气候变化对湖南省马尾松适宜生境影响分析
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摘要
【目的】气候变化会导致树种适宜生境发生变化,从而对准确地制定长期森林经营规划方案产生影响。为了在制定长期森林经营规划中贯彻适地适树原则,需要研究气候变化对树种适宜生境分布的影响。【方法】以湖南省马尾松(Pinus massoniana)为研究对象,利用2016年湖南省连续清查森林资源档案更新数据中的马尾松空间分布数据、高程数据和气候数据,采用最大熵法(Maxent)模型,分温度变化、降水量不变,降水量变化、温度不变,降水量和温度均变化3种情景模拟马尾松在湖南省适宜生境的动态变化。【结果】①Maxent模型模拟结果中,训练精度、模拟精度的AUC(area under the ROC curve)值在AUC评估标准中属于良好(0.80～0.90)水平,可以较好地模拟马尾松适宜生境;②2016年马尾松适宜生境主要分布于湖南省中部和西北部,小部分分布于东部和南部。适宜生境、低适宜生境和不适宜生境所占面积比例分别为28.30%、40.10%、31.60%;③2016—2050年温度和降水量均有所增加,年平均温度增加2.30℃,年平均降水量增加19.9 mm。在温度升高、降水量不变,降水量升高、温度不变和温度、降水量均升高3种气候情景下,湖南省马尾松适宜生境面积比例分别变化了0.58%、0.53%和-0.65%,不适宜生境相比2016年均有所减少,分别减少了7.22%、2.00%和0.15%;④刀切法确定了最湿季均温(Bio8)、最暖季均温(Bio10)、最冷季降水量(Bio19)为影响马尾松分布的主导气候因子,其中最冷季降水量为最主要的气候因子。【结论】湖南省马尾松种植区主要分布在该省中部和西北部,当未来气候呈现温度增加、降水量不变的情景时,种植区域适当向东扩展;当未来气候呈现降水量增加、温度不变或二者均增加的情景时,种植区域适当向北扩展。
【Objective】Climate change will lead to changes in suitable habitats of tree species, which will have an impact on the scientifically making of long-term forest management plans. In order to implement the principle of matching species with suitable sites when making long-term forest management plan, we need to consider the impact of climate change on the suitable habitats of tree species. 【Method】Pinus massoniana in Hunan was chosen as the research object; distribution data of P. massoniana from the updated date in continuous forest inventory of Hunan Province in 2016 were collected to simulate dynamic changes of P. massoniana using maximum entropy(Maxent) model in three scenarios. The scenarios included temperature change while keeping the precipitation constant, precipitation change while keeping temperature constant and changing both temperature and precipitation. 【Result】① Maxent simulation results showed that the AUC(area under the ROC curve) values of training accuracy and simulation accuracy were considered good(0.80-0.90) level in the AUC evaluation criteria. It also demonstrated that the model could accurately simulate suitable habitats of P. massoniana. ②In 2016, suitable habitats of P. massoniana were mainly distribute in the central and northwestern parts of Hunan Province. Only a small part of suitable habitats were distributed in the eastern and southern parts of Hunan. The proportions of suitable habitats, low suitable habitats, and unsuitable habitats were 28.30%, 40.10%, and 31.60%, respectively.③Both temperature and precipitation were assumed to increase from 2016 to 2050. The annual average temperature will increase by 2.3℃, and the average annual precipitation would increase by 19.9 mm. In three scenarios listed above, the proportion of suitable habitats area of P. massoniana in Hunan Province were changed by 0.58%, 0.53% and-0.65%. Compared with 2016, unsuitable habitats in 2050 will decrease by 7.22%, 2.00% and 0.15%, respectively. The results of Jackknife analysis showed that the most humid season average temperature(Bio8), the warmest season average temperature(Bio10) and the most cold season precipitation(Bio19) were dominating climate factors that greatly impact suitable habitats of P. massoniana. Among these, the coldest seasonal precipitation was the most important factor.【Conclusion】P. massoniana planting area is mainly distributed in the central and northwestern parts of Hunan Province. When the future climate will increase in temperature while keeping precipitation constant, the planting area will expand to the east. When the future climate will increase in precipitation while keeping temperature constant or increase both in temperature and precipitation, the planting area will expand appropriately to the north.
