机构地区:[1]鄱阳湖湿地与流域研究教育部重点实验室(江西师范大学),南昌330022 [2]江西师范大学生命科学学院,南昌330022
出 处:《生态学报》2014年第19期5522-5529,共8页Acta Ecologica Sinica
基 金:国家自然科学基金项目(31000196);江西省重大生态安全问题监控协同创新中心资助项目(JXS-EW-03);江西省水利厅科技项目"鄱阳湖冬候鸟时空分布对水文节律的响应";鄱阳湖科学考察基金(20114ABG01100-1-03)
摘 要:分析了1985—2011年鄱阳湖国家级自然保护区白琵鹭(Platalea leucorodia)越冬种群数量的年际变化趋势,检验了白琵鹭种群年际数量变化与越冬地气候变化的相关性,气候变量包括月平均气温、月平均最高气温、月平均最低气温和月降水量。研究结果表明,1985—2011年鄱阳湖国家级自然保护区白琵鹭种群数量为(4 632±470)只,呈显著的线性增长趋势,但年际波动较大。在越冬地,白琵鹭的种群数量与白琵鹭越冬期当年冬季各月的气温和降水变量相关系数较小,且均没有显著的相关性。同时,发现越冬地的气候条件对白琵鹭种群数量的影响存在显著的时滞效应:越冬期的月值气候变量与1—9a后的白琵鹭种群数量几乎都存在显著正相关性;10月降水量与2a后的白琵鹭种群数量存在显著负相关,12月平均最高气温与8a后的白琵鹭种群数量存在显著负相关。多元线性回归分析结果表明,越冬地2a前的10月平均最高气温、4a前的11月平均最高气温、8a前的11月降水量、4a前的12月平均气温是白琵鹭种群数量变化的显著预测变量,共同解释了白琵鹭种群数量年际变化的78.9%;其中前3个变量可以共同解释白琵鹭种群数量变化的72.1%,这两个月份正是白琵鹭的越冬初期,是结束长距离迁徙的阶段,可能是白琵鹭补充能量的关键时期,这个时期越冬地恶劣的天气可能导致白琵鹭无法获得充足的能量,不利于能量的恢复,从而可能给种群造成不利的影响。We analyzed the trend in population change Poyang Lake National Nature Reserve between 1985 and of the Eurasian Spoonbill (Platalea leucorodia) wintering in the 2011, and examined the correlation between its population size and climate variables at that reserve. The climate variables included monthly average air temperature, monthly average maximum air temperature, monthly average minimum air temperature, and monthly precipitation. The results showed that the population size of the Eurasian Spoonbill in the Poyang Lake National Nature Reserve was 4632_+470, with a significant linear increase over the period studied and drastic annual fluctuations. There were no significant correlations between population size and climate conditions in the same year. However, we found that climate in wintering areas had a carry-over effect on subsequent population number changes of the Eurasian Spoonbill. The climate in the wintering period was significantly positively correlated with the population size after 1--9 years, precipitation in October was significantly negatively correlated with population size after 2 years, and the average maximum air temperature in December was significantly negatively correlated with population size after 8 years. The results of stepwise linear regression showed that the average minimum air temperature in October 2 years earlier, the average minimum air temperature in November 4 years earlier, the precipitation in November 11 years earlier and the average air temperature in December 4 years earlier were significant predictor factors for population size fluctuations of the Eurasian Spoonbill and accounted for 78.9% of the population size change. The first three variables accounted for 72.1% of the population size fluctuation of the Eurasian Spoonbill. These 2 months represent the primary wintering period when the Eurasian Spoonbill had just arrived at their wintering area. This may be the key period for the Eurasian Spoonbill in which it replenishes its energy. Bad weather in this period may l
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