Main Climatic Drivers Research Articles

Compound-Specific Carbon Isotopes and Concentrations of Carbohydrates and Organic Acids as Indicators of Tree Decline in Mountain Pine

We investigated seasonal variations in δ13C values and concentrations of carbohydrates and organic acids in needles of declining and healthy mountain pine (Pinus mugo ssp. uncinata (DC.) Domin) trees from the Swiss National Park (SNP), using compound-specific isotopes analysis (CSIA). Our goal was to study the impact of climatic drivers on the individual compounds and understand the reasons of partial tree declines in relation to healthy mountain pine trees under seasonal weather patterns. We found that temperature is the main climatic driver determining the seasonal carbon dynamics at the needle level. Lower seasonal δ13C variability and lower concentration levels of sucrose in needles suggest less photosynthetic activity and sink carbon demand in declining compared to healthy mountain pine trees. Higher concentration levels of hexose (glucose and fructose) can play a reserve function for surviving mechanisms of mountain pine trees. Seasonal patterns of organic acid (malate and citrate) suggest an increasing investment in maintenance and repair mechanisms. The seasonal course of carbohydrates and organic acids can therefore be considered an indicator for a modified carbon metabolism within the leaves and possibly within the other tree tissues, partially explaining the decline of mountain pine trees.

An intra-stand approach to identify intra-annual growth responses to climate in Pinus nigra subsp. laricio Poiret trees from southern Italy

The growth of Pinus nigra tree stands is known to be limited by spring-summer precipitation (P). We explored the intra-annual growth dynamics (early-wood EW and late-wood LW of tree-rings) and their responses to climate (in monthly, seasonal and annual scale) in Pinus nigra subsp. laricio at the intra-stand level in Calabria, at the pines' mesic to xeric distribution range. We used a variety of age detrending methods to assess how the adaptive potential to climate change of each tree varies within the even-aged forest stand. In years of wet climate, when precipitation (P) could infiltrate deeper below ground, higher growth rates occurred in 83% of trees, best explained by P accumulated over several previous years. The variability of EW increment was best explained by 3–5 previous year P (including the growth year) in 61% of trees, while LW increment was best explained by 1–3 year P in 78% of trees. This would suggest that in wet years most trees utilized not only surface but also deeper moisture pools using their taproot to produce both EW and LW. In contrast, during dry years, for 39% of trees the most significant predictor for EW was June rainfall. August P explained LW variability in 35% of the trees, while the influence of 1–3 year P on LW was reduced to 48%. Thus, under a drier climate ca. 1/3 of the trees within the stand significantly reduced their capacity to utilize deeper ground moisture, indicating higher vulnerability to drought stress. Multiple-year P appeared as the main climatic driver for growth in most trees, but only became evident through age detrending methods retaining low frequency growth variability. Our findings are the first to provide such insight into the wide spectrum of climatic factors that may drive P. laricio’s inter-stand and inter-annual productivity. They also assist to identify the most vulnerable trees to drought stress within a forest stand. Such information could prove very useful in the application of silvicultural treatments (e.g., selective thinning) aiming to increase the resilience of tree stands to future drought intensification.

Time lag and negative responses of forest greenness and tree growth to warming over circumboreal forests.

The terrestrial forest ecosystems in the northern high latitude region have been experiencing significant warming rates over several decades. These forests are considered crucial to the climate system and global carbon cycle and are particularly vulnerable to climate change. To obtain an improved estimate of the response of vegetation activity, e.g., forest greenness and tree growth, to climate change, we investigated spatiotemporal variations in two independent data sets containing the dendroecological information for this region over the past 30years. These indices are the normalized difference vegetation index (NDVI3g) and the tree-ring width index (RWI), both of which showed significant spatial variability in past trends and responses to climate changes. These trends and responses to climate change differed significantly in the ecosystems of the circumarctic (latitude higher than 67°N) and the circumboreal forests (latitude higher and lower than 50°N and 67°N, respectively), but the way in which they differed was relatively similar in theNDVI3g and the RWI. In the circumarctic ecosystem, the climate variables of the current summer were the main climatic drivers for the positive response to the increase in temperatures showed by both the NDVI3g and the RWI indices. On the other hand, in the circumboreal forest ecosystem, the climate variables of the previous year (from summer to winter) were also important climatic drivers for both the NDVI3g and the RWI. Importantly, both indices showed that the temperatures in the previous year negatively affected the ecosystem. Although such negative responses to warming did not necessarily lead to a past negative linear trend in the NDVI3g and the RWI over the past 30years, future climate warming could potentially cause severe reduction in forest greenness and tree growth in the circumboreal forest ecosystem.

