Long-term Vegetation Research Articles

人类活动干扰下区域植被动态变化——以西双版纳为例

云南省西双版纳地区是我国典型热带雨林区，随着社会经济发展，人类活动对区域植被格局与动态产生强烈影响。利用NDVI变化趋势分析、土地利用转移矩阵和基于MODIS数据的干扰指数（MGDI）3种方法，分析了2000-2010年人类活动干扰下研究区植被动态变化，构建了人类活动干扰指数，并利用冗余分析的方法，分析其与植被特征的相关性。结果表明：通过NDVI变化趋势得出，2000-2010年间，研究区植被覆盖度总体较高，植被变化趋势的斜率均大于0，说明植被总体趋于改善；基于土地利用转移矩阵结果表明，植被变化主要发生在常绿阔叶林、常绿针叶林转变为乔木园地、灌木园地、人工园地或居住用地；基于MODIS影像结果得出，西双版纳地区MGDI分布很不均匀，且2000-2010不同土地覆被类型MGDI相差不大。构建的人类活动干扰指数结果显示人类干扰强度由中心向边缘呈递增趋势，呈分散分布，这与人类活动的分布规模和强度相关。通过冗余分析可知，NDVI与人类活动相关性较大，MGDI与人类活动相关性不大。总体上来说，上述3种方法能够从不同侧面反映出人类活动干扰下植被长时间的变化趋势。因此，对于西双版纳地区，局地的人类活动特别是旅游、基础设施建设、农业活动等对热带雨林自然生态系统的干扰不容忽视。;Xishuangbanna in Yunnan province is a typical tropical rainforest area in China. With the socio-economic development, human activities have exerted strong impacts on pattern and dynamics of regional vegetation. By analyzing the trend of NDVI, the transfer matrix of land use and disturbance index (MGDI) based on MODIS data, we examined the dynamics of regional vegetation under human disturbance from 2000 to 2010 in this paper. We developed the disturbance index of human activities and found its correlations with vegetation characteristics via the Redundancy analysis. The results showed that the coverage of vegetation in the study area was generally high, and the SLOPE values of the trend of vegetation change were all greater than 0, and the vegetation tended to improve in general during period of 2000-2010. The transfer matrix of land use indicated that the main vegetation dynamics were the changes of evergreen broad-leaved forest and evergreen coniferous forest into plantation shrub, artificial garden or residential land. Based on the MODIS images, it can be seen that the MGDI distribution in Xishuangbanna was very uneven, and the MGDI of different land covers from 2000 to 2010 showed little difference. From the disturbance index of human activity, it can been seen that the disturbance intensity of human activity is higher at the edge than in the center, and the overall distribution was decentralized. The dynamics were related to the distribution scale and intensity of human activities. According to redundancy analysis, NDVI was highly correlated with human activities, while MGDI was not. In general, the long-term vegetation change under human disturbances could be reflected by using three methods used in this study. Through the construction of disturbance index of human activity, we can identify the spatial distribution of disturbance. Human activities especially tourism, infrastructure construction, agricultural activities and other disturbances cannot be ignored for the natural ecosystem of tropical rainforest in Xishuangbanna region.

Climate-human-landscape interaction in the eastern foothills of Mt. Kilimanjaro (equatorial East Africa) during the last two millennia

The Mt. Kilimanjaro region is known for its long history of intensive agriculture, but the temporal extent of human activity and its impact on the regional ecosystem are not well known. In this study, climate-human-landscape interactions during the past ~2200 years were examined using climate and vegetation proxies extracted from the continuous and high-resolution sediment record of Lake Chala. Ancient-to-modern regional human activity is documented against a backdrop of long-term vegetation dynamics in the low-elevation savanna woodland southeast of Mt. Kilimanjaro and riparian forest within Chala crater. During prolonged dry periods (~1170–1300 CE), succulent dry crater forest expanded relative to the moist lakeshore forest. The savanna landscape surrounding Chala crater was relatively stable through time, except that savanna grasses were stimulated by higher precipitation, consistent with the fuel-limited fire regime evidenced in the charcoal record. Expansion of subalpine ericaceous vegetation and a general decline in Afromontane forest taxa on Mt. Kilimanjaro after 550 CE may reflect a lowering of its upper forest line. The earliest robust signature of human influence on regional vegetation involves an increase in ruderal (weedy) plant taxa around 1100 CE, possibly associated with the development of Chagga homegardens and associated agroforestry in the submontane forest zone. A first hint of cereal agriculture (likely sorghum) is observed around 1550 CE, followed by a more robust signature from 1780 CE onwards which likely reflects the start of lowland irrigation agriculture. From 1780 CE we also find the first undisputed appearance of maize, introduced to East Africa about a century earlier.

