Feasibility of ley-farming system performance in a semi-arid region using spatial analysis

In order to assess feasibility of ley farming system performance in the Aq-Qala township, a semi-arid region in north of Iran, Multi-Criteria Analysis (MCA) method and Geographic Information System (GIS) techniques were integrated to evaluate the suitability of wheat, barley and annual alfalfa cultivation. The agronomic and ecological requirements of three crops were identified from available scientific literatures. In this study, environmental variables were included: 1) average, minimum and maximum temperatures, 2) precipitation, 3) slope, 4) slope aspects, 5) elevation and 6) soil characteristics such as organic matter, pH, electrical conductivity (EC), texture, nitrogen, phosphorus, potassium, calcium, iron, and zinc. Weights of these variables were extracted from analysis of Analytical Hierarchy Process (AHP) questionnaires. The suitability analysis was based on matching between land qualities/characteristics and crop requirements. It was done by the weighted overlay technique (WOT) in GIS. In order to assess the land suitability of ley farming system performance, the digital suitability layers of three crops were overlaid and integrated in GIS media by raster calculator functions, then zoning of region was done in 4 classes, including: Highly suitable, moderately suitable, marginally suitable and non-suitable. Our results indicated that 35.1% (35495.20 ha) of total areas of studied region is suitable for ley farming system. According to the generated agricultural suitability map, it was determinate that 15.2% (20681.77 ha) of the region is non-suitable for ley-farming performance, 19.5% (23245.74 ha) is marginally suitable and, 30.2% (33725.60 ha) is moderately suitable. Highly suitable, moderately suitable and marginally suitable lands were expected to have a crop yield of 80–100%, 60–80% and 40–60% of the yield under optimal conditions with practicable and economic inputs, respectively. It was found that the most areas of the southern and central parts of Aq-Qala are the highly and moderately suitable regions. The results demonstrated that the high EC, low OM and low rainfall are the key limiting factors in non-suitable areas.     

Potential geographical distribution of Actinidia spp. and its predominant indices under climate change

Kiwifruit (Actinidia ssp.) is an economically and nutritionally important fruit crop with a remarkably high vitamin C content. Shaanxi Province, China, has the world's largest production base for kiwifruit; hence, it is necessary to accurately assess the potential geographic distribution of kiwifruit in this area for planting planning and government management. To perform this analysis, we selected three categories of environmental indices (climate, soil, and topographical) for a total of 18 ecological suitability assessment indices. Based on fuzzy mathematic theory, we built 18 membership functions to show the quantitative relationship between kiwifruit yield and these 18 assessment indices. Furthermore, an assessment model of kiwifruit suitability for cultivation was constructed using a combination of the weighted average method and GIS spatial analysis of the present land-use map of Shaanxi. The results show that 5860.1 km² (14.0%) of arable land and orchard can be demarcated as highly suitable for kiwifruit cultivation, 7868.9 km² (18.7%) suitable for rapeseed cultivation; 11,392.1 km² (27.1%) marginally suitable for rapeseed cultivation; and 16,892.5 km² (40.2%) as unsuitable for kiwifruit cultivation in this province. We provide a useful assessment system for ecological zoning of kiwifruit suitability and identify the highly suitable planting area of kiwifruit in Shaanxi Province. south Shannan and south Guanzhong. These results provide a reference tool for distribution rationalization and resource optimization of kiwifruit-planting areas.     