【Objective】Climate change will lead to changes in suitable habitats of tree species, which will have an impact on the scientifically making of long-term forest management plans. In order to implement the principle of matching species with suitable sites when making long-term forest management plan, we need to consider the impact of climate change on the suitable habitats of tree species. 【Method】Pinus massoniana in Hunan was chosen as the research object; distribution data of P. massoniana from the updated date in continuous forest inventory of Hunan Province in 2016 were collected to simulate dynamic changes of P. massoniana using maximum entropy(Maxent) model in three scenarios. The scenarios included temperature change while keeping the precipitation constant, precipitation change while keeping temperature constant and changing both temperature and precipitation. 【Result】① Maxent simulation results showed that the AUC(area under the ROC curve) values of training accuracy and simulation accuracy were considered good(0.80-0.90) level in the AUC evaluation criteria. It also demonstrated that the model could accurately simulate suitable habitats of P. massoniana. ②In 2016, suitable habitats of P. massoniana were mainly distribute in the central and northwestern parts of Hunan Province. Only a small part of suitable habitats were distributed in the eastern and southern parts of Hunan. The proportions of suitable habitats, low suitable habitats, and unsuitable habitats were 28.30%, 40.10%, and 31.60%, respectively.③Both temperature and precipitation were assumed to increase from 2016 to 2050. The annual average temperature will increase by 2.3℃, and the average annual precipitation would increase by 19.9 mm. In three scenarios listed above, the proportion of suitable habitats area of P. massoniana in Hunan Province were changed by 0.58%, 0.53% and-0.65%. Compared with 2016, unsuitable habitats in 2050 will decrease by 7.22%, 2.00% and 0.15%, respectively. The results of Jackknife analysis showed that the most humid season average temperature(Bio8), the warmest season average temperature(Bio10) and the most cold season precipitation(Bio19) were dominating climate factors that greatly impact suitable habitats of P. massoniana. Among these, the coldest seasonal precipitation was the most important factor.【Conclusion】P. massoniana planting area is mainly distributed in the central and northwestern parts of Hunan Province. When the future climate will increase in temperature while keeping precipitation constant, the planting area will expand to the east. When the future climate will increase in precipitation while keeping temperature constant or increase both in temperature and precipitation, the planting area will expand appropriately to the north.
引文
[1] 郭彦龙,卫海燕,路春燕,等.气候变化下桃儿七潜在地理分布的预测[J].植物生态学报,2014,38(3):249-261.DOI:10.3724/SP.J.1258.2014.00022.GUO Y L,WEI H Y,LU C Y,et al.Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change[J].Chinese Journal of Plant Ecology,2014,38(3):249-261.
[2] STOCKWELL D R B.Improving ecological niche models by data mining large environmental datasets for surrogate models[J].Ecological Modelling,2006,192(1/2):188-196.DOI:10.1016/j.ecolmodel.2005.05.029.
[3] SANTANA F S,DE SIQUEIRA M F,SARAIVA A M,et al.A reference business process for ecological niche modelling[J].Ecological Informatics,2008,3(1):75-86.DOI:10.1016/j.ecoinf.2007.12.003.
[4] 冯益明,刘洪霞.基于Maxent与GIS的锈色棕榈象在中国潜在的适生性分析[J].华中农业大学学报,2010,29(5):552-556.FENG Y M,LIU H X.Potential suitability analysis of Rhychophorus ferrugineus (Olvier) in China based on max Ent and GIS[J].Journal of Huazhong Agricultural University,2010,29(5):552-556.
[5] 孙敬松,周广胜.利用最大熵法(MaxEnt)模拟中国冬小麦分布区的年代际动态变化[J].中国农业气象,2012,33(4):481-487.DOI:10.3969/j.issn.1000-6362.2012.04.002.SUN J S,ZHOU G S.Inter-decadal variability of winter wheat planting zone in China during 1961 to 2010 simulated by maximum entropy (MaxEnt)[J].Chinese Journal of Agrometeorology,2012,33(4):481-487.