An Ongoing Blended Long-Term Vegetation Health Product for Monitoring Global Food Security

Remotely observing global vegetation from space has endured for nearly 50 years. Many datasets have been developed to monitor vegetation status. Tailored to specifically monitor global food security concerning drought and crop yield, a suite of datasets based on vegetation health concepts and Advanced Very High Resolution Radiometer (AVHRR) observation was developed in the 1980s and utilized throughout the world. Nowadays, satellites based imaging radiometers have evolved into the Visible Infrared Imaging Radiometer Suite (VIIRS) era. With proper algorithm development, the blended version of the data suite, composed of the AVHRR dataset from 1981 to 2012 and VIIRS dataset from 2013 and afterwards, has bridged the long-term AVHRR observation and high-quality VIIRS data. This paper explains the blended version of the data suite.

Environmental controls over Holocene carbon accumulation in Distichia muscoides-dominated peatlands in the eastern Andes of Colombia

The long-term carbon (C) and vegetation dynamics of tropical, high-Andean cushion peatlands are poorly understood. Here, we present radiocarbon-dated paleoecological records and modern microclimate data from high-elevation peatlands currently dominated by the cushion plant Distichia muscoides in the páramo (alpine tundra) of the eastern Colombian Andes. Focusing on a well-dated 4300-year-old peat core collected at 4194 m elevation from the Sierra Nevada del Cocuy, we investigated the response of peatland vegetation to hydroclimate changes and environmental controls on C accumulation. In addition, we carried out a regional synthesis of existing C accumulation data from northern Andean peatlands to place our new results in broad geographic and temporal context over the last 17,000 years. Our results show that the current Distichia-dominated peatlands are a recent landscape feature on El Cocuy occurring only during the last ∼250 years. The Distichia peatlands have extremely high sediment accumulation rates of up to 1 cm yr−1 and C accumulation rates between 183.7 and 849.5 g C m−2 yr−1, decreasing with the elevation of a site. These rates far exceed an expected modern C accumulation rate of 110 g C m−2 yr−1, calculated by extrapolating an exponential function from a late Holocene average C accumulation rate of 48.6 g C m−2 yr−1 for the northern Andes. This suggests that recent Distichia establishment represents an acceleration of C accumulation at a rate higher than expected from decomposition-related autogenic effects. Before the modern climate warming period, our record indicates that Distichia cushions have only grown intermittently, often after the peatland was flooded with mineral sediments. Mineral sediment deposits at 3290, 2590, 1620, 930, and 860 cal. yr BP correspond with wet intervals from lake-derived records of hydroclimate change in the northern Andes and indicate increases in precipitation and subsequent in-wash of mineral sediments. However, within the last 150 years, mineral sediment deposition has increased in frequency, likely due to warming-induced melting of permanent snow and ice mobilizing exposed fluvio-glacial sediments. Increased mineral nutrients, rising temperatures, and strong diurnal temperature contrast in the tropical mountains may explain the rapid C accumulation rates. Taken together, we show that Andean peatlands have experienced the largest shift in vegetation and C accumulation rates in the last 250 years than at any other time during the last 4000 years.

