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Wang X, Li Z, Zhang L, Wang Y, Liu Y, Ma Y. The optimized Maxent model reveals the pattern of distribution and changes in the suitable cultivation areas for Reaumuria songarica being driven by climate change. Ecol Evol 2024; 14:e70015. [PMID: 39026959 PMCID: PMC11255383 DOI: 10.1002/ece3.70015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/16/2024] [Accepted: 07/03/2024] [Indexed: 07/20/2024] Open
Abstract
Reaumuria songarica, a drought-resistant shrub, is widely distributed and plays a crucial role in the northern deserts of China. It is a key species for desert rehabilitation and afforestation efforts. Using the Maxent model to predict suitable planting areas for R. songarica is an important strategy for combating desertification. With 184 occurrence points of R. songarica and 13 environmental variables, the optimized Maxent model has identified the main limiting factors for its distribution. Distribution patterns and variation trends of R. songarica were projected for current and future climates (2030s, 2050s, 2070s, and 2090s) and different scenarios (ssp_126, ssp_370, and ssp_585). Results show that setting parameters to RM (regulation multiplier) = 4 and FC (feature combination) = LQHPT yields a model with good accuracy and high reliability. Currently, R. songarica is primarily suitable for desert control in eight provinces and autonomous regions, including Inner Mongolia, Xinjiang, Qinghai, and Ningxia. The total suitable planting area is 148.80 × 104 km2, representing 15.45% of China's land area. Precipitation (Precipitation of the wettest month, Precipitation of the warmest quarter, and Annual precipitation) and Ultraviolet-B seasonality are the primary environmental factors limiting the growth and distribution of R. songarica. Mean temperature of the warmest quarter is the primary factor driving changes in the distribution of suitable areas for R. songarica under future climate scenarios. In future climate scenarios, the suitable planting area of R. songarica will shrink, and the distribution center will shift towards higher latitude, potentially indicate further desertification. The area of highly suitable habitat has increased, while moderately and less suitable habitat areas have decreased. Increased precipitation within R. songarica's water tolerance range is favorable for its growth and reproduction. With changes in the suitable cultivation area for R. songarica, priority should be given to exploring and utilizing its germplasm resources. Introduction and cultivation can be conducted in expanding regions, while scientifically effective measures should be implemented to protect germplasm resources in contracting regions. The findings of this study provide a theoretical basis for addressing desertification resulting from climate change and offer practical insights for the development, utilization, introduction, and cultivation of R. songarica germplasm resources.
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Affiliation(s)
- Xinyou Wang
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
| | - Zhengsheng Li
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
| | - Lijun Zhang
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
| | - Yanlong Wang
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
| | - Ying Liu
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
| | - Yushou Ma
- Qinghai Academy of Animal and Veterinary Sciences, Qinghai Provincial Key Laboratory of Adaptive Management on Alpine Grassland, Key Laboratory of Superior Forage Germplasm in the Qinghai‐Tibetan Plateau, Qinghai UniversityXiningQinghaiChina
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Pica A, Vela D, Magrini S. Forest Orchids under Future Climate Scenarios: Habitat Suitability Modelling to Inform Conservation Strategies. PLANTS (BASEL, SWITZERLAND) 2024; 13:1810. [PMID: 38999650 PMCID: PMC11243989 DOI: 10.3390/plants13131810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/14/2024]
Abstract
Orchidaceae is one of the largest and most diverse families of flowering plants in the world but also one of the most threatened. Climate change is a global driver of plant distribution and may be the cause of their disappearance in some regions. Forest orchids are associated with specific biotic and abiotic environmental factors, that influence their local presence/absence. Changes in these conditions can lead to significant differences in species distribution. We studied three forest orchids belonging to different genera (Cephalanthera, Epipactis and Limodorum) for their potential current and future distribution in a protected area (PA) of the Northern Apennines. A Habitat Suitability Model was constructed for each species based on presence-only data and the Maximum Entropy algorithm (MaxEnt) was used for the modelling. Climatic, edaphic, topographic, anthropogenic and land cover variables were used as environmental predictors and processed in the model. The aim is to identify the environmental factors that most influence the current species distribution and the areas that are likely to contain habitats suitable for providing refuge for forest orchids and ensuring their survival under future scenarios. This will allow PA authorities to decide whether to invest more resources in conserving areas that are potential refuges for threatened species.
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Affiliation(s)
- Antonio Pica
- Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy
| | - Daniele Vela
- Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy
| | - Sara Magrini
- Department of Ecological and Biological Sciences, University of Tuscia, 01100 Viterbo, Italy
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Nan Q, Li C, Li X, Zheng D, Li Z, Zhao L. Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change. PLANTS (BASEL, SWITZERLAND) 2024; 13:1082. [PMID: 38674491 PMCID: PMC11054219 DOI: 10.3390/plants13081082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 03/31/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024]
Abstract
Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana's geographical distribution, including the driest month's precipitation, the coldest month's minimum temperature, the wettest month's precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.