Land suitability for energy crops under scenarios of climate change and land‐use

Bioenergy is expected to play a critical role in climate change mitigation. Most integrated assessment models assume an expansion of agricultural land for cultivation of energy crops. This study examines the suitability of land for growing a range of energy crops on areas that are not required for food production, accounting for climate change impacts and conservation requirements. A global fuzzy logic model is employed to ascertain the suitable cropping areas for a number of sugar, starch and oil crops, energy grasses and short rotation tree species that could be grown specifically for energy. Two climate change scenarios are modelled (RCP2.6 and RCP8.5), along with two scenarios representing the land which cannot be used for energy crops due to forest and biodiversity conservation, food agriculture and urban areas. Results indicate that 40% of the global area currently suitable for energy crops overlaps with food land and 31% overlaps with forested or protected areas, highlighting hotspots of potential land competition risks. Approximately 18.8 million km² is suitable for energy crops, to some degree, and does not overlap with protected, forested, urban or food agricultural land. Under the climate change scenario RCP8.5, this increases to 19.6 million km² by the end of the century. Broadly, climate change is projected to decrease suitable areas in southern regions and increase them in northern regions, most notably for grass crops in Russia and China, indicating that potential production areas will shift northwards which could potentially affect domestic use and trade of biomass significantly. The majority of the land which becomes suitable is in current grasslands and is just marginally or moderately suitable. This study therefore highlights the vital importance of further studies examining the carbon and ecosystem balance of this potential land‐use change, energy crop yields in sub‐optimal soil and climatic conditions and potential impacts on livelihoods.     

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.     

Developing a land evaluation model for faba bean cultivation using geographic information system and multi-criteria analysis (A case study: Gonbad-Kavous region,Iran)

This study was carried out to assess the land suitability for rainfed faba bean (Vicia faba L.) cultivation in Gonbad-Kavous region (Golestan province, north of Iran) using geographic information system (GIS) and analytical hierarchy process (AHP), the most common methods for evaluation of land use suitability. Several parameters were considered in this study, including the annual average, minimum and maximum temperatures, annual precipitation, slope, elevation, and some soil properties such as organic matter, pH, EC, texture, phosphorus, potassium, calcium, iron, and zinc. The environmental parameters and the classification system used in the this work are inspired by the United Nations Food and Agriculture Organization (FAO) method dedicated to land suitability. In determining the weights of parameters, expert opinions were consulted and the final land suitability map was generated in five classes. As evidenced by the results, it was estimated that 23.48% of the study area (48,354.5 ha) is highly suitable for faba bean cropping, while 25.38% (52,237.37 ha) is moderately suitable and 25.03% (51,522.85 ha) is marginally suitable. In addition, our results indicated that just 26.11% of total agricultural lands are non-suitable for crop production. The currently non-suitable (49,778.80 ha) and permanently non-suitable (3997.09 ha) classes are located in the north and northwest parts of Gonbad-Kavous township. Soil salinity, low organic matter, low precipitation, high Ca content, and deficiency of P and Fe contents were found to be key limiting factors in this area.     

Predicting how adaptation to climate change could affect ecological conservation: secondary impacts of shifting agricultural suitability

Aim:  Ecosystems face numerous well‐documented threats from climate change. The well‐being of people also is threatened by climate change, most prominently by reduced food security. Human adaptation to food scarcity, including shifting agricultural zones, will create new threats for natural ecosystems. We investigated how shifts in crop suitability because of climate change may overlap currently protected areas (PAs) and priority sites for PA expansion in South Africa. Predicting the locations of suitable climate conditions for crop growth will assist conservationists and decision‐makers in planning for climate change. Location:  South Africa. Methods:  We modelled climatic suitability in 2055 for maize and wheat cultivation, two extensively planted, staple crops, and overlaid projected changes with PAs and PA expansion priorities. Results:  Changes in winter climate could make an additional 2 million ha of land suitable for wheat cultivation, while changes in summer climate could expand maize suitability by up to 3.5 million ha. Conversely, 3 million ha of lands currently suitable for wheat production are predicted to become climatically unsuitable, along with 13 million ha for maize. At least 328 of 834 (39%) PAs are projected to be affected by altered wheat or maize suitability in their buffer zones. Main conclusions:  Reduced crop suitability and food scarcity in subsistence areas may lead to the exploitation of PAs for food and fuel. However, if reduced crop suitability leads to agricultural abandonment, this may afford opportunities for ecological restoration. Expanded crop suitability in PA buffer zones could lead to additional isolation of PAs if portions of newly suitable land are converted to agriculture. These results suggest that altered crop suitability will be widespread throughout South Africa, including within and around lands identified as conservation priorities. Assessing how climate change will affect crop suitability near PAs is a first step towards proactively identifying potential conflicts between human adaptation and conservation planning.     