Temperature and fuel availability control fire size/severity in the boreal forest of central Northwest Territories, Canada

The north-central Canadian boreal forest experienced increased occurrence of large and severe wildfires caused by unusually warm temperatures and drought events during the last decade. It is, however, difficult to assess the exceptional nature of this recent wildfire activity, as few long-term records are available in the area. We analyzed macroscopic sedimentary charcoal from four lakes and pollen grains from one of those lakes to reconstruct long-term fire regimes and vegetation histories in the boreal forest of central Northwest Territories. We used regional estimates of past temperature and hydrological changes to identify the climatic drivers of fire activity over the past 10,000 years. Fires were larger and more severe during warm periods (before ca. 5000 cal yrs. BP and during the last 500 years) and when the forest landscape was characterized by high fuel abundance, especially fire-prone spruce. In contrast, colder conditions combined with landscape opening (i.e., lower fuel abundance) during the Neoglacial (after ca. 5000 cal yrs. BP) were related with a decline in fire size and severity. Fire size and severity increased during the last five centuries, but remained within the Holocene range of variability. According to climatic projections, fire size and severity will likely continue to increase in central Northwest Territories in response to warmer conditions, but precipitation variability, combined with increased abundance of deciduous species or opening of the landscape, could limit fire risk in the future.

The relative contribution of vegetation greening to the hydrological cycle in the Three-North region of China: A modelling analysis

China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the north-eastern, northern, and north-western regions, collectively referred to as the Three-North region (TNR), to combat desertification and control dust storms. Although these programs have alleviated environmental problems in the region to a certain extent, the effects of increasing vegetation greenness on the hydrological cycle remain controversial. In this study, the relative effects of afforestation programs on the hydrologic processes in the TNR were identified based on large-scale hydrological modeling and satellite remote sensing data. The model forcing was featured with long-term vegetation dynamics. The study period ranged from 2000 to 2015, during which the greening of vegetation in the TNR was increased after multiple afforestation programs were carried out around 2000. The results indicated that, despite the spatial heterogeneity, the vegetation leaf area index (LAI) exhibited a significant increase across the TNR. Evapotranspiration (ET) increased over the entire region at the rate of 2.9 mm/year from 2000 to 2015, and its spatial pattern was consistent with changes in the LAI and precipitation. However, this does not imply equal contribution by vegetation growth and precipitation change. The results from the simulation scenarios indicated that precipitation change had a more significant influence on the ET, soil moisture and runoff than vegetation growth at the regional scale. Vegetation greening and precipitation increase in the Loess Plateau indicated their approximately equal impacts on ET and soil moisture. Consequently, the hydrological cycle was sensitive to afforestation practices at small-catchment or sub-regional scales where the magnitude of vegetation greening is relatively high. Therefore, the hydrological effect of vegetation greening at large scale may be overestimated by previous studies. To ensure sustainable water resource management at the TNR scale, special attention should be paid to climate change rather than afforestation efforts under the current level of ecological restoration programs.

Post-fire vegetation succession in the Siberian subarctic tundra over 45 years

Wildfires are relatively rare in subarctic tundra ecosystems, but they can strongly change ecosystem properties. Short-term fire effects on subarctic tundra vegetation are well documented, but long-term vegetation recovery has been studied less. The frequency of tundra fires will increase with climate warming. Understanding the long-term effects of fire is necessary to predict future ecosystem changes.We used a space-for-time approach to assess vegetation recovery after fire over more than four decades. We studied soil and vegetation patterns on three large fire scars (>44, 28 and 12 years old) in dry, lichen-dominated forest tundra in Western Siberia. On 60 plots, we determined soil temperature and permafrost thaw depth, sampled vegetation and measured plant functional traits. We assessed trends in Normalized Difference Vegetation Index (NDVI) to support the field-based results on vegetation recovery.Soil temperature, permafrost thaw depth and total vegetation cover had recovered to pre-fire levels after >44 years, as well as total vegetation cover. In contrast, after >44 years, functional groups had not recovered to the pre-fire state. Burnt areas had lower lichen and higher bryophyte and shrub cover. The dominating shrub species, Betula nana, exhibited a higher vitality (higher specific leaf area and plant height) on burnt compared with control plots, suggesting a fire legacy effect in shrub growth. Our results confirm patterns of shrub encroachment after fire that were detected before in other parts of the Arctic and Subarctic.In the so far poorly studied Western Siberian forest tundra we demonstrate for the first time, long-term fire-legacies on the functional composition of relatively dry shrub- and lichen-dominated vegetation.