Climate signals in a multispecies tree-ring network from central and southern Italy and reconstruction of the late summer temperatures since the early 1700s

Abstract. A first assessment of the main climatic drivers that modulate the tree-ring width (RW) and maximum latewood density (MXD) along the Italian Peninsula and northeastern Sicily was performed using 27 forest sites, which include conifers (RW and MXD) and broadleaves (only RW). Tree-ring data were compared using the correlation analysis of the monthly and seasonal variables of temperature, precipitation and standardized precipitation index (SPI, used to characterize meteorological droughts) against each species-specific site chronology and against the highly sensitive to climate (HSTC) chronologies (based on selected indexed individual series). We find that climate signals in conifer MXD are stronger and more stable over time than those in conifer and broadleaf RW. In particular, conifer MXD variability is directly influenced by the late summer (August, September) temperature and is inversely influenced by the summer precipitation and droughts (SPI at a timescale of 3 months). The MXD sensitivity to August–September (AS) temperature and to summer drought is mainly driven by the latitudinal gradient of summer precipitation amounts, with sites in the northern Apennines showing stronger climate signals than sites in the south. Conifer RW is influenced by the temperature and drought of the previous summer, whereas broadleaf RW is more influenced by summer precipitation and drought of the current growing season. The reconstruction of the late summer temperatures for the Italian Peninsula for the past 300 years, based on the HSTC chronology of conifer MXD, shows a stable model performance that underlines periods of climatic cooling (and likely also wetter conditions) in 1699, 1740, 1814, 1914 and 1938, and follows well the variability of the instrumental record and of other tree-ring-based reconstructions in the region. Considering a 20-year low-pass-filtered series, the reconstructed temperature record consistently deviates < 1 °C from the instrumental record. This divergence may also be due to the precipitation patterns and drought stresses that influence the tree-ring MXD at our study sites. The reconstructed late summer temperature variability is also linked to summer drought conditions and it is valid for the west–east oriented region including Sardinia, Sicily, the Italian Peninsula and the western Balkan area along the Adriatic coast.

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world's largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960-2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960-2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982-2014. No significant changes in SOS or EOS were observed during 1960-1981. April-June and August-September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April-June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale.

Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr−1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr−1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.

Spatiotemporal variation of watershed health propensity through reliability-resilience-vulnerability based drought index (case study: Shazand Watershed in Iran)

Quantitative response of the watershed health to climate variability is of critical importance for watershed managers. However, existing studies seldom considered the impact of climate variability on watershed health. The present study therefore aimed to analyze the temporal and spatial variability of reliability (Rel), resilience (Res) and vulnerability (Vul) indicators in node years of 1986, 1998, 2008 and 2014 in connection with Standardized Precipitation Index (SPI) for 24 sub-watersheds in the Shazand Watershed of Markazi Province in Iran. The analysis was based on rainfall variability as one of the main climatic drivers. To achieve the study purposes, the monthly rainfall time series of eight rain gauge stations distributed across the watershed or neighboring areas were analyzed and corresponding SPIs and Rel ResVul indicators were calculated. Ultimately, the spatial variation of SPI oriented Rel ResVul was mapped for the study watershed using Geographic Information System (GIS). The average and standard deviation of SPI-Rel ResVul index for the study years of 1986, 1998, 2008 and 2014 was obtained 0.240±0.025, 0.290±0.036, 0.077±0.0280 and 0.241±0.081, respectively. In overall, the results of the study proved the spatiotemporal variations of SPI-Rel ResVul watershed health index in the study area. Accordingly, all the sub-watersheds of the Shazand Watershed were grouped in unhealthy and very unhealthy conditions in all the study years. For 1986 and 1998 all the sub-watersheds were assessed in unhealthy status. Whilst, it declined to very unhealthy condition in 2008 and then some 75% of the watershed ultimately referred again to unhealthy and the rest still remained under very unhealthy conditions in 2014.

