生态环境学报
生態環境學報
생태배경학보
ECOLOGY AND ENVIRONMENT
2015年
3期
365-371
,共7页
青稞%归一化植被指数%归一化绿波段差值植被指数%土壤调节植被指数%红外增温
青稞%歸一化植被指數%歸一化綠波段差值植被指數%土壤調節植被指數%紅外增溫
청과%귀일화식피지수%귀일화록파단차치식피지수%토양조절식피지수%홍외증온
highland barley%normalized difference vegetation index%green normalized difference vegetation index%soil adjusted vegetation index%infrared warming
气候变暖影响着农作物生长及其植被指数。为了探讨西藏高原青稞（Hordeum vulgare Linn. var. nudum Hook.f.）归一化植被指数（normalized difference vegetation index，NDVI）、归一化绿波段差值植被指数（normalized green difference vegetation index，GNDVI）和土壤调节植被指数（soil adjusted vegetation index，SAVI）对气候变暖的初始响应，2014年5月在西藏达孜县布设了一个红外增温实验（3个水平，即对照，1000和2000 W红外增温）。通过对2014年6─9月利用农业多光谱相机获取的3种植被指数和利用HOBO微气候观测系统获取的两个深度（5和20 cm）的土壤温湿度的统计分析，探讨了西藏高原青稞植被指数对红外增温的响应及其与土壤温湿度的相互关系。结果表明，1000和2000 W的增温使5 cm的土壤温度（t5）分别升高了约1.62和1.77℃，使20 cm的土壤温度（t20）分别升高了约1.16和1.43℃；相反使5 cm的土壤湿度（SM5）分别下降了约1.8%和14.1%，使20 cm的土壤湿度（SM20）分别下降了21.6%和14.7%。1000 W的增温使NDVI、GNDVI和SAVI分别增加了约2.4%、4.3%和0.5%；2000 W的增温则使NDVI、GNDVI和SAVI分别增加了约5.5%、5.3%和4.8%，尽管增加幅度并不显著。单因子回归分析表明，t5与NDVI（r2=0.110，P=0.026）和GNDVI（r2=0.254，P=0.0004）为负相关，而与SAVI无关（r2=0.069，P=0.082）；t20与GNDVI为负相关（r2=0.218，P=0.001），而与NDVI（r2=0.040，P=0.190）和SAVI（r2=0.014，P=0.443）无关；SM5与NDVI（r2=0.277，P=0.0002）、GNDVI（r2=0.394，P=0.0000）和SAVI（r2=0.208， P=0.002）为正相关。SM20与GNDVI为正相关（r2=0.193，P=0.003），而与NDVI（r2=0.059，P=0.107）和SAVI（r2=0.037， P=0.209）无关。多重回归分析表明，SM5主导着NDVI、GNDVI和SAVI的变异。偏相关分析表明，NDVI、GNDVI和SAVI与SM5的相关系数分别为0.442（P=0.003）、0.412（P=0.007）和0.404（P=0.008）；与SM20的相关系数分别为-0.042（P=0.792）、0.051（P=0.749）和-0.033（P=0.837）；与 t5的相关系数分别为-0.154（P=0.332）、-0.019（P=0.907）和-0.170（P=0.282）；与 t20的相关系数分别为0.228（P=0.147）、-0.041（P=0.795）和0.268（P=0.086）。因此，红外增温引起的干旱抑制了青稞的生长，进而影响了植被指数，即植被指数的不显著变化可能与红外增温引起的土壤干旱有关。
氣候變暖影響著農作物生長及其植被指數。為瞭探討西藏高原青稞（Hordeum vulgare Linn. var. nudum Hook.f.）歸一化植被指數（normalized difference vegetation index，NDVI）、歸一化綠波段差值植被指數（normalized green difference vegetation index，GNDVI）和土壤調節植被指數（soil adjusted vegetation index，SAVI）對氣候變暖的初始響應，2014年5月在西藏達孜縣佈設瞭一箇紅外增溫實驗（3箇水平，即對照，1000和2000 W紅外增溫）。通過對2014年6─9月利用農業多光譜相機穫取的3種植被指數和利用HOBO微氣候觀測繫統穫取的兩箇深度（5和20 cm）的土壤溫濕度的統計分析，探討瞭西藏高原青稞植被指數對紅外增溫的響應及其與土壤溫濕度的相互關繫。結果錶明，1000和2000 W的增溫使5 cm的土壤溫度（t5）分彆升高瞭約1.62和1.77℃，使20 cm的土壤溫度（t20）分彆升高瞭約1.16和1.43℃；相反使5 cm的土壤濕度（SM5）分彆下降瞭約1.8%和14.1%，使20 cm的土壤濕度（SM20）分彆下降瞭21.6%和14.7%。1000 W的增溫使NDVI、GNDVI和SAVI分彆增加瞭約2.4%、4.3%和0.5%；2000 W的增溫則使NDVI、GNDVI和SAVI分彆增加瞭約5.5%、5.3%和4.8%，儘管增加幅度併不顯著。