Estimating the multi-decadal carbon deficit of burned Amazonian forests

Wildfires in humid tropical forests have become more common in recent years, increasing the rates of tree mortality in forests that have not co-evolved with fire. Estimating carbon emissions from these wildfires is complex. Current approaches rely on estimates of committed emissions based on static emission factors through time and space, yet these emissions cannot be assigned to specific years, and thus are not comparable with other temporally-explicit emission sources. Moreover, committed emissions are gross estimates, whereas the long-term consequences of wildfires require an understanding of net emissions that accounts for post-fire uptake of CO2. Here, using a 30 year wildfire chronosequence from across the Brazilian Amazon, we calculate net CO2 emissions from Amazon wildfires by developing statistical models comparing post-fire changes in stem mortality, necromass decomposition and vegetation growth with unburned forest plots sampled at the same time. Over the 30 yr time period, gross emissions from combustion during the fire and subsequent tree mortality and decomposition were equivalent to 126.1 Mg CO2 ha−1 of which 73% (92.4 Mg CO2 ha−1) resulted from mortality and decomposition. These emissions were only partially offset by forest growth, with an estimated CO2 uptake of 45.0 Mg ha−1over the same time period. Our analysis allowed us to assign emissions and growth across years, revealing that net annual emissions peak 4 yr after forest fires. At present, Brazil’s National Determined Contribution (NDC) for emissions fails to consider forest fires as a significant source, even though these are likely to make a substantial and long-term impact on the net carbon balance of Amazonia. Considering long-term post-fire necromass decomposition and vegetation regrowth is crucial for improving global carbon budget estimates and national greenhouse gases (GHG) inventories for tropical forest countries.

Landslide response to vegetation by example of July 25–26, 2013, extreme rainstorm, Tianshui, Gansu Province, China

Loss Plateau of China is an area with long-term vegetation restoration while serious mass movements. Local vegetation does act as sediment reducing role while quantification of their effect on landslides is lacking. This work presents a first research work about the connection between landslides and vegetation by the example of July 25–26, 2013, extreme rainstorm. High-resolution sensing orthoimages, landside width, and simplified infinite slope theory were used to examine landslide distribution and the lateral apparent cohesion of roots. The results reveal that shallow landslides have a higher probability at the transitional slope area. The majority of them have a gradient of 20–25°, locate on south-facing slopes, and areas with sparse vegetation. Vegetation cover, represented by the Green-Red Vegetation Index (GRVI), is the controlling factor of landslide distribution and size. The estimated lateral apparent cohesion of plant roots is not positively related to GRVI, and increase when GRVI > 0.2. The relationship between landslide width and slope gradient indicates that strong root strength may result in larger landslide volume. This result of this work is a pioneering trial in correlating the lateral apparent cohesion from roots and forest crown, which is helpful for understanding the effect of vegetation on landslides.

An improved trend vegetation analysis for non-stationary NDVI time series based on wavelet transform.

The aim of this paper is to improve trend analysis for non-stationary Normalized Difference Vegetation Index (NDVI) time series (TS) over different areas in Tunisia based on the wavelet transform (WT) multi-resolution analysis (MRA-WT), statistical test, and meteorological data. The MRA-WT was applied in order to decompose the TS into different components. However, the most challenge for TS analysis using MRA-WT laid in the selection of two optimum parameters: the level of decomposition and mother wavelet (MW). In this work, both factors were investigated. Firstly, the level of decomposition was calculated for 18 different MWs, and secondly the energy to Shannon entropy ratio criterion was investigated to choose the most suitable MW. The Mann-Kendall test (MK) and Sen's slope were applied to the last approximation component in order to analyze long-term vegetation changes. Finally, the influence of meteorological data for trend was analyzed. The results were first computed for different sites in Tunisia using MODIS NDVI TS from 2001 to 2017. The obtained results proved the importance of MW selection. Level 5 was considered for the TS as the best level of decomposition for long-term vegetation changes. The Daubechies and Symlets MWs (db9 and sym4) showed the highest energy to entropy ratio for three selected vegetation canopies. A combination of the two MW was proposed to derive a trend vegetation analysis at image level. A degradation in the forest area and a few increases in cropland and vegetation area were presented.