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Affiliation(s)
- Qianru Nan
- School of Resources and Environmental Science, Hubei University, Wuhan 430062, China; (Q.N.); (X.L.); (D.Z.); (Z.L.)
| | - Chunhui Li
- Agricultural Development Service Centre of Enshi Tujia and Miao Autonomous Prefecture, Enshi 44500, China
| | - Xinghao Li
- School of Resources and Environmental Science, Hubei University, Wuhan 430062, China; (Q.N.); (X.L.); (D.Z.); (Z.L.)
| | - Danni Zheng
- School of Resources and Environmental Science, Hubei University, Wuhan 430062, China; (Q.N.); (X.L.); (D.Z.); (Z.L.)
| | - Zhaohua Li
- School of Resources and Environmental Science, Hubei University, Wuhan 430062, China; (Q.N.); (X.L.); (D.Z.); (Z.L.)
| | - Liya Zhao
- School of Resources and Environmental Science, Hubei University, Wuhan 430062, China; (Q.N.); (X.L.); (D.Z.); (Z.L.)
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Li J, Deng C, Duan G, Wang Z, Zhang Y, Fan G. Potentially suitable habitats of Daodi goji berry in China under climate change. FRONTIERS IN PLANT SCIENCE 2024; 14:1279019. [PMID: 38264027 PMCID: PMC10803630 DOI: 10.3389/fpls.2023.1279019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 12/18/2023] [Indexed: 01/25/2024]
Abstract
Introduction Goji berry (Lycium barbarum L.) is a famous edible and medicinal herb worldwide with considerable consumption. The recent cultivation of goji berries in the Daodi region was seriously reduced due to increased production costs and the influence of policy on preventing nongrain use of arable land in China. Consequently, production of Daodi goji berry was insufficient to meet market demands for high-quality medicinal materials. Searching for regions similar to the Daodi region was necessary. Methods The MaxEnt model was used to predicted the current and future potential regions suitable for goji berry in China based on the environmental characteristics of the Daodi region (including Zhongning County of Zhongwei prefecture-level city, and its surroundings), and the ArcGIS software was used to analyze the changes in its suitable region. Results The results showed that when the parameters were FC = LQHP and RM = 2.1, the MaxEnt model was optimal, and the AUC and TSS values were greater than 0.90. The mean temperature and precipitation of the coldest quarter were the most critical variables shaping the distribution of Daodi goji berries. Under current climate conditions, the suitable habitats of the Daodi goji berry were 45,973.88 km2, accounting for 0.48% of China's land area, which were concentrated in the central and western Ningxia Province (22,589.42 km2), and the central region of Gansu Province (18,787.07 km2) bordering western Ningxia. Under future climate scenarios, the suitable area was higher than that under current climate conditions and reached the maximum under RCP 6.0 (91,256.42 km2) in the 2050s and RCP 8.5 (82,459.17 km2) in the 2070s. The expansion regions were mainly distributed in the northeast of the current suitable ranges, and the distributional centroids were mainly shifted to the northeast. The moderately and highly suitable overlapping habitats were mainly distributed in Baiyin (7,241.75 km2), Zhongwei (6,757.81 km2), and Wuzhong (5, 236.87 km2) prefecture-level cities. Discussion In this stduy, MaxEnt and ArcGIS were applied to predict and analyze the suitable habitats of Daodi goji berry in China under climate change. Our results indicate that climate warming is conducive to cultivating Daodi goji berry and will not cause a shift in the Daodi region. The goji berry produced in Baiyin could be used to satisfy the demand for high-quality medicinal materials. This study addresses the insufficient supply and guides the cultivation of Daodi goji berry.
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Affiliation(s)
- Jianling Li
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China
- Qinghai Plateau Tree Genetics and Breeding Laboratory, Qinghai University, Xining, China
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai University, Xining, China
| | - Changrong Deng
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China
- Qinghai Plateau Tree Genetics and Breeding Laboratory, Qinghai University, Xining, China
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai University, Xining, China
| | - Guozhen Duan
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China
- Qinghai Plateau Tree Genetics and Breeding Laboratory, Qinghai University, Xining, China
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai University, Xining, China
| | - Zhanlin Wang
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China
- Qinghai Plateau Tree Genetics and Breeding Laboratory, Qinghai University, Xining, China
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai University, Xining, China
| | - Yede Zhang
- Qinghai Kunlun Goji Industry Technology Innovation Research Co., Ltd., Delingha, China
| | - Guanghui Fan
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China
- Qinghai Plateau Tree Genetics and Breeding Laboratory, Qinghai University, Xining, China
- State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, China
- Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources, Qinghai University, Xining, China
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