A multi-proxy Holocene palaeoenvironmental record of climate change and prehistoric human activity from Lough Cullin, southeast Ireland

A multiproxy (pollen, microcharcoal, loss-on-ignition, magnetic susceptibility and geochemistry) sequence from Lough Cullin, southeast Ireland, supported by a high-resolution radiocarbon chronology, modelled using Bayesian approaches, provides a record of environmental change for much of the Holocene. Following the establishment of mixed deciduous woodland, climatic deterioration was likely responsible for pronounced vegetation change and erosion, 7615–6500 cal. BC to 6245–5575 cal. BC, evidence for the ‘8.2 Kyr’ BP climate event. The so-called ‘elm decline’ is dated to 4220–3980 cal. BC and whilst there are possible indications of an anthropogenic cause, clear evidence of woodland clearance with cereal pollen is recorded at 3900–3700 cal. BC, 3790–3580 cal. BC and 3760–3650 cal. BC, during a period of clearance and farming of 320–450 years duration. A reduction in farming/settlement and woodland regeneration during the Middle Neolithic parallels the archaeological record, with low levels of activity during the Late Neolithic/Chalcolithic after 2960–2525 cal. BC, prior to increases during the Bronze Age then woodland clearance and agriculture between 1500–1410 and 1275–1000 cal. BC, corresponding with the archaeological evidence. A subsequent ‘step-wise’ reduction in human activity follows, from the latter date to 815–685 cal. BC, and a brief but pronounced cessation at 690–535 cal. BC. Renewed woodland clearance and agriculture commenced until 415–250 cal. BC. From the latter date until cal. AD 390–540, the Late Iron Age/Early Medieval period, a phase of woodland recovery is attested, followed by renewed landscape disturbance and arable agriculture in particular, continuing to the close of the record at cal. AD 780–1035.

Incorporating Vegetation Type Transformation with NDVI Time-Series to Study the Vegetation Dynamics in Xinjiang

Time-series normalized difference vegetation index (NDVI) is commonly used to conduct vegetation dynamics, which is an important research topic. However, few studies have focused on the relationship between vegetation type and NDVI changes. We investigated changes in vegetation in Xinjiang using linear regression of time-series MOD13Q1 NDVI data from 2001 to 2020. MCD12Q1 vegetation type data from 2001 to 2019 were used to analyze transformations among different vegetation types, and the relationship between the transformation of vegetation type and NDVI was analyzed. Approximately 63.29% of the vegetation showed no significant changes. In the vegetation-changed area, approximately 93.88% and 6.12% of the vegetation showed a significant increase and decrease in NDVI, respectively. Approximately 43,382.82 km2 of sparse vegetation and 25,915.44 km2 of grassland were transformed into grassland and cropland, respectively. Moreover, 17.4% of the area with transformed vegetation showed a significant increase in NDVI, whereas 14.61% showed a decrease in NDVI. Furthermore, in areas with NDVI increased, the mean NDVI slopes of pixels in which sparse vegetation transferred to cropland, sparse vegetation transferred to grassland, and grassland transferred to cropland were 9.8 and 3.2 times that of sparse vegetation, and 1.97 times that of grassland, respectively. In areas with decreased NDVI, the mean NDVI slopes of pixels in which cropland transferred to sparse vegetation, grassland transferred to sparse vegetation were 1.75 and 1.36 times that of sparse vegetation, respectively. The combination of vegetation type transformation NDVI time-series can assist in comprehensively understanding the vegetation change characteristics.

Distribution, Dominance Structure, Species Richness, and Diversity of Bats in Disturbed and Undisturbed Temperate Mountain Forests

The increase in mean annual temperature and reduction in summer rainfall from climate change seem to increase the frequency of natural and human-made disturbances to forest vegetation. This type of rapid vegetation change also significantly affects bat diversity. The aim of our study was to document differences in the ecological parameters of bat assemblages in different types of temperate mountain forests, particularly between disturbed and undisturbed coniferous and deciduous forests. Additionally, these issues were considered along an elevation gradient. We mist netted bats on 73 sites, between 931 and 1453 m elevation, in the forests of the Tatra Mountains in southern Poland. During 2016–2020, 745 bats, representing 15 species, were caught. The most abundant were Myotis mystacinus (Kuhl, 1817) (53.0%) and M. brandtii (Eversmann, 1845) (21.5%). We observed differences in species diversity, elevational distribution, and dominance between different types of forests and forest zones. Species richness peaked at around 1000–1100 m elevation. The highest species richness and other indices were observed in undisturbed beech stands, although they constituted only about 2.7% of the forest area. The lowest species diversity was observed in disturbed coniferous forests, in both the lower and upper forest zone. The species richness and dominance structure of bat assemblages were also found to depend on the location above sea level. In some bat species, the sex ratio was higher at higher elevations, and differences in the sex ratio in a few bat species, between different types of forests, were observed. Our findings suggest that disturbed, beetle-killed spruce forests are an unsuitable environment for some bat species.

Spatial analysis and model construction of NDVI Based on meteorological data

NDVI (Normalized Vegetation Index) is an important characteristic index to study regional vegetation change, which is greatly influenced by meteorological data. Based on the analysis of the trend change and correlation between NDVI and PWV (Precipitable Water Vapor), precipitation and temperature in four geographical regions of China, this paper constructs a model between NDVI and PWV, precipitation and temperature in each geographical region according to multiple regression, and predicts NDVI through meteorological data. The results show that:(1) NDVI and meteorological factors have the same changing trend, and the maximum value appears in every region from June to September, and the value of NDVI in southern region is relatively large. (2) The correlation between rainfall and NDVI is the highest in Qinghai-Tibet region, the correlation between temperature, PWV and NDVI is the highest in northern region, the correlation between NDVI and rainfall, temperature and PWV is the lowest in southern region. (3)According to the meteorological data ,NDVI prediction can be achieved better, and the prediction effect in southern region is the best and the model accuracy is the highest. (4) NDVI is negatively related to El Niño event, positively related to La Nina event, and the stronger El Niño and La Nina events are, the higher the correlation is.