Proposed long-term monitoring protocol and applications for Aloidendron dichotomum populations

The iconic succulent tree, Aloidendron dichotomum, is found throughout the arid and semi-arid parts of South Africa and Namibia. It has been suggested as a climate change indicator species with long-term monitoring of populations initiated by various institutions in order to improve understanding of its population dynamics and main climate drivers. This proposed monitoring protocol attempts to combine various methodologies already used in order to standardise on field data collection procedures. In order to illustrate the value of the data collected this paper compares baseline demographic data recorded for 12 populations across the Northern Cape (South Africa).Live and dead tree densities were highly variable across populations. Size class distribution (SCD) analysis using height classes and basal diameter classes resulted in different population curve types depending on the variable plotted emphasising the importance of variable choice.Comparison of the midpoint of the basal diameter classes and the natural logarithm of density of individuals per class indicated different linear regression slopes for the Kokerboomkloof population and eight other populations and in one instance, the Kokerboomkloof intercept value differed. In all populations, the calculated centroid value was smaller than the median indicating growing populations.The low occurrence of leaf fungi and scale as well as damage to leaves and stems, indicate that populations are generally healthy with regard to pests and disease. Percentage live and dead heads, dead canopy and dead trunks for surveyed trees were highly variable across populations.At present, the 12 surveyed South African A. dichotomum populations appear to be in good health and are recruiting. Our study highlights that the choice of population surveyed is of importance and that a wide range of populations in close proximity to one another and at different sites situated far apart have to be surveyed in order to produce an unbiased assessment of populations.

Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation response to climate change.

Trends and Variability in Droughts in the Pacific Islands and Northeast Australia

AbstractDrought is a recurrent climate feature of the Pacific Islands and northeast Australia with meteorological and socioeconomic impacts documented from early European settlement. In this study, precipitation records for 21 countries and territories in the Pacific for the period 1951 to 2010 have been examined to identify trends in drought occurrence, duration, and magnitude. The strength of the relationships between the main climate drivers in the Pacific—El Niño–Southern Oscillation (ENSO), the interdecadal Pacific oscillation (IPO), and the Pacific decadal oscillation (PDO)—and precipitation has been also examined. Station-scale drought trends are largely positive, but the majority are statistically nonsignificant with the significant trends mainly in the subtropics. Spatially, trend patterns are largely heterogeneous. A significant relationship between the oceanic component of ENSO and precipitation is confirmed for a large part of the Pacific Islands and eastern Australia with a strong lagged relationship in the year after the El Niño onset at locations southwest of the South Pacific convergence zone (SPCZ) and north of the intertropical convergence zone (ITCZ). Similarly, a strong relationship was found with the IPO and PDO at most locations. Drought was found to be longer and more severe southwest of the SPCZ and north of the ITCZ during the positive phases of the IPO and PDO.

Reconstructing a millennial‐scale record of flooding in a single valley setting: the 2011 flood‐affected Lockyer Valley, south‐east Queensland, Australia

ABSTRACTThis paper reconstructs past flooding from a range of settings in Lockyer Creek, a key tributary of the mid‐Brisbane River, which experienced extreme flood events in AD 2011 and AD 2013. Optically stimulated luminescence samples (n = 110) were collected from alluvial material preserved in within‐channel benches and floodplains. Age distributions from material in the bedrock reaches confirm an event ∼ 300 years ago which stripped the valley alluvium to bedrock. In the unconfined reaches floodplain deposits indicate lateral stability over the past 6000 years. Marked differences in the inundation patterns of the AD 2011 event highlighted changes in downstream channel geometry. The age distribution of alluvium in reaches not inundated during AD 2011 was older, ∼12 000 years, with no preserved evidence of deposition during the past 1000 years. A relatively continuous record of floodplain deposition in reaches which were inundated in AD 2011 identifies a major peak in flood activity also around 300 years ago (∼AD 1730) with five additional peaks occurring at approximately AD 1962, AD 1897, AD 1300, AD 550 and 5400 BC. The main climatic driver of changes in flooding over this timescale is oscillations in El Niño Southern Oscillation and although proxy records are scarce for this region, some correlations with high‐resolution records of rainfall variability are apparent.

