated, based on seasonal field survey conducted from November 2012 to August 2013. During the survey, a total of 109 phytoplankton species from 3 groups were identified in the southern waters of Miaodao Archipelago, of which 77 were diatoms, 29 were dinoflagellates, and 3 were chrysophytes. Species number was higher in winter (73), moderate in autumn (70), but lower in summer (31) and spring (27). The species richness index in autumn (5.92) and winter (4.28) was higher than that in summer (2.83) and spring (1.41). The Shannon-Wiener diversity index was high in autumn (2.82), followed by winter (1.99) and summer (1.92), and low in spring (0.07). The species evenness index in autumn (0.46) and summer (0.39) was higher than that in winter (0.32) and spring (0.02). On the basis of principal component analysis (PCA) and redundancy analysis (RDA), we found that dissolved inorganic nitrogen (DIN) and chemical oxygen demand (COD) in spring, COD in summer, pH in autumn, and salinity and oil pollutant in winter, respectively, showed the strongest association with the distribution of phytoplankton diversity. The spatial heterogeneity of the southern waters of Miaodao Archipelago was quite obvious, and three zones, i.e., northeastern, southwestern and inter-island water area, were identified by cluster analysis (CA) based on key environmental variables.

Evaluation on island ecological vulnerability and its spatial heterogeneity

The evaluation on island ecological vulnerability (IEV) can help reveal the comprehensive characteristics of the island ecosystem and provide reference for controlling human activities on islands. An IEV evaluation model which reflects the land-sea dual features, natural and anthropogenic attributes, and spatial heterogeneity of the island ecosystem was established, and the southern islands of Miaodao Archipelago in North China were taken as the study area. The IEV, its spatial heterogeneity, and its sensitivities to the evaluation elements were analyzed. Results indicated that the IEV was in status of mild vulnerability in the archipelago scale, and population pressure, ecosystem productivity, environmental quality, landscape pattern, and economic development were the sensitive elements. The IEV showed significant spatial heterogeneities both in land and surrounding waters sub-ecosystems. Construction scale control, optimization of development allocation, improvement of exploitation methods, and reasonable ecological construction are important measures to control the IEV.

Spatial heterogeneity of estuarine wetland ecosystem health influenced by complex natural and anthropogenic factors

The evaluation of estuarine wetland ecosystem health (EWEH) is vital and difficult due to complex influencing factors and their spatial heterogeneities. An EWEH evaluation model was established in this study on the basis of the typical features of estuarine wetland ecosystems with focus on spatial heterogeneity. The index system comprises external factors, internal factors, and ecological state, and covers all aspects of the natural and anthropogenic factors, with each index possessing its own spatial heterogeneity. The Yellow River Delta, a typical estuarine wetland in China, was selected as the study area to demonstrate the model. Results indicated that the present EWEH in the entire study area was in good status with distinct spatial heterogeneity. Ecosystem productivity, seawater intrusion, human interference, and Yellow River input were the most relevant indexes of EWEH. The temporal variations of EWEH fluctuated from 1987 to 2016. The decrease in the Yellow River input and the increase in human activity intensity deteriorated EWEH, whereas the alongshore embankment and nature reserve construction improved EWEH in certain parts. The influence of natural factors continuously decreased, and human activity became the main driving factor of the EWEH spatial variation. Our model was proven to possess comprehensive reflections of estuarine wetland ecological characteristics, full exhibitions of spatial heterogeneity, and high applicability; therefore, it can be widely used to evaluate EWEH in different areas.

A model to assess fundamental and realized carrying capacities of island ecosystem: A case study in the southern Miaodao Archipelago of China

Research on carrying capacity, aiming at maintaining the limited ability of the Earth’s life supporting system to sustain human development, requires a comprehensive and ecosystem-based approach to monitor and assess the localized sustainability of coupled social and ecological systems. A definition termed the ecosystem-based carrying capacity of island (EBCCI) was developed in this paper of which the indices of fundamental and realized carrying capacities of island (FCCI and RCCI) were highlighted to emphasize the inter-dependencies between social systems and ecological systems. In order to avoid the difficulties and uncertainties of direct assessment, the related assessment model was established on the basis of synthetic evaluation of inherent and external factors affecting the EBCCI. The southern Miaodao Archipelago (SMA) located in the intersection of the Bohai Sea and the Yellow Sea, China, was taken as a typical example to acquire integrated recognition of the island ecosystem and its carrying capacity so as to discuss its sustainable development. The index scores of FCCI and RCCI in the SMA were 0.818 5 and 0.712 9 out of 1.0, respectively, with acceptable uncertainties. The results showed a relatively well capacity to sustain progress and relatively well realization of the carrying capacity of island ecosystem, owing to a well capacity of ecologically regulating, general performance of both ecologically supporting and resource provisioning, and a relatively high level of social supporting system. The study implied that it was critical to optimize the inter-dependencies and to sustain the relative balance between social systems and ecological systems so as to improve the RCCI and further facilitate the sustainability of SMA. The approach proposed in this paper provides a powerful tool which is well applicative to the regional level of an oceanic island or archipelago to study the sustainable development and can be further popularized to the coastal zone.