A distribution model for Glossina brevipalpis and Glossina austeni in Southern Mozambique,Eswatini and South Africa for enhanced area-wide integrated pest management approaches

BackgroundGlossina austeni and Glossina brevipalpis (Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique.Methodology/Principal findingsThe present study used existing entomological survey data of G. austeni and G. brevipalpis to develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species).Conclusions/SignificanceThe models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area.     

Combination of fuzzy-AHP and GIS techniques in land suitability assessment for wheat (Triticum aestivum) cultivation

Land suitability classification is a useful management practice to ensure planned and sustainable use of agricultural lands according to their potentials. The main purposes of this study were to analyze land suitability for bread wheat (Triticum aestivum) cultivation and generate a land suitability map for wheat by integrating the analytical hierarchy (AHP)-fuzzy algorithm with the Geographical Information System (GIS) in the Tozanlı sub-basin located in the upper part of Yeşilırmak Basin, Turkey. Topographic (elevation, slope, aspect) characteristics of the basin and some of physical and chemical properties of soils (texture, pH, electrical conductivity, lime, organic matter, and soil depth) were used as criteria in determining the suitability classes. Ninety-two disturbed soil samples were collected from 0 to 20 cm depth in October 2017 using random sampling method. Weighted overlay spatial analysis in GIS was used to combine different thematic layers to identify areas suitable for wheat production. The fuzzy-AHP suitability assessment model was adapted to determine the weights for topographic and soil properties. The highest specific weights were obtained for soil depth (0.232) and elevation (0.218), while the lowest weight was calculated for aspect (0.042). Highly, moderately, and marginally suitable lands for wheat cultivation cover 2.63, 9.85 and 32.59% of the study area, respectively. In addition, the results indicated that 54.92% of the total area is permanently unsuitable for wheat cultivation. The results revealed that integration of AHP-fuzzy algorithm and GIS techniques is a useful method for accurate evaluation of land suitability in planning for specific crop production and decreasing the negative environmental impacts of agricultural practices.     

Ecological niche modeling for conservation planning of an endemic snail in the verge of becoming a pest in cardamom plantations in the Western Ghats biodiversity hotspot

Conservation managers and policy makers are often confronted with a challenging dilemma of devising suitable strategies to maintain agricultural productivity while conserving endemic species that at the early stages of becoming pests of agricultural crops. Identification of environmental factors conducive to species range expansion for forecasting species distribution patterns will play a central role in devising management strategies to minimize the conflict between the agricultural productivity and biodiversity conservation. Here, we present results of a study that predicts the distribution of Indrella ampulla, a snail endemic to the Western Ghats biodiversity hotspot, which is becoming a pest in cardamom (Ellettaria cardamomum) plantations. We determined the distribution patterns and niche overlap between I. ampulla and Ellettaria cardamomum using maximum entropy (MaxEnt) niche modeling techniques under current and future (2020–2080) climatic scenarios. The results showed that climatic (precipitation of coldest quarter and isothermality) and soil (cation exchange capacity of soil [CEC]) parameters are major factors that determine the distribution of I. ampulla in Western Ghats. The model predicted cardamom cultivation areas in southern Western Ghats are highly sensitive to invasion of I. ampulla under both present and future climatic conditions. While the land area in the central Western Ghats is predicted to become unsuitable for I. ampulla and Ellettaria cardamomum in future, we found 71% of the Western Ghats land area is suitable for Ellettaria cardamomum cultivation and 45% suitable for I. ampulla, with an overlap of 35% between two species. The resulting distribution maps are invaluable for policy makers and conservation managers to design and implement management strategies minimizing the conflicts to sustain agricultural productivity while maintaining biodiversity in the region.     