Climate reconstruction for the last two millennia in central Iberia: The role of East Atlantic (EA), North Atlantic Oscillation (NAO) and their interplay over the Iberian Peninsula

Abstract A multi-proxy characterization of the uppermost sedimentary infill of an Iberian alpine lake (Cimera, 2140 m a.s.l.) was performed to establish the climatic and environmental conditions for the Iberian Central Range (ICR) over the last two millennia. This multi-proxy characterization was used to reconstruct the intense runoff events, lake productivity and soil erosion in the lake catchment and interpret these factors in terms of temperature and precipitation variability. The Roman Period (RP; 200 BCE – 500 CE) beginning was characterized by an alternation between cold and warm periods as indicated by short-lived oscillations of intense runoff conditions and soil erosion, although warm conditions dominated the end of the period and the Early Middle Age (EMA; 500–900 CE) onset in the ICR. A noticeable decrease in intense runoff events and a progressive decrease in soil erosion during the late EMA indicated a shift to colder temperatures. In terms of precipitation, both the RP and EMA climate periods displayed a transition from dry to wet conditions that led to a decrease in lake productivity. The Medieval Climate Anomaly (MCA; 900–1300 CE) was characterized by warm and dry conditions with frequent intense runoff episodes and increases in lake productivity and soil erosion, whereas the Little Ice Age (LIA; 1300–1850 CE) showed the opposite characteristics. The Industrial Era (1850–2012 CE) presented an increase in lake productivity that likely demonstrates the influence of global warming. The spatio-temporal integration of the Cimera record with other Iberian reconstructions has been used to identify the main climate drivers over this region. During the RP and EMA, N–S and E–W humidity gradients were dominant, whereas during the MCA and LIA, these gradients were not evident. These differences could be ascribed to interactions between the North Atlantic Oscillation (NAO) and East Atlantic (EA) phases. During the RP, the general warm conditions and the E–W humidity gradient indicate a dominant interplay between a negative NAO phase and a positive EA phase (NAO−–EA+), whereas the opposite conditions during the EMA indicate a NAO+–EA− interaction. The dominant warm and arid conditions during the MCA and the cold and wet conditions during the LIA indicate the interplay of the NAO+–EA+ and NAO−–EA−, respectively. Furthermore, the higher solar irradiance during the RP and MCA may support the predominance of the EA+ phase, whereas the opposite scenario during the EMA and LIA may support the predominance of the EA− phase, which would favour the occurrence of frequent and persistent blocking events in the Atlantic region during these periods.

Floodplain forests of the Iberian Peninsula: Vegetation classification and climatic features

AbstractAimsTo produce a formalized classification of floodplain forests in the Iberian Peninsula and to assess their main bioclimatic gradients.LocationIberian Peninsula.MethodsA data set with more than 3000 vegetation plots of floodplain forests was compiled from vegetation‐plot databases, while climatic data were derived from a digital climatic atlas. After filtering of plots according to their area and geographic stratification, 1892 plots were used to build a typology from association to order level using multivariate classification methods (Fuzzy C‐means, agglomerative hierarchical clustering). The phi fidelity index was used to determine the diagnostic species of the syntaxa in the proposed classification. Main climatic gradients were explored using non‐metric multidimensional gradient analysis, and ANOVA was carried out in order to define the bioclimatic features of Iberian floodplain forests.ResultsA total of 41 floodplain forest associations were distinguished for the Iberian Peninsula, grouped in nine suballiances, four alliances and two orders. Mediterraneity (summer aridity) was the main climatic driver, as it separates the temperate floodplain forests of the order Alno‐Fraxinetalia from the Mediterranean forests of the Populetalia albae. Continentality and precipitation were mainly relevant at alliance level, as they separated both the temperate alliances Alnion and Hyperico‐Alnion, the latter more oceanic, and the Mediterranean alliances Populion and Osmundo‐Alnion, the latter from more rainy areas. Temperature was an important driver at association level, as the associations included in the same suballiance or alliance differed regarding their thermicity index.ConclusionsOur study develops the first formalized classification of Iberian floodplain forests and provides their bioclimatic diagnosis. One new alliance, Hyperico‐Alnion, is proposed for floodplain forests of the Cantabrian watershed. Mediterraneity, continentality and precipitation drive floodplain forest diversity at broad scale, while temperature is the main bioclimatic driver at fine scale. The proposed classification provides the scientific basis for the conservation of this habitat type, with high conservation priority, in southern Europe.