[6] 李丽鹤,刘会玉,林振山,等.基于MAXENT和ZONATION的加拿大一枝黄花入侵重点监控区确定[J].生态学报,2017,37(9):3124-3132.DOI:10.5846/stxb201601260182.LI L H,LIU H Y,LIN Z S,et al.Identifying priority areas for monitoring the invasion of Solidago canadensis based on MAXENT and ZONATION[J].Acta Ecologica Sinica,2017,37(9):3124-3132.
[7] 雷军成,王莎,王军围,等.未来气候变化对我国特有濒危动物黑麂适宜生境的潜在影响[J].生物多样性,2016,24(12):1390-1399.DOI:10.17520/biods.2016152.LEI J C,WANG S,WANG J W,et al.Potential effects of future climate change on suitable habitat of Muntiacus crinifrons,an endangered and endemic species in China[J].Biodiversity Science,2016,24(12):1390-1399.
[8] 张东方,张琴,郭杰,等.基于MaxEnt模型的当归全球生态适宜区和生态特征研究[J].生态学报,2017,37(15):5111-5120.DOI:10.5846/stxb201605030837.ZHANG D F,ZHANG Q,GUO J,et al.Research on the global ecological suitability and characteristics of regions with Angelica sinensis based on the MaxEnt model[J].Acta Ecologica Sinica,2017,37(15):5111-5120.
[9] 唐继洪,程云霞,罗礼智,等.基于Maxent模型的不同气候变化情景下我国草地螟越冬区预测[J].生态学报,2017,37(14):4852-4863.DOI:10.5846/stxb201604040608.TANG J H,CHENG Y X,LUO L Z,et al.Maxent-based prediction of overwintering areas of Loxostege sticticalis in China under different climate change scenarios[J].Acta Ecologica Sinica,2017,37(14):4852-4863.
[10] 陶冀,关键,彭露萍,等.湖南省马尾松材积生长率模型研究[J].低碳世界,2016(26):280-282.DOI:10.16844/tk.2016.26.171.
[11] HIJMANS R J,CAMERON S E,PARRA J L,et al.Very high resolution interpolated climate surfaces for global land areas[J].International Journal of Climatology,2005,25(15):1965-1978.DOI:10.1002/joc.1276.
[12] 石彦军,任余龙,王式功,等.BCC_CSM气候模式对中国区域气候变化模拟能力的检验 [J].高原气象,2012,31(5):1257-1267.SHI Y J,REN Y L,WANG S G,et al.Verification of simulation ability of BCC_CSM climate model in regional climate change in China[J].Plateau Meteorology,2012,31(5):1257-1267.
[13] PHILLIPS S J,ANDERSON R P,SCHAPIRE R E.Maximum entropy modeling of species geographic distributions[J].Ecological Modelling,2006,190(3/4):231-259.DOI:10.1016/j.ecolmodel.2005.03.026.
[14] MORENO R,ZAMORA R,MOLINA J R,et al.Predictive modeling of microhabitats for endemic birds in South Chilean temperate forests using Maximum entropy (MaxEnt)[J].Ecological Informatics,2011,6(6):364-370.DOI:10.1016/j.ecoinf.2011.07.003.
[15] 王运生,谢丙炎,万方浩,等.ROC曲线分析在评价入侵物种分布模型中的应用[J].生物多样性,2007,15(4):365-372.DOI:10.3321/j.issn:1005-0094.2007.04.005.WANG Y S,XIE B Y,WAN F H,et al.Application of ROC curve analysis in evaluating the performance of alien species’ potential distribution models[J].Biodiversity Science,2007,15(4):365.
[16] HANLEY A,MCNEIL J.The meaning and use of the area under a receiver operating characteristic (ROC) curve[J].Radiology,1982,143(1):29-36.DOI:10.1148/radiology.143.1.7063747.
[17] 胡理乐,张海英,秦岭,等.中国五味子分布范围及气候变化影响预测[J].应用生态学报,2012,23(9):2445-2450.DOI:10.13287/j.1001-93 32.2012.0338.HU L L,ZHANG H Y,QIN L,et al.Current distribution of Schisandra chinensis in China and its predicted responses to climate change[J].Chinese Journal of Applied Ecology,2012,23(9):2445-2450.