印度野牛在中国的分布及其栖息地适宜性分析

印度野牛(Bos gaurus)在中国分布在云南省南部和西藏藏南地区。2016年2-3月和2016年11-12月, 我们在西双版纳州、普洱市及高黎贡山区域开展印度野牛调查, 并对藏南地区进行文献调研, 共获得47处印度野牛有效出现位点数据。目前云南地区印度野牛种群数量约180-210头, 面临着严重的生存危机; 在高黎贡山未发现印度野牛。利用印度野牛分布位点数据, 选取地形、土地覆被类型、人类足迹指数、距水源和道路距离以及气候共5类14种因子作为自变量建立MaxEnt生态位模型, 通过模拟云南和西藏印度野牛的适宜分布区, 分析各环境因子对该物种分布的影响。结果表明: 模型预测精度较高, 平均AUC (area under the curve)值为0.994。印度野牛潜在适宜栖息地可划分为高适宜、次适宜、低适宜和不适宜4个等级。高适宜栖息地主要分布在云南省西双版纳和藏南地区, 其中西双版纳部分镶嵌有次适宜和低适宜栖息地斑块, 面积为4,987 km²; 藏南部分高适宜栖息地面积为13,995 km²。次适宜栖息地主要分布于云南省南部、高黎贡山区域以及藏南高适宜栖息地区的边缘, 总面积为32,778 km²。低适宜和不适宜栖息地区连接成片, 位于云南省中部、北部地区和藏南地区北部。Jackknife检验结果显示, 季节温度变化和等温线对印度野牛潜在分布区的影响较大, 而地形因子和降水变化的影响较弱。遥感地物分类结果表明: 橡胶林等人工经济林的种植占据了西双版纳野牛的适宜栖息地, 降低了景观连接度。建议管理部门加大对天然林的保护力度, 控制橡胶林等人工林在野牛适宜栖息地的扩张, 提高景观连接度, 以促进该物种种群的恢复。     

Zoning eco-environmental vulnerability for environmental management and protection

Eco-environmental vulnerability assessment is crucial for environmental and resource management. However, evaluation of eco-environmental vulnerability over large areas is a difficult and complex process because it is affected by many variables including hydro-meteorology, topography, land resources, and human activities. The Thua Thien – Hue Province and its largest river system, the Perfume River, are vital to the social-economic development of the north central coastal region of Vietnam, but there is no zoning system for environmental protection in this region. An assessment framework is proposed to evaluate the vulnerable eco-environment in association with 16 variables with 6 of them constructed from Landsat 8 satellite image products. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands where social-economic activities have been developing rapidly. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. The proposed integrated method of remote sensing (RS), GIS, and AHP to evaluate the eco-environmental vulnerability is useful for environmental protection and proper planning for land use and construction in the future.     

Monitoring ecological status of wetlands using linked fuzzy inference system- remote sensing analysis

The present study develops an applicable model to simulate the ecological status of saltwater lakes in which depth and total dissolved solids are selected as the effective factors on aquatic habitats. First, spectral images of the operational land imager of Landsat 8 were used to simulate distribution of depth and total dissolved solids by applying two feed forward neural networks. Next, a Mamdani fuzzy inference system was used to develop habitat suitability rules of Artemia and Flamingo as the selected target species in which expert opinions were considered. Finally, habitat suitability maps of target species were generated by linking distribution maps of selected effective parameters and fuzzy inference system. Based on the results in the Urmia lake as a case study, the Nash–Sutcliffe efficiency coefficients of depth and total dissolved solids are 0.88 and 0.5 which indicates the proposed method for simulating distribution of these parameters is reliable. Average depth in the simulated date is 227 cm, while average simulated total dissolved solids is 264 g per litre. Simulation of habitat suitability maps demonstrated that average habitat suitability of Artemia is less than 30% in the most areas of the lake. Moreover, average habitat suitability of the Flamingo is less than 10% which implies the ecological status of the lake is critical and ecological restoration is necessary. The main advantage of the proposed method is to develop a framework for combining the expert opinions with remote sensing data processing to generate habitat suitability maps in lakes.     

A Presence-Only Model of Suitable Roosting Habitat for the Endangered Indiana Bat in the Southern Appalachians