Climatic and anthropogenic factors driving water quality variability in a shallow coastal lagoon (Aveiro lagoon, Portugal): 1985–2010 data analysis

Understanding the natural variability of coastal ecosystems, and in particular distinguishing between the natural fluctuations and the ones that are caused by anthropogenic interventions and long-term climatic variability, is a major concern for establishing adequate management and adaptation strategies. The Aveiro lagoon, a shallow coastal lagoon (Portugal), holds one of the largest saltmarshes and saltpans in Europe and is a very important ecosystem from both economic and ecological viewpoints, making the protection of its water masses a requirement. To better understand the variability of its ecosystem, the factors controlling seasonal, inter-annual and long-term variability of the water quality in the Aveiro lagoon were thus analyzed. The statistical analysis was based on a set of climatic, hydrological and water quality observations undertaken between 1985 and 2010. Seasonal variations were mostly related with the seasonal variation of the main climatic and hydrological drivers, while long-term shifts were typically driven by the anthropogenic interventions in the lagoon. After the adoption of secondary treatment for industrial effluents on 1992, a recovery from hypoxia conditions occurred in the upstream area of the lagoon. After 2000 lower concentrations of silicates occurred downstream, and may also derive from some anthropogenic modifications (e.g., shunting of river water to the sewage system, deepening of the inlet) that may have affected the physical dynamics. In the downstream area of the lagoon, chlorophyll a presented a downward trend between 1985 and 2010 and lower concentrations after 2000, which were probably associated with the lower concentrations of silicates. Results from the data analysis showed that the seasonal, inter-annual and long-term trends observed in the Aveiro lagoon depend on the influence of both anthropogenic and climate drivers, putting in evidence the need to combine these different drivers when evaluating and developing management strategies for estuarine ecosystems.

Does slope exposure affect frost ring formation in <i>Picea obovata</i> growing at treeline in the Southern Urals?

Topographic complexity in mountainous ecosystems strongly influences plant growth and as such also wood formation. This wood formation can possibly be used to understand topographic variation of the main climatic drivers, e.g. by modulating frost events. Here we test the influence of different slope exposures on the spatio-temporal distribution of frost rings in Siberian spruce (Ledeb.) in the Southern Urals, Russia. We sampled on two opposite slopes, northeast (NE) and southwest (SW), on three elevation levels from the highest single trees to closed canopy forest and analysed frost ring occurrence and their seasonal timing. Frost ring formation at all exposure-elevation combinations was common and mainly concentrated in the early part of the growing season. The age until trees record frost rings was equally similar (until about 35 years) on both slopes and different elevational levels with the exception of the climatically harshest site, the highest elevation on the NE slope. While we could not deduce a direct, easily identifiable climatic driver for the formation of frost rings, our analysis shows high potential to disentangle the complex interplay between climate, site condition and tree growth in mountainous ecosystems.Picea obovata

Classification and multivariate analysis of differences in gross primary production at different elevations using biome-bgc in the páramos, ecuadorian andean region

Gross primary production (GPP) in climate change studies with multi- species and elevation variables are difficult to measure and simulate. Models tend to provide a representation of dynamic process through long-term analysis by using generalized parameterizations. Even, current approaches of modelling do not contemplate easily the variation of GPP at different elevations for different vegetation types in regions like páramos, mainly due to data unavailability. In these models information from cells is commonly averaged, and therefore average elevation, ecophysiology of vegetation, as well as other parameters is generalized. The vegetation model BIOME- BGC was applied to the Ecuadorian Andean region for elevations greater than 4000 masl with the presence of typical vegetation of páramo for 10 years of simulation (period 2000-2009). An estimation of the difference of GPP obtained using a generalized altitude and predominant type of vegetation could lead to a better estimation of the uncertainty in the magnitude of the errors in global climate models. This research explores GPP from 3 different altitudes and 3 vegetation types against 2 main climate drivers (Short Wave Radiation and Vapor Pressure Deficit). Since it is important to measure the possible errors or difference in the use of averaged meteorological and ecophysiological data, here we present a multivariate analysis of the dynamic difference of GPP in time, relative to an altitude and type of vegetation. A copula multivariable model allows us to identify and classify the changes in GPP per type of vegetation and altitude. The Frank copula model of joint distributions was our best fit between GPP and climate drivers and it allowed us to understand better the dependency of the variables. These results can explore extreme situations where averaged simplified approaches could mislead. The change of GPP over time is essential for future climate scenarios of the ecosystem storage and release of carbon to the atmosphere. Our findings suggest that a classification of the difference is highly important to be extended to cells that have similar properties.