Forecasting fire risk with machine learning and dynamic information derived from satellite vegetation index time-series

Fire risk mapping – mapping the probability of fire occurrence and spread – is essential for pre-fire management as well as for efficient firefighting efforts. Most fire risk maps are generated using static information on variables such as topography, vegetation density, and fuel instantaneous wetness. Satellites are often used to provide such information. However, long-term vegetation dynamics and the cumulative dryness status of the woody vegetation, which may affect fire occurrence and spread, are rarely considered in fire risk mapping. Here, we investigate the impact of two satellite-derived metrics that represent long-term vegetation status and dynamics on fire risk mapping – the long-term mean normalized difference vegetation index (NDVI) of the woody vegetation (NDVIW) and its trend (NDVIT). NDVIW represents the mean woody density at the grid cell, while NDVIT is the 5-year trend of the woody NDVI representing the long-term dryness status of the vegetation. To produce these metrics, we decompose time-series of satellite-derived NDVI following a method adjusted for Mediterranean woodlands and forests. We tested whether these metrics improve fire risk mapping using three machine learning (ML) algorithms (Logistic Regression, Random Forest, and XGBoost). We chose the 2007 wildfires in Greece for the analysis. Our results indicate that XGBoost, which accounts for variable interactions and non-linear effects, was the ML model that produced the best results. NDVIW improved the model performance, while NDVIT was significant only when NDVIW was high. This NDVIW–NDVIT interaction means that the long-term dryness effect is meaningful only in places of dense woody vegetation. The proposed method can produce more accurate fire risk maps than conventional methods and can supply important dynamic information that may be used in fire behavior models.

Effects of plant growth and spacing on soil hydrological changes: a field study

Effects of plant growth on soil hydrological changes need to be considered for long-term vegetation management of geotechnical infrastructure. Most existing studies focused on one particular plant age. This study quantifies the effects of plant growth on the evolution of soil hydraulic properties and matric suction over time, through field monitoring and numerical soil–plant–atmosphere interaction modelling. A full-scale flat landfill cover in China was monitored for more than a year. Four 6 m × 6 m grass plots made of compacted silty sand were formed, three of which were vegetated with shrubs having different plant spacing (0·5, 0·8 and 1·1 m), while the fourth one was left grassed. In addition to monitoring matric suction changes, multiple soil cores were sampled to determine the root length density (RLD) and saturated hydraulic conductivity (ks) after 2, 4, 7 and 13 months of transplantation. Regardless of plant spacing, ks always reduced during the first 2–3 months of growth. When a threshold RLD of 2 cm/cm3 was reached, ks increased substantially. This was especially the case for closely spaced shrubs, whose roots were decayed. Suction preserved upon rainfall depended on the plant growth-induced changes in ks. Although closely spaced (0·5 m) shrubs preserved the most suction during the first 6 months of growth, the beneficial hydrological effects vanished after growing for 9 months because of the shrub growth-induced increase in ks. Instead, the widely spaced (1·1 m) shrubs, which showed the least increase in ks, preserved the most suction in later stages. Nonetheless, the spacing of shrubs did not affect the annual cumulative percolation of the landfill cover very significantly, which narrowly ranged between 3·1 and 4·7% of the annual precipitation during the monitoring period.

Changes in soil carbon fractions and enzyme activities under different vegetation types of the northern Loess Plateau.