We know little about how forest bats, which are cryptic and mobile, use roosts on a landscape scale. For widely distributed species like the endangered Indiana bat Myotis sodalis, identifying landscape-scale roost habitat associations will be important for managing the species in different regions where it occurs. For example, in the southern Appalachian Mountains, USA, M. sodalis roosts are scattered across a heavily forested landscape, which makes protecting individual roosts impractical during large-scale management activities. We created a predictive spatial model of summer roosting habitat to identify important predictors using the presence-only modeling program MaxEnt and an information theoretic approach for model comparison. Two of 26 candidate models together accounted for >0.93 of AICc weights. Elevation and forest type were top predictors of presence; aspect north/south and distance-to-ridge were also important. The final average best model indicated that 5% of the study area was suitable habitat and 0.5% was optimal. This model matched our field observations that, in the southern Appalachian Mountains, optimal roosting habitat for M. sodalis is near the ridge top in south-facing mixed pine-hardwood forests at elevations from 260–575 m. Our findings, coupled with data from other studies, suggest M. sodalis is flexible in roost habitat selection across different ecoregions with varying topography and land use patterns. We caution that, while mature pine-hardwood forests are important now, specific areas of suitable and optimal habitat will change over time. Combining the information theoretic approach with presence-only models makes it possible to develop landscape-scale habitat suitability maps for forest bats.     

Global Agricultural Land Resources – A High Resolution Suitability Evaluation and Its Perspectives until 2100 under Climate Change Conditions

Changing natural conditions determine the land''s suitability for agriculture. The growing demand for food, feed, fiber and bioenergy increases pressure on land and causes trade-offs between different uses of land and ecosystem services. Accordingly, an inventory is required on the changing potentially suitable areas for agriculture under changing climate conditions. We applied a fuzzy logic approach to compute global agricultural suitability to grow the 16 most important food and energy crops according to the climatic, soil and topographic conditions at a spatial resolution of 30 arc seconds. We present our results for current climate conditions (1981–2010), considering today''s irrigated areas and separately investigate the suitability of densely forested as well as protected areas, in order to investigate their potentials for agriculture. The impact of climate change under SRES A1B conditions, as simulated by the global climate model ECHAM5, on agricultural suitability is shown by comparing the time-period 2071–2100 with 1981–2010. Our results show that climate change will expand suitable cropland by additionally 5.6 million km², particularly in the Northern high latitudes (mainly in Canada, China and Russia). Most sensitive regions with decreasing suitability are found in the Global South, mainly in tropical regions, where also the suitability for multiple cropping decreases.     

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum‐suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 10³ km², and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 10³ km² and 60.21 × 10³ km² in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.     

Effects of climate change on economic feasibility of future date palm production: An integrated assessment in Iran

This study set out to build a model identifying areas where a positive Net Present Value (NPV) could be obtained from date palm (Phoenix dactylifera) using CLIMEX and six parameters including (a) suitable soil taxonomy and physicochemical soil properties, (b) slopes of less than 10°, (c) land uses suitable for date palm cultivation, (d) availability of roads, (e) availability of water, and (f) low risk of the lethal disease caused by Fusarium oxysporum f. spp. in the years 2030, 2050, 2070, and 2100 in Iran. Here, we utilized the A2 scenario and two global climate models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). Economic feasibility was estimated based on the assumption that the decision to plant date palms by landholders is motivated by a desire to maximize their return to land. Our results indicate that only 5450 km² of southern Iran will be highly profitable for cultivation of date palm, with NPV > 10,000, while profitable (with NPV between 4200 and 10,000) and moderately profitable (with NPV between 0 and 4200) areas would cover only 500 and 50 km², respectively, in future. A comparison of mean outputs from the two chosen GCMs and those of the economic and CLIMEX output combination indicates that only about 0.01% of areas from both GCMs will be highly economically viable for cultivation of date palm. In this study we ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication.     

Development of a protocol to identify land function based on multifunctionality and suitability analysis: A case study of the Nanyuntai Forest Farm,China

Accurately identifying regional land functions is important for balancing and coordinating multiple ecosystem services. Identification of land functions should be guided by the ecological suitability analysis framework, highlighting the primary ecological function and considering the temporal and spatial trends of land functions to resolve the contradictions among various needs of land ecology, production, and life. Taking Nanyuntai Forest Farm in Lianyungang City, Jiangsu Province, as a case study, we used the Analytical Hierarchical Process to construct a systematic and complete land multi-function evaluation and spatial suitability evaluation system, and used the ArcGIS spatial analysis technology to analyze its land function changes from 2011 to 2021. Finally, the results of multifunctionality and suitability analysis were integrated to identify the land's ecological, production, and living functions by constructing the algorithm using Python. Our results showed that the proportions of ecological, production, and living functions of the land in the study area were 56.82, 34.03, and 9.15%, respectively. This study highlighted that the results of land function identification based on comprehensive land-change-trend and spatial suitability analyses were more precise and coordinated. This comprehensive evaluation is a valuable and practical method for decision-makers and land managers to create land use maps and determine high-priority areas that require conservation measures for sustainable management. Moreover, this approach can be practically applied to other planning units.     