Precipitation and Anthropogenic Activities Jointly Green the China–Mongolia–Russia Economic Corridor

Climate change and anthropogenic activities are widely considered the main factors affecting vegetation growth. However, their relative contributions are under debate. Within the non-climatic impact, detailed human activities, particularly government policy adjustments, are less investigated. In this study, we develop a fractional vegetation coverage (FVC) extraction method based on MODIS-EVI satellite data to analyze the spatiotemporal variation of vegetation and its attributions in the China–Mongolia–Russia Economic Corridor (CMREC). The average FVC has improved, with a general increase of 0.02/10a from 2000 to 2020. We construct a driving factor identification system for FVC change, based on partial and multiple correlation coefficients, and we divide the driving forces of FVC changes into seven climate-driven types and one non-climate-driven type. The results reveal that FVC changes caused by climatic factors account for 28.2% of CMREC. The most prominent greening (19.5%) is precipitation-driven, and is extensively distributed in Khentii Aimag, Mongolia; southeast Inner Mongolia; west Jilin Province; and southwest Heilongjiang Province, China. Moreover, we quantify the relative contribution of climatic and non-climatic factors to significant FVC change using the first-difference multivariate regression method. The results indicate that the effects of non-climatic factors on vegetation change outweigh those of climatic factors in most areas. According to the land cover change and regional policy adjustment, anthropogenic activities such as afforestation, reclamation, and planting structure adjustment explain most vegetation improvement in the Northeast Plain; eastern Inner Mongolia; and the Hetao Irrigation District, China. Meanwhile, both vegetation improvement and degradation disperse concurrently in the Mongolian and Russian parts of CMREC, where climate change and anthropogenic activities positively and negatively affect vegetation change, respectively. Despite the greening in most CMREC, it must be noted that human-induced greening is unsustainable to some degree. The overdevelopment of black soil area and sandy land, adverse effects of afforestation projects, and natural hazards related to weather and climate extremes altogether threaten the local ecological security in the long run. Therefore, governments should develop new desertification countermeasures in accordance with the laws of nature, and enhance international cooperation to guarantee the ecological safety of CMREC.

Biophysical Determinants of Shifting Tundra Vegetation Productivity in the Beaufort Delta Region of Canada

Temperature increases across the circumpolar north have driven rapid increases in vegetation productivity, often described as ‘greening’. These changes have been widespread, but spatial variation in their pattern and magnitude suggests that biophysical factors also influence the response of tundra vegetation to climate warming. In this study, we used field sampling of soils and vegetation and random forests modeling to identify the determinants of trends in Landsat-derived Enhanced Vegetation Index, a surrogate for productivity, in the Beaufort Delta region of Canada between 1984 and 2016. This region has experienced notable change, with over 71% of the Tuktoyaktuk Coastlands and over 66% of the Yukon North Slope exhibiting statistically significant greening. Using both classification and regression random forests analyses, we show that increases in productivity have been more widespread and rapid at low-to-moderate elevations and in areas dominated by till blanket and glaciofluvial deposits, suggesting that nutrient and moisture availability mediate the impact of climate warming on tundra vegetation. Rapid greening in shrub-dominated vegetation types and observed increases in the cover of low and tall shrub cover (4.8% and 6.0%) also indicate that regional changes have been driven by shifts in the abundance of these functional groups. Our findings demonstrate the utility of random forests models for identifying regional drivers of tundra vegetation change. To obtain additional fine-grained insights on drivers of increased tundra productivity, we recommend future research combine spatially comprehensive time series satellite data (as used herein) with samples of high spatial resolution imagery and integrated field investigations.

Paleovegetation dynamics in an alternative stable states landscape in the montane Western Ghats, India

Peat deposits (>50 ka) in the montane Nilgiris (Western Ghats, India), have been central to the reconstruction of late Quaternary paleoclimate using paleovegetation changes in the forest-grassland vegetation mosaic that coexist here. However, it is well-known that short-term disturbances can also cause vegetation switches when multiple stable vegetation states exist. We studied paleovegetation changes within the alternative stable states framework using stable carbon isotopes (relative abundance of C3-C4 vegetation) on the cellulose fraction from two high-resolution radiocarbon-dated peat cores ~170 m apart in the Sandynallah valley: Core 1 closer to the hillslope (32,000 years old) and Core 2 from the centre of the valley (45,000 years old). Core 1 is located in an ecotone showing shola-sedgeland dynamics with vegetation switching at c.22 ka from shola (possibly due to fire) to a prolonged unstable state until 13 ka sustained by low waterlogging. Following a hiatus c.13 ka, sedgeland dominates, with a shift into shola at 3.75 ka driven by increasing aridity. Core 2 shows a stable sedgeland mixed C3-C4 composition responding to temperature, enriched in C3-vegetation in the last glacial with C4-dominance beginning c.18.5 ka, indicative of deglacial warming. The distinctive vegetation states at corresponding times in Cores 1 and 2 within the same valley, responding independently to disturbances and climate, respectively, is the first paleo-record from an alternative stable states landscape in the montane tropics. Thus, short-term disturbances and site attributes need to be accounted for before ascribing vegetation change to changing climate in such vegetation mosaics.