Knowledge of the soil organic carbon components and enzyme activities during long‐term natural vegetation restoration is essential for managing the restoration of vegetation. In this study, the variations of soil organic carbon components (i.e., soil organic carbon (SOC), microbial biomass carbon (MBC), easily oxidized carbon (EOC), particulate organic carbon (POC)) and enzyme activities (i.e., amylase, catalase, urease, and sucrase) were measured in four vegetation types: control (grasslands, GL), forest (Xanthoceras sorbifolia, XS), and shrublands (Hippophae rhamnoides, HR; Caragana korshinskii, CK). We found that vegetation types significantly affect soil organic carbon components and enzyme activities. The SOC content of the XS plot is higher than HR, CK, and GL by 88.43%, 117.09%, and 37.53% at the 0–20 cm layer; the soil SOC content of the XS plot is higher than HR and CK by 27.04% and 26.87%, and lower than GL 12.90% at the 20–40 cm layer. The highest POC and urease were observed in the XS plot at a depth of 0–20 cm, that is, 1.32 g/kg and 98.51 mg/kg, respectively. The highest EOC, amylase, and sucrase were observed in GL at a depth of 0–20 cm, that is, 5.44 g/kg, 39.23, and 607.62 mg/g. On the vertical section of the soil, the SOC fractions and the enzyme activities were greater in the upper layer than in the lower layer for each vegetation type except for MBC and catalase activity. Correlation analysis demonstrated that the SOC and POC content significantly influenced urease and sucrase activities and that MBC significantly influenced catalase activity. These results provide important information about SOC fractions and enzyme activities resulting from vegetation types in the Loess Plateau and also supplement our understanding of soil C sequestration in vegetation restoration.

Prioritizing Research Needs in Natural Resources: Using Q-Methodology as a Focus Group Discussion Tool

Abstract Combining Q-methodology with focus groups offers a novel opportunity to explore how researchers and managers can collectively address natural resource management issues. We explored the potential utility of this pairing for prioritizing long-term vegetation recovery research needs after wildfire at a two-day workshop. The approach entailed individual Q-sort activities, followed by focus group discussion about differences and similarities in Q-sort outcomes between managers and researchers. We found that Q-methodology was a versatile discussion tool that offered opportunities for building shared definitions of management issues and identifying new pathways for collaboration between diverse participants. Group discussion around research needs also fostered opportunities for identifying organizational barriers and fostering partnerships to overcome them. Collecting social data on research needs prior to designing or conducting data collection efforts can help ensure that outputs have practical value and utility for land management. Study Implications Establishing shared research priorities between researchers and managers is one way to ensure that scientific advancements have practical applications. Using outputs from Q-sort activities as a prompt to initiate discussion between researchers and managers is an effective technique for understanding divergent prioritizations, identifying organizational and scientific barriers, and establishing feasible next steps for collective action to produce application-oriented research. Employing mixed-method social data collection early in the land management planning process is increasingly valuable; many recent policies for forest and natural resource management require the incorporation of collaborative components.

Species Monitoring Using Unmanned Aerial Vehicle to Reveal the Ecological Role of Plateau Pika in Maintaining Vegetation Diversity on the Northeastern Qinghai-Tibetan Plateau

Plateau pika (Ochotona curzoniae, hereafter pika) is considered to exert a profound impact on vegetation species diversity of alpine grasslands. Great efforts have been made at mound or quadrat scales; nevertheless, there is still controversy about the effect of pika. It is vital to monitor vegetation species composition in natural heterogeneous ecosystems at a large scale to accurately evaluate the real role of pika. In this study, we performed field survey at 55 alpine grassland sites across the Shule River Basin using combined methods of aerial photographing using an unmanned aerial vehicle (UAV) and traditional ground measurement. Based on our UAV operation system, Fragmentation Monitoring and Analysis with aerial Photography (FragMAP), aerial images were acquired. Plot-scale vegetation species were visually identified, and total pika burrow exits were automatically retrieved using the self-developed image processing software. We found that there were significant linear relationships between the vegetation species diversity indexes obtained by these two methods. Additionally, the total number of identified species by the UAV method was 71, which was higher than the Quadrat method recognition, with the quantity of 63. Our results indicate that the UAV was suitable for long-term repeated monitoring vegetation species composition of multiple alpine grasslands at plot scale. With the merits of UAV, it confirmed that pika’s disturbance belonged to the medium level, with the density ranging from 30.17 to 65.53 ha−1. Under this density level, pika had a positive effect on vegetation species diversity, particularly for the species richness of sedge and forb. These findings conclude that the UAV was an efficient and economic tool for species monitoring to reveal the role of pika in the alpine grasslands.

