Effects of land use and physicochemical water quality on grass shrimp, Palaemonetes pugio, and its parasitic isopod, Probopyrus pandalicola, in South Carolina, USA tidal creeks

Grass shrimp, Palaemonetes pugio, are a common inhabitant of US East and Gulf coast salt marshes and are a food source for recreationally and economically important fish and crustacean species. Due to the relationship of grass shrimp with their ecosystem, any significant changes in grass shrimp population may have the potential to affect the estuarine system. Land use is a crucial concern in coastal areas where increasing development impacts the surrounding estuaries and salt marshes and has made grass shrimp population studies a logical choice to investigate urbanization effects. Any impact on tidal creeks will be an impact on grass shrimp populations and their associated micro-environment whether predator, prey or parasitic symbiont. Anthropogenic stressors introduced into the grass shrimp ecosystem may even change the intensity of infections from parasitic symbionts. An ectoparasite found on P. pugio is the bopyrid isopod Probopyrus pandalicola. Little is known about factors that may affect the occurrence of this isopod in grass shrimp populations. The goal was to analyze the prevalence of P. pandalicola in grass shrimp in relation to land use classifications, water quality parameters, and grass shrimp population metrics. Eight tidal creeks in coastal South Carolina were sampled monthly over a three year period. The occurrence of P. pandalicola ranged from 1.2% to 5.7%. Analysis indicated that greater percent water and marsh coverage resulted in a higher incidence of bopyrid occurrence. Analysis also indicated that higher bopyrid incidence occurred in creeks with higher salinity, temperature, and pH but lower dissolved oxygen. The land use characteristics found to limit bopyrid incidence were limiting to grass shrimp (definitive host) populations and probably copepod (intermediate host) populations as well.

Quantitative analysis of land mammal zoogeographical regions in China and adjacent regions

Quantitative analysis of land mammal zoogeographical regions in China and adjacent regions. Zoological Studies 43(1): 142-160. In this paper, our aim was to determine, by means of quantitative analysis, the distribution patterns of the land mammals in China and, adjacent regions using physiographical regions as operative geographical units (OGUs). Based, on the pre-sence or absence of 11 orders, 42 families, 197 genera, and 577 species of land mammals in their zoogeographical regions, which were used as OGUs, we studied the biotic boundary between the Oriental Region (OR) and the Palaearctic Region (PR), as well as subregion boundaries. The boundary's statistical significance was tested by G-test as described by McCoy et al. A significantly strong biotic boundary was found to separate the PR from the OR, and there is a weak biotic boundary in the PR, which divides it into 2 subregions. We concluded that the biotic boundary which separates the PR and OR is a strong boundary. We suggest that the Qinghai-Xizang Plateau should be regarded as a subregion of the PR, which can embody its characteristics of high elevations and a frigid climatic, which is called the Qing-Zang subregion of the PR (QZSP).

STUDIES ON THE PURIFICATION AND RECLAMATION OF WASTE-WATER FROM A MEDIUM-SIZED CITY BY AN INTEGRATED BIOLOGICAL POND SYSTEM

The feasibility of an inexpensive wastewater treatment system is evaluated in this study. An integrated biological pond system was operated for more than 3 years to purify the wastewater from a medium-sized city, Central China. The experiment was conducted in 3 phases with different treatment combinations for testing their purification efficiencies. The pond system was divided into 3 functional regions: influent purification, effluent upgrading and multi-utilization. These regions were further divided into several zones and subzones. Various kinds of aquatic organisms, including macrophytes, algae, microorganisms and zooplankton, were effectively cooperating in the wastewater treatment in this system. The system attained high reductions of BOD5, COD, TSS, TN, TP and other pollutants. The purification efficiencies of this system were higher than those of most traditional oxidation ponds or ordinary macrophyte ponds. The mutagenic effect and numbers of bacteria and viruses declined significantly during the process of purification. After the wastewater flowed through the upgrading zone, the concentrations of pollutants and algae evidently decreased. Plant harvesting did not yield dramatic effects on reductions of the main pollutants, though it did significantly affect the biomass productivity of the macrophytes. The effluent from this system could be utilized in irrigation and aquaculture. Some aquatic products were harvested from this system and some biomass was utilized for food, fertilizer, fodder and some other uses. The wastewater was reclaimed for various purposes.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

A methodology of characterizing status and trend of land changes in oases: A case study of Sangong River watershed, Xinjiang, China

National Natural Science Foundation of China [40471134]; program of Lights of the West China by the Chinese Academy of Science

Assessing the consequence of land use change on agricultural productivity in China

China's cultivated land has been undergoing dramatic changes along with its rapidly growing economy and population. The impacts of land use transformation on food production at the national scale, however, have been poorly understood due to the lack of detailed spatially explicit agricultural productivity information on cropland change and crop productivity. This study evaluates the effect of the cropland transformation on agricultural productivity by combining the land use data of China for the period of 1990-2000 from TM images and a satellite-based NPP (net primary production) model driven with NOAH/AVHRR data. The cropland area of China has a net increase of 2.79 Mha in the study period, which causes a slightly increased agricultural productivity (6.96 Mt C) at the national level. Although the newly cultivated lands compensated for the loss from urban expansion, but the contribution to production is insignificant because of the low productivity. The decrease in crop production resulting from urban expansion is about twice of that from abandonment of arable lands to forests and grasslands. The productivity of arable lands occupied by urban expansion was 80% higher than that of the newly cultivated lands in the regions with unfavorable natural conditions. Significance of cropland transformation impacts is spatially diverse with the differences in land use change intensity and land productivity across China. The increase in arable land area and yet decline in land quality may reduce the production potential and sustainability of China's agro-ecosystems. (C) 2008 Elsevier B.V. All rights reserved.