單因子迴歸分析錶明，t5與NDVI（r2=0.110，P=0.026）和GNDVI（r2=0.254，P=0.0004）為負相關，而與SAVI無關（r2=0.069，P=0.082）；t20與GNDVI為負相關（r2=0.218，P=0.001），而與NDVI（r2=0.040，P=0.190）和SAVI（r2=0.014，P=0.443）無關；SM5與NDVI（r2=0.277，P=0.0002）、GNDVI（r2=0.394，P=0.0000）和SAVI（r2=0.208， P=0.002）為正相關。SM20與GNDVI為正相關（r2=0.193，P=0.003），而與NDVI（r2=0.059，P=0.107）和SAVI（r2=0.037， P=0.209）無關。多重迴歸分析錶明，SM5主導著NDVI、GNDVI和SAVI的變異。偏相關分析錶明，NDVI、GNDVI和SAVI與SM5的相關繫數分彆為0.442（P=0.003）、0.412（P=0.007）和0.404（P=0.008）；與SM20的相關繫數分彆為-0.042（P=0.792）、0.051（P=0.749）和-0.033（P=0.837）；與 t5的相關繫數分彆為-0.154（P=0.332）、-0.019（P=0.907）和-0.170（P=0.282）；與 t20的相關繫數分彆為0.228（P=0.147）、-0.041（P=0.795）和0.268（P=0.086）。因此，紅外增溫引起的榦旱抑製瞭青稞的生長，進而影響瞭植被指數，即植被指數的不顯著變化可能與紅外增溫引起的土壤榦旱有關。
기후변난영향착농작물생장급기식피지수。위료탐토서장고원청과（Hordeum vulgare Linn. var. nudum Hook.f.）귀일화식피지수（normalized difference vegetation index，NDVI）、귀일화록파단차치식피지수（normalized green difference vegetation index，GNDVI）화토양조절식피지수（soil adjusted vegetation index，SAVI）대기후변난적초시향응，2014년5월재서장체자현포설료일개홍외증온실험（3개수평，즉대조，1000화2000 W홍외증온）。통과대2014년6─9월이용농업다광보상궤획취적3충식피지수화이용HOBO미기후관측계통획취적량개심도（5화20 cm）적토양온습도적통계분석，탐토료서장고원청과식피지수대홍외증온적향응급기여토양온습도적상호관계。결과표명，1000화2000 W적증온사5 cm적토양온도（t5）분별승고료약1.62화1.77℃，사20 cm적토양온도（t20）분별승고료약1.16화1.43℃；상반사5 cm적토양습도（SM5）분별하강료약1.8%화14.1%，사20 cm적토양습도（SM20）분별하강료21.6%화14.7%。1000 W적증온사NDVI、GNDVI화SAVI분별증가료약2.4%、4.3%화0.5%；2000 W적증온칙사NDVI、GNDVI화SAVI분별증가료약5.5%、5.3%화4.8%，진관증가폭도병불현저。단인자회귀분석표명，t5여NDVI（r2=0.110，P=0.026）화GNDVI（r2=0.254，P=0.0004）위부상관，이여SAVI무관（r2=0.069，P=0.082）；t20여GNDVI위부상관（r2=0.218，P=0.001），이여NDVI（r2=0.040，P=0.190）화SAVI（r2=0.014，P=0.443）무관；SM5여NDVI（r2=0.277，P=0.0002）、GNDVI（r2=0.394，P=0.0000）화SAVI（r2=0.208， P=0.002）위정상관。SM20여GNDVI위정상관（r2=0.193，P=0.003），이여NDVI（r2=0.059，P=0.107）화SAVI（r2=0.037， P=0.209）무관。다중회귀분석표명，SM5주도착NDVI、GNDVI화SAVI적변이。편상관분석표명，NDVI、GNDVI화SAVI여SM5적상관계수분별위0.442（P=0.003）、0.412（P=0.007）화0.404（P=0.008）；여SM20적상관계수분별위-0.042（P=0.792）、0.051（P=0.749）화-0.033（P=0.837）；여 t5적상관계수분별위-0.154（P=0.332）、-0.019（P=0.907）화-0.170（P=0.282）；여 t20적상관계수분별위0.228（P=0.147）、-0.041（P=0.795）화0.268（P=0.086）。인차，홍외증온인기적간한억제료청과적생장，진이영향료식피지수，즉식피지수적불현저변화가능여홍외증온인기적토양간한유관。
Climatic warming affects the crop growth and its related vegetation indices. In order to understand the initial response of normalized difference vegetation index (NDVI), normalized green difference vegetation index (GNDVI) and soil adjusted vegetation index (SAVI) to climatic warming, a field warming experiment using infrared radiator was conducted in a highland barley located at the Dazi county of the Tibet since late May, 2015. There were three warming treatments, i.e., control, low (1000 W) and high (2000W) warming. The NDVI, GNDVI and SAVI were obtained using an agricultural digital camera during the period from June to September in 2015. Meanwhile, the soil temperature and soil moisture at depths of 5 cm and 20 cm were also obtained using HOBO microclimate observing systems. Then this study analyzed the response of NDVI, GNDVI and SAVI to infrared warming and the relationships between the three vegetation indices and soil temperature and moisture. The 1000 W and 2000 W infrared warming increased soil temperature at the depth of 5 cm (t5) by 1.62℃ and 1.77℃, and soil temperature at the depth of 20 cm (t20) by 1.16℃and 1.43℃, but decreased soil moisture at the depth of 5 cm (SM5) by 1.8% and 14.1%, and soil moisture at the depth of 20 cm (SM20) by 21.6% and 14.7%, respectively. The 1000 W infrared warming increased NDVI by 2.4%, GNDVI by 4.3% and SAVI by 0.5%, whereas the 2000 W infrared warming increased NDVI by 5.5%, GNDVI by 5.3% and SAVI by 4.8%, although these changes were non-significant. Simple regression analyses showed that (1) NDVI (r2=0.110,P=0.026) and GNDVI(r2=0.254, P=0.0004)decreased with increasingt5,whereas there was non-significant correlation between SAVI andt5 (r2=0.069,P=0.082); (2) GNDVI decreased with increasingt20, (r2=0.218,P=0.001), whereas there were non-significant relationships between NDVI (r2=0.040,P=0.190), SAVI (r2=0.014,P=0.443) andt20; (3) NDVI (r2=0.277,P=0.0002), GNDVI (r2=0.394,P=0.0000) and SAVI (r2=0.208,P=0.002)increased with increasing SM5; and (4) GNDVI increased with increasing SM20(r2=0.193,P=0.003), whereas there were non-significant correlations between NDVI (r2=0.059,P=0.107), SAVI (r2=0.037,P=0.209) and SM20. Multiple regression analyses indicated that SM5dominated the variations of NDVI, GNDVI and SAVI. Partial correlation analyses demonstrated that (1) the correlation coefficients of NDVI, GNDVI and SAVI with SM5were 0.442 (P=0.003), 0.412 (P=0.007) and 0.404 (P=0.008); (2) with SM20were -0.042 (P=0.792), 0.051 (P=0.749) and -0.033 (P=0.837); (3) witht5were -0.154 (P=0.332), -0.019 (P=0.907) and -0.170 (P=0.282); and (4) witht20 were 0.228 (P=0.147), -0.041 (P=0.795) and 0.268 (P=0.086), respectively. Therefore, the soil drying induced by infrared warming suppressed the growth of highland barley, which in turn affected vegetation indices. That is, the non-significant changes of the three vegetation indices may be due to the infrared warming-induced drying.
