Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, touri...Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, tourism riches, as well as ecological benefits, such as nutrient regulation and carbon sequestration. Thus, this work aimed to generate potential distribution modeling for the Brazilian forest species, to provide information that will serve as a strategy for conservation, restoration and commercial plantation of them, that is, encouraging the use of legal native species in the forest sector. Eleven tree species and 19 bioclimatic variables were selected. The software Maxent 3.3.3 was applied in the generation of the distribution models and the area under the curve of receiver operating characteristic （AUC） was used to analyze the model. The Jackknife test contributed to identify which bioclimatic variables are most important or influential in the model. The models showed AUC values ranged from 0.857 to 0.983. The species with higher AUC values were Araucaria angustifolia, Mimosa scabrella and Euterpe edulis, respectively. The maximum temperature of warmest month showed the highest influence for the most species, followed by the mean diurnal range and annual precipitation. It was observed that for some species, there were restricted areas of environmental suitability, such as Araucaria angustifolia, Ilex paraguariensis and Mimosa scabrella. The models used could trace the potential distribution areas using the environmental variables, and these models contribute significantly to sustainable forest management.展开更多
In developing countries, land productivity involves little market, where the agricultural land use is mainly determined by the food demands as well as the land suitability. The land use pattern will not ensure everywh...In developing countries, land productivity involves little market, where the agricultural land use is mainly determined by the food demands as well as the land suitability. The land use pattern will not ensure everywhere enough land for certain cropping if spatial allocation just according to land use suitability. To solve this problem, a subzone and a pre-allocation for each land use are added in spatial allocation module, and land use suitability and area optimi- zation module are incorporated to constitute a whole agricultural land use optimal allocation （ALUOA） system. The system is developed on the platform .Net 2005 using ArcGIS Engine （version 9.2） and C# language, and is tested and validated in Yili watershed of Xinjiang Region on the newly reclaimed area. In the case study, with the help of soil data obtained from 69 points sampled in the fieldwork in 2008, main river data supplied by the Department of Water Resources of Xinjiang Uygur Autonomous Region in China, and temperature data provided by Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences, land use suitability on eight common crops are evaluated one by one using linear weighted summation method in the land use suitability model. The linear pro- gramming （LP） model in area optimization model succeeds to give out land area target of each crop under three scenarios. At last, the land use targets are allotted in space both with a six subzone file and without a subzone file. The resuits show that the land use maps with a subzone not only ensure every part has enough land for every crop, but also gives a more fragmental land use pattern, with about 87.99% and 135.92% more patches than the one without, while at the expense of loss between 15.30% and 19.53% in the overall suitability at the same time.展开更多
文摘Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, tourism riches, as well as ecological benefits, such as nutrient regulation and carbon sequestration. Thus, this work aimed to generate potential distribution modeling for the Brazilian forest species, to provide information that will serve as a strategy for conservation, restoration and commercial plantation of them, that is, encouraging the use of legal native species in the forest sector. Eleven tree species and 19 bioclimatic variables were selected. The software Maxent 3.3.3 was applied in the generation of the distribution models and the area under the curve of receiver operating characteristic （AUC） was used to analyze the model. The Jackknife test contributed to identify which bioclimatic variables are most important or influential in the model. The models showed AUC values ranged from 0.857 to 0.983. The species with higher AUC values were Araucaria angustifolia, Mimosa scabrella and Euterpe edulis, respectively. The maximum temperature of warmest month showed the highest influence for the most species, followed by the mean diurnal range and annual precipitation. It was observed that for some species, there were restricted areas of environmental suitability, such as Araucaria angustifolia, Ilex paraguariensis and Mimosa scabrella. The models used could trace the potential distribution areas using the environmental variables, and these models contribute significantly to sustainable forest management.
基金Under the auspices of National Natural Science Foundation of China (No. 41001108, 41071065)Beijing Municipal Natural Science Foundation (No. 9113029)
文摘In developing countries, land productivity involves little market, where the agricultural land use is mainly determined by the food demands as well as the land suitability. The land use pattern will not ensure everywhere enough land for certain cropping if spatial allocation just according to land use suitability. To solve this problem, a subzone and a pre-allocation for each land use are added in spatial allocation module, and land use suitability and area optimi- zation module are incorporated to constitute a whole agricultural land use optimal allocation （ALUOA） system. The system is developed on the platform .Net 2005 using ArcGIS Engine （version 9.2） and C# language, and is tested and validated in Yili watershed of Xinjiang Region on the newly reclaimed area. In the case study, with the help of soil data obtained from 69 points sampled in the fieldwork in 2008, main river data supplied by the Department of Water Resources of Xinjiang Uygur Autonomous Region in China, and temperature data provided by Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences, land use suitability on eight common crops are evaluated one by one using linear weighted summation method in the land use suitability model. The linear pro- gramming （LP） model in area optimization model succeeds to give out land area target of each crop under three scenarios. At last, the land use targets are allotted in space both with a six subzone file and without a subzone file. The resuits show that the land use maps with a subzone not only ensure every part has enough land for every crop, but also gives a more fragmental land use pattern, with about 87.99% and 135.92% more patches than the one without, while at the expense of loss between 15.30% and 19.53% in the overall suitability at the same time.