[18] 应凌霄,刘晔,陈绍田,等.气候变化情景下基于最大熵模型的中国西南地区清香木潜在分布格局模拟[J].生物多样性,2016,24(4):453-461.DOI:10.17520/biods.2015246.YING L X,LIU Y,CHEN S T,et al.Simulation of the potential range of Pistacia weinmannifolia in southwest China with climate change based on the Maximum-entropy (Max-ent) Model[J].Biodiversity Science,2016,24(4):453-461.
[19] TOWNSEND P A,COHOON K P.Sensitivity of distributional prediction algorithms to geographic data completeness[J].Ecological Modelling,1999,117(1):159-164.DOI:10.1016/s0304-3800(99)00023-x.
[20] 许国.Jackknife估计及其应用浅探[J].山东师大学报(自然科学版),2000,15(4):454-455.XU G.Explore on estimation and application of Jackknife[J].Journal of Shandong Normal University(Natural Science),2000,15(4):454-455.
[21] LU C Y,GU W,DAI A H,et al.Assessing habitat suitability based on geographic information system (GIS) and fuzzy:a case study of Schisandra sphenanthera Rehd.et Wils.in Qinling Mountains,China[J].Ecological Modelling,2012,242:105-115.DOI:10.1016/j.ecolmodel.2012.06.002.
[2] STOCKWELL D R B.Improving ecological niche models by data mining large environmental datasets for surrogate models[J].Ecological Modelling,2006,192(1/2):188-196.DOI:10.1016/j.ecolmodel.2005.05.029.
[3] SANTANA F S,DE SIQUEIRA M F,SARAIVA A M,et al.A reference business process for ecological niche modelling[J].Ecological Informatics,2008,3(1):75-86.DOI:10.1016/j.ecoinf.2007.12.003.
[4] 冯益明,刘洪霞.基于Maxent与GIS的锈色棕榈象在中国潜在的适生性分析[J].华中农业大学学报,2010,29(5):552-556.FENG Y M,LIU H X.Potential suitability analysis of Rhychophorus ferrugineus (Olvier) in China based on max Ent and GIS[J].Journal of Huazhong Agricultural University,2010,29(5):552-556.
[5] 孙敬松,周广胜.利用最大熵法(MaxEnt)模拟中国冬小麦分布区的年代际动态变化[J].中国农业气象,2012,33(4):481-487.DOI:10.3969/j.issn.1000-6362.2012.04.002.SUN J S,ZHOU G S.Inter-decadal variability of winter wheat planting zone in China during 1961 to 2010 simulated by maximum entropy (MaxEnt)[J].Chinese Journal of Agrometeorology,2012,33(4):481-487.
[6] 李丽鹤,刘会玉,林振山,等.基于MAXENT和ZONATION的加拿大一枝黄花入侵重点监控区确定[J].生态学报,2017,37(9):3124-3132.DOI:10.5846/stxb201601260182.LI L H,LIU H Y,LIN Z S,et al.Identifying priority areas for monitoring the invasion of Solidago canadensis based on MAXENT and ZONATION[J].Acta Ecologica Sinica,2017,37(9):3124-3132.
[7] 雷军成,王莎,王军围,等.未来气候变化对我国特有濒危动物黑麂适宜生境的潜在影响[J].生物多样性,2016,24(12):1390-1399.DOI:10.17520/biods.2016152.LEI J C,WANG S,WANG J W,et al.Potential effects of future climate change on suitable habitat of Muntiacus crinifrons,an endangered and endemic species in China[J].Biodiversity Science,2016,24(12):1390-1399.
[8] 张东方,张琴,郭杰,等.基于MaxEnt模型的当归全球生态适宜区和生态特征研究[J].生态学报,2017,37(15):5111-5120.DOI:10.5846/stxb201605030837.ZHANG D F,ZHANG Q,GUO J,et al.Research on the global ecological suitability and characteristics of regions with Angelica sinensis based on the MaxEnt model[J].Acta Ecologica Sinica,2017,37(15):5111-5120.