Storm runoff generation in headwater catchments on the Chinese Loess Plateau after long-term vegetation rehabilitation

Storm runoff is important for maintaining surface water resources, while this function is significantly affected by land use and land cover changes, e.g., afforestation and reforestation. The Chinese Loess Plateau (CLP) has undergone large-scale vegetation rehabilitation, especially afforestation over the past 20 years. We hypothesize that afforestation has profoundly changed the amounts and mechanisms of storm runoff generation in headwater catchments on the CLP. To test this hypothesis, rainfall, soil moisture, and streamflow were monitored in a grass catchment and an adjacent forest catchment for two consecutive years. The objective of this study was to elucidate the varied mechanisms of storm runoff generation in these two contrasting revegetated catchments. Results showed that (1) average runoff coefficient in the grassland catchment (0.042) was approximately ten times higher than that in the forestland catchment (0.004), confirming the impact of catchment afforestation on the suppression of storm runoff generation. (2) Peak rainfall intensity was the first-order control of the runoff coefficient in the grassland catchment, but not in the forestland catchment. (3) Threshold values for antecedent soil moisture (~18%) and the sum of antecedent soil moisture index and event precipitation (~210 mm) were identified in the grassland catchment, above which storm runoff significantly increased. (4) Two extraordinary high runoff coefficient events were observed in the grassland catchment, one due to high peak rainfall intensity and strong surface runoff and the other due to high rainfall amount and high antecedent soil moisture. We conclude that long-term afforestation has changed the mechanisms and patterns of storm runoff generation, and different conditions of rainfall intensity, rainfall amount and antecedent soil moisture determined the hydrological connectivity between the upper hillslope and downhill gully in the catchment. This study deepens our understanding of the mechanisms and thresholds of storm runoff generation in headwater catchments on the CLP.

Long-Term Seeding Outcomes in Slash Piles and Skid Trails after Conifer Removal

Conifer removal in interior woodland ecosystems of the western US is a common management treatment used to decrease fire hazard and shift woodlands to more historical states. Woody material is frequently removed by skidding material off site and via slash pile burning. Assessing the long-term outcomes of seeding treatments after such ground disturbing activities is critical for informing future management and treatment strategies. Using two designed experiments from a central Oregon juniper woodland, we resampled slash piles and skid trails 8 years after seeding. Our objectives were to assess the long-term vegetation response to conifer removal, ground disturbance, and seeding source (cultivar and local) in slash piles and skid trails. We found that seeded species persisted in the long term, but abundance patterns depended on the species, seed source, and the type of disturbance. In general, there were more robust patterns of persistence after pile burning compared to skid trails. Seeding also suppressed exotic grass cover in the long term, particularly for the local seed source. However, the invasion levels we report are still problematic and may have impacts on biodiversity, forage and fire behavior. Our short-term results were not predictive of longer-term outcomes, but short- and long-term patterns were somewhat predictable based on species life history traits and ecological succession. The use of a mix of species with different life history traits may contribute to seeding success in terms of exotic grass suppression. Lastly, our results suggest that locally adapted seed sources may perform as well or better compared to cultivars. However, more aggressive weed treatments before and after conifer removal activities and wider seeding application may be needed to effectively treat exotic grass populations.