Ecological suitability evaluation for mountainous area development based on conceptual model of landscape structure,function, and dynamics

Minimizing the ecological impact of land development is a fundamental principle of sustainable development. Ecological suitability assessment is the key to realizing sustainability and is also significant for optimizing spatial patterns of territorial development. Especially in mountainous areas where the ecosystem is both vulnerable and important, quantitative evaluation of ecological suitability for land development is particularly important and urgent given current development strategy of urban construction in mountainous areas in China. Taking Dali Bai Autonomous Prefecture, a representative urban construction zone in a mountainous area in Yunnan Province, China, as a study area, and based on the fundamental theory of structural and functional dynamics from landscape ecology, this study has explored the integrated ecological resistance (IER) conceptual model and constructed an index system with aspects of ecological elements, ecological importance, and ecological resilience. The results showed that: (1) the ecological suitability level was higher in the north than in the south and higher in the east than in the west, as well as higher in the Bazi region than in mountainous areas. Dali City, Binchuan County, and Xiangyun County had large ecological suitable zones for development and construction. Foci of ecological resistance having strong ecological constraints were mainly concentrated in Heqing County and in various other places; (2) by combining the integrated ecological resistance and arable land distributions, the study area was zoned into five regions: prior development zone, moderate development zone, potential development zone, restricted development zone, and forbidden development zone. Moderate, potential, and restricted development zones occupied most of the area, accounting for 28.89%, 24.69%, and 21.40%, respectively, whereas prior development zones accounted for only 8.91%; (3) based on the areal proportions of ecological suitability zoning, the 12 counties of Dali Prefecture can be grouped into three categories: prior areas for conservation, comprehensive development areas, and prior areas for development. Xiangyun County and Binchuan County should be regarded as key areas of Dali Prefecture for urban construction in mountainous areas. This research has explored an ecological suitability evaluation system from the perspective of landscape ecology and made fully understanding of ecological suitability factors in the study area, which provided a good reference to ecological suitability evaluation for mountainous area development in the worldwide.     

Factors restricting the range expansion of the invasive green anole Anolis carolinensis on Okinawa Island,Japan

The green anole Anolis carolinensis invaded the Ogasawara Islands in Japan, drove various native species to extinction, and its distribution expanded 14 years after initial establishment. A. carolinensis invaded Okinawa Island, but it has not expanded its distribution in more than 25 years, although its density is extremely high in the southern region. To determine whether A. carolinensis has the potential to expand its distribution on Okinawa Island, we performed phylogenetic analysis of mitochondrial ND2 DNA sequences to study the origin of A. carolinensis that invaded Okinawa Island. We further used a species distribution model (MaxEnt) based on the distribution of native populations in North America to identify ecologically suitable areas on Okinawa Island. Nucleotide sequence analysis shows that the invader A. carolinensis originated in the western part of the Gulf Coast and inland areas of the United States and that a portion of the anoles on Okinawa was not introduced via the Ogasawara Islands. The MaxEnt predictions indicate that most areas in Okinawa Island are suitable for A. carolinensis. Therefore, A. carolinensis may have the potential to expand its distribution in Okinawa Island. The predictions indicate that habitat suitability is high in areas of high annual mean temperature and urbanized areas. The values of precipitation in summer in the northern region of Okinawa Island were higher compared with those of North America, which reduced the habitat suitability in Okinawa Island. Adaptation to low temperatures, an increase in the mean temperature through global warming, and an increase in open environments through land development will likely expand the distribution of A. carolinensis in Okinawa Island. Therefore, we must continue to monitor the introduced populations and be alert to the possibility that city planning that increases open environments may cause their range to expand.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.