[9] 唐继洪,程云霞,罗礼智,等.基于Maxent模型的不同气候变化情景下我国草地螟越冬区预测[J].生态学报,2017,37(14):4852-4863.DOI:10.5846/stxb201604040608.TANG J H,CHENG Y X,LUO L Z,et al.Maxent-based prediction of overwintering areas of Loxostege sticticalis in China under different climate change scenarios[J].Acta Ecologica Sinica,2017,37(14):4852-4863.
[10] 陶冀,关键,彭露萍,等.湖南省马尾松材积生长率模型研究[J].低碳世界,2016(26):280-282.DOI:10.16844/tk.2016.26.171.
[11] HIJMANS R J,CAMERON S E,PARRA J L,et al.Very high resolution interpolated climate surfaces for global land areas[J].International Journal of Climatology,2005,25(15):1965-1978.DOI:10.1002/joc.1276.
[12] 石彦军,任余龙,王式功,等.BCC_CSM气候模式对中国区域气候变化模拟能力的检验 [J].高原气象,2012,31(5):1257-1267.SHI Y J,REN Y L,WANG S G,et al.Verification of simulation ability of BCC_CSM climate model in regional climate change in China[J].Plateau Meteorology,2012,31(5):1257-1267.
[13] PHILLIPS S J,ANDERSON R P,SCHAPIRE R E.Maximum entropy modeling of species geographic distributions[J].Ecological Modelling,2006,190(3/4):231-259.DOI:10.1016/j.ecolmodel.2005.03.026.
[14] MORENO R,ZAMORA R,MOLINA J R,et al.Predictive modeling of microhabitats for endemic birds in South Chilean temperate forests using Maximum entropy (MaxEnt)[J].Ecological Informatics,2011,6(6):364-370.DOI:10.1016/j.ecoinf.2011.07.003.
[15] 王运生,谢丙炎,万方浩,等.ROC曲线分析在评价入侵物种分布模型中的应用[J].生物多样性,2007,15(4):365-372.DOI:10.3321/j.issn:1005-0094.2007.04.005.WANG Y S,XIE B Y,WAN F H,et al.Application of ROC curve analysis in evaluating the performance of alien species’ potential distribution models[J].Biodiversity Science,2007,15(4):365.
[16] HANLEY A,MCNEIL J.The meaning and use of the area under a receiver operating characteristic (ROC) curve[J].Radiology,1982,143(1):29-36.DOI:10.1148/radiology.143.1.7063747.
[17] 胡理乐,张海英,秦岭,等.中国五味子分布范围及气候变化影响预测[J].应用生态学报,2012,23(9):2445-2450.DOI:10.13287/j.1001-93 32.2012.0338.HU L L,ZHANG H Y,QIN L,et al.Current distribution of Schisandra chinensis in China and its predicted responses to climate change[J].Chinese Journal of Applied Ecology,2012,23(9):2445-2450.
[18] 应凌霄,刘晔,陈绍田,等.气候变化情景下基于最大熵模型的中国西南地区清香木潜在分布格局模拟[J].生物多样性,2016,24(4):453-461.DOI:10.17520/biods.2015246.YING L X,LIU Y,CHEN S T,et al.Simulation of the potential range of Pistacia weinmannifolia in southwest China with climate change based on the Maximum-entropy (Max-ent) Model[J].Biodiversity Science,2016,24(4):453-461.
[19] TOWNSEND P A,COHOON K P.Sensitivity of distributional prediction algorithms to geographic data completeness[J].Ecological Modelling,1999,117(1):159-164.DOI:10.1016/s0304-3800(99)00023-x.
[20] 许国.Jackknife估计及其应用浅探[J].山东师大学报(自然科学版),2000,15(4):454-455.XU G.Explore on estimation and application of Jackknife[J].Journal of Shandong Normal University(Natural Science),2000,15(4):454-455.
[21] LU C Y,GU W,DAI A H,et al.Assessing habitat suitability based on geographic information system (GIS) and fuzzy:a case study of Schisandra sphenanthera Rehd.et Wils.in Qinling Mountains,China[J].Ecological Modelling,2012,242:105-115.DOI:10.1016/j.ecolmodel.2012.06.002.