Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China

Forest ecosystems in an ecotone and their dynamics to climate change are growing ecological and environmental concerns. Phenology is one of the most critical biological indicators of climate change impacts on forest dynamics. In this study, we estimated and visualized the spatiotemporal patterns of forest phenology from 2001 to 2017 in the Qinling Mountains (QMs) based on the enhanced vegetation index (EVI) from MODerate-resolution Imaging Spectroradiometer (MODIS). We further analyzed this data to reveal the impacts of climate change and topography on the start of the growing season (SOS), end of the growing season (EOS), and the length of growing season (LOS). Our results showed that forest phenology metrics were very sensitive to changes in elevation, with a 2.4 days delayed SOS, 1.4 days advanced EOS, and 3.8 days shortened LOS for every 100 m increase in altitude. During the study period, on average, SOS advanced by 0.13 days year−1, EOS was delayed by 0.22 days year−1, and LOS increased by 0.35 day year−1. The phenological advanced and delayed speed across different elevation is not consistent. The speed of elevation-induced advanced SOS increased slightly with elevation, and the speed of elevation-induced delayed EOS shift reached a maximum value of 1500 m from 2001 to 2017. The sensitivity of SOS and EOS to preseason temperature displays that an increase of 1 °C in the regionally averaged preseason temperature would advance the average SOS by 1.23 days and delay the average EOS by 0.72 days, respectively. This study improved our understanding of the recent variability of forest phenology in mountain ecotones and explored the correlation between forest phenology and climate variables in the context of the ongoing climate warming.

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Spatial and temporal variation in morphology in Australian whistlers and shrike-thrushes: is climate change causing larger appendages?

Biological Journal of the Linnean Society ◽

10.1093/biolinnean/blaa028 ◽

2020 ◽

Vol 130 (1) ◽

pp. 101-113

Author(s):

Isabelle R Onley ◽

Janet L Gardner ◽

Matthew R E Symonds

Keyword(s):

Climate Change ◽

Body Size ◽

Temporal Variation ◽

Relative Size ◽

Bird Species ◽

Spatial And Temporal Variation ◽

Climatic Warming ◽

Morphological Response ◽

Allen’S Rule ◽

Spatio Temporal

Abstract Allen’s rule is an ecogeographical pattern whereby the size of appendages of animals increases relative to body size in warmer climates in order to facilitate heat exchange and thermoregulation. Allen’s rule predicts that one consequence of a warming climate would be an increase in the relative size of appendages, and evidence from other bird species suggests that this might be occurring. Using measurements from museum specimens, we determined whether spatio-temporal variation in bills and legs of Australian Pachycephalidae species exhibits within-species trends consistent with Allen’s rule and increases in temperature attributable to climatic warming. We conducted regression model analyses relating appendage size to spatio-temporal variables, while controlling for body size. The relative bill size in four of the eight species was negatively associated with latitude. Tarsus length showed no significant trends consistent with Allen’s rule. No significant increases in appendage size were found over time. Although bill size in some species was positively correlated with warmer temperatures, the evidence was not substantial enough to suggest a morphological response to climatic warming. This study suggests that climate change is not currently driving adaptive change towards larger appendages in these species. We suggest that other adaptive mechanisms might be taking place.

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Spatial and temporal variation in weather events critical for boreal agriculture: II Precipitation

Agricultural and Food Science ◽

10.23986/afsci.51466 ◽

2016 ◽

Vol 25 (1) ◽

Cited By ~ 1

Author(s):

Pirjo Peltonen-Sainio ◽

Pentti Pirinen ◽

Hanna M. Mäkelä ◽

Hannu Ojanen ◽

Ari Venäläinen

Keyword(s):

Temporal Variation ◽

Crop Protection ◽

Growth Yield ◽

Weather Conditions ◽

Growing Season ◽

Spatial And Temporal Variation ◽

Finnish Meteorological Institute ◽

High Soil Moisture ◽

Weather Events ◽

Time Period

There is great temporal and spatial variation in precipitation in Finland. Both drought episodes and repeated, abundant rains may interfere with crop growth, yield and quality formation, and many agricultural operations (such as tillage, sowing, crop protection and harvesting). The windows for optimal operations are often narrow due to the short growing season and variable weather conditions. Field traffic at high soil moisture may e.g. cause soil compaction. Also, the high environmental footprint on agriculture under high latitude conditions is often attributable to fluctuations in precipitation. The station-wise precipitation observations from the Finnish Meteorological Institute for the time period of 54 years (1961‒2014) were interpolated to a regular 10 km × 10 km grid covering the whole country. Several successive time slices were used to calculate the likelihood of: 1) drought periods and 2) periods with repeated rains with above normal precipitation sum so that both of these lasted for at least a) two weeks or b) three weeks. We demonstrated substantial spatial and temporal variation in the likelihood of drought and repeated rains: drought episodes were common during the early half of the growing season, while again repeated rains with high accumulated precipitation (lasting for two weeks) became common in the latter part of the growing season. Though, we highlighted in this paper some examples of how these events may affect agriculture and their environmental impacts, the datasets published here may be applied for many other assessments.

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Spatial and temporal variation in climate change: a bird’s eye view

Climatic Change ◽

10.1007/s10584-009-9644-9 ◽

2009 ◽

Vol 97 (1-2) ◽

Cited By ~ 15

Author(s):

Joseph J. Fontaine ◽

Karie L. Decker ◽

Susan K. Skagen ◽

Charles van Riper

Keyword(s):

Climate Change ◽

Temporal Variation ◽

Spatial And Temporal Variation

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Assessing the spatio-temporal variation and uncertainty patterns of historical and future projected water resources in China

Journal of Water and Climate Change ◽

10.2166/wcc.2013.072 ◽

2013 ◽

Vol 4 (3) ◽

pp. 302-316

Author(s):

Qiuan Zhu ◽

Hong Jiang ◽

Changhui Peng ◽

Jinxun Liu ◽

Xiuqin Fang ◽

...

Keyword(s):

Climate Change ◽

Temporal Variation ◽

Spatial And Temporal Variation ◽

Historical Period ◽

Precipitation Pattern ◽

Climate Change Scenarios ◽

Emission Scenarios ◽

Future Period ◽

Dynamic Global Vegetation Model ◽

The Future

The spatial and temporal variation and uncertainty of precipitation and runoff in China were compared and evaluated between historical and future periods under different climate change scenarios. The precipitation pattern is derived from observed and future projected precipitation data for historical and future periods, respectively. The runoff is derived from simulation results in historical and future periods using a dynamic global vegetation model (DGVM) forced with historical observed and global climate models (GCMs) future projected climate data, respectively. One GCM (CGCM3.1) under two emission scenarios (SRES A2 and SRES B1) was used for the future period simulations. The results indicated high uncertainties and variations in climate change effects on hydrological processes in China: precipitation and runoff showed a significant increasing trend in the future period but a decreasing trend in the historical period at the national level; the temporal variation and uncertainty of projected precipitation and runoff in the future period were predicted to be higher than those in the historical period; the levels of precipitation and runoff in the future period were higher than those in the historical period. The change in trends of precipitation and runoff are highly affected by different climate change scenarios. GCM structure and emission scenarios should be the major sources of uncertainty.

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