Foliar Spectra and Traits of Bog Plants across Nitrogen Deposition Gradients

Bogs, as nutrient-poor ecosystems, are particularly sensitive to atmospheric nitrogen (N) deposition. Nitrogen deposition alters bog plant community composition and can limit their ability to sequester carbon (C). Spectroscopy is a promising approach for studying how N deposition affects bogs because of its ability to remotely determine changes in plant species composition in the long term as well as shorter-term changes in foliar chemistry. However, there is limited knowledge on the extent to which bog plants differ in their foliar spectral properties, how N deposition might affect those properties, and whether subtle inter- or intraspecific changes in foliar traits can be spectrally detected. The objective of the study was to assess the effect of N deposition on foliar traits and spectra. Using an integrating sphere fitted to a field spectrometer, we measured spectral properties of leaves from the four most common vascular plant species (Chamaedaphne calyculata, Kalmia angustifolia, Rhododendron groenlandicum and Eriophorum vaginatum) in three bogs in southern Québec and Ontario, Canada, exposed to different atmospheric N deposition levels, including one subjected to a 18-year N fertilization experiment. We also measured chemical and morphological properties of those leaves. We found detectable intraspecific changes in leaf structural traits and chemistry (namely chlorophyll b and N concentrations) with increasing N deposition and identified spectral regions that helped distinguish the site-specific populations within each species. Most of the variation in leaf spectral, chemical, and morphological properties was among species. As such, species had distinct spectral foliar signatures, allowing us to identify them with high accuracy with partial least squares discriminant analyses (PLSDA). Predictions of foliar traits from spectra using partial least squares regression (PLSR) were generally accurate, particularly for the concentrations of N and C, soluble C, leaf water, and dry matter content (<10% RMSEP). However, these multi-species PLSR models were not accurate within species, where the range of values was narrow. To improve the detection of short-term intraspecific changes in functional traits, models should be trained with more species-specific data. Our field study showing clear differences in foliar spectra and traits among species, and some within-species differences due to N deposition, suggest that spectroscopy is a promising approach for assessing long-term vegetation changes in bogs subject to atmospheric pollution.

Effects of Long-Term Vegetation Restoration on Distribution of Deep Soil Moisture in Semi-arid Northwest of China

We aim to understand the distribution of soil moisture and its controlling factors for regional vegetation restoration in a semi-arid sandy land. The top 500 cm soils of the main introduced vegetation types restored for different years in Chinese Mu Us Sandy Land were collected, and the soil moisture and influencing factors were analyzed. The results demonstrated that the total soil water storage decreased in a sequence of shrub land (S) ˃ arbor land (A) ˃ shifting sandy land (CK) ˃ grassland (G). With the increase of restoration period, the soil moisture increased in arbor land and decreased first and then increased in both shrub land and grassland. Soil moisture was negatively correlated (P < 0.05) with root length density (RLD) in G56, S36, A21, and S21. RLD and soil moisture in S56 showed an extremely significant negative correlation (P < 0.01). Soil water content had a positive correlation with silt content (P < 0.05) but demonstrated a negative correlation with the sand content (P < 0.05) in A56. Both silt and sand contents showed negative correlations with soil moisture in G56 (P < 0.05). In summary, vegetation type, restoration period, RLD, and silt and clay contents have significant effects on soil moisture. To improve the soil moisture status, arbors and bushes should be preferentially considered for vegetation restoration in semi-arid northwest of China.

Fire-vegetation interactions during the last 11,000 years in boreal and cold temperate forests of Fennoscandia

The long-term ecological interactions between fire and the composition of dominant trees and shrubs in boreal and cold temperate Fennoscandian forests are still under discussion. We hypothesized that fire-prone taxa should abound during periods and regions characterized by higher fire disturbance, while fire-intolerant taxa should dominate when and where fire activity is low. Biomass burning (BB) is here investigated based on 69 sedimentary charcoal records. For the same sites, the relative contribution of pollen-based reconstructions of dominant vegetation cover divided into three different fire-sensitivity classes is explored by means of a statistical approach. The overall patterns found across Fennoscandia suggest that Ericaceae (mainly Calluna), Pinus, Betula and Populus are strongly positively correlated with multi-millennial variability of BB in both boreal and cold temperate forests, confirming their fire-prone character (taxa adapted/favoured by burning). Positive but much weaker (and not always significant) relationships also exist between long-term trends in BB and Fagus, Quercus, Corylus, Alnus, Juniperus, Carpinus and Salix, fire-tolerant taxa that survive low/moderate intense fires because of specific functional traits or their rapid, enhanced regeneration after fire. A strong negative significant correlation is instead detected between BB and Picea, Ulmus Tilia, Fraxinus, which are fire-intolerant taxa and can locally disappear for a short time after a fire. This large-scale analysis supports our initial hypothesis that tree and shrub dominance was closely linked to biomass burning since the onset of the Holocene in the study regions. Fire was an important ecosystem disturbance in Fennoscandia influencing long-term vegetation dynamics and composition over the last 11,000 years, although human activities probably altered the strength of fire-vegetation interactions during more recent millennia.