Investigating natural drivers of vegetation coverage variation using MODIS imagery in Qinghai, China

The climatically sensitive Qinghai province of China has been recognized as a hotspot for studies on the feedbacks of terrestrial ecosystems to global climate change. Thus, investigating vegetation coverage and its natural drivers in Qinghai is an important focus of ecosystem research. On the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series data, we estimated the vegetation coverage in this region using the dimidiate pixel model. Trend analyses, correlations between meteorological parameters, changes in vegetation coverage, and the temporal and spatial relationships between soil texture and vegetation coverage were used to investigate the possible drivers of vegetation coverage variations. The results indicated that the reduction of vegetation coverage slowed down in the period from 2000 to 2012. Annual mean temperature was the main climatic driver of the total extremely low and low vegetation coverage areas in Qinghai, followed by the precipitation anomalies. The extremely low and low vegetation coverage areas were mainly distributed in regions with a mean annual relative air humidity of <40% and the spatial distributions of these two area types differentiated along the 200-mm rainfall contours. The total extremely low and low vegetation coverage areas were mainly characterized by sandy clay loam soil, followed by loamy sand and sandy soil. Regions with sandy loam or loam soil have the greatest risk of vegetation coverage reductions. Knowledge of vegetation coverage variation and its natural drivers in the ecologically fragile region of Qinghai can provide scientific support for managing environmental change and desertification.

Long tree-ring chronologies provide evidence of recent tree growth decrease in a Central African tropical forest.

It is still unclear whether the exponential rise of atmospheric CO2 concentration has produced a fertilization effect on tropical forests, thus incrementing their growth rate, in the last two centuries. As many factors affect tree growth patterns, short -term studies might be influenced by the confounding effect of several interacting environmental variables on plant growth. Long-term analyses of tree growth can elucidate long-term trends of plant growth response to dominant drivers. The study of annual rings, applied to long tree-ring chronologies in tropical forest trees enables such analysis. Long-term tree-ring chronologies of three widespread African species were measured in Central Africa to analyze the growth of trees over the last two centuries. Growth trends were correlated to changes in global atmospheric CO2 concentration and local variations in the main climatic drivers, temperature and rainfall. Our results provided no evidence for a fertilization effect of CO2 on tree growth. On the contrary, an overall growth decline was observed for all three species in the last century, which appears to be significantly correlated to the increase in local temperature. These findings provide additional support to the global observations of a slowing down of C sequestration in the trunks of forest trees in recent decades. Data indicate that the CO2 increase alone has not been sufficient to obtain a tree growth increase in tropical trees. The effect of other changing environmental factors, like temperature, may have overridden the fertilization effect of CO2.

Evapotranspiration deficit controls net primary production and growth of silver fir: Implications for Circum-Mediterranean forests under forecasted warmer and drier conditions

Warming-induced drought stress has been hypothesized as a major driver of forest net primary production (NPP) reduction, but we lack reliable field data to assess if higher temperatures lead to forest NPP reduction, particularly in humid sites and at basin to landscape spatial scales. The use of a landscape approach would allow considering the feedbacks operating between climate, topography, soil vegetation and water resources. Here we follow that approach by simulating NPP using the regional hydro-ecologic simulation system (RHESSys) model and by comparing the results with radial growth data (tree-ring widths and intrinsic water-use efficiency – iWUE). We evaluate the relationships between climate, growth, NPP, atmospheric CO2 concentrations (ca) and iWUE in xeric and mesic silver fir forests subjected to contrasting water balances. The growth data successfully validated the 11-month NPP cumulated until spring. The main negative climatic driver of growth and NPP was the summer evapotranspiration deficit, which shows a negative association with tree-ring width indices. Sensitivity analyses indicate that rising ca do not compensate the severe NPP reduction associated to warmer and drier conditions. The positive effect of rising ca on NPP is mediated by climatic site conditions being detected only in mesic sites, whereas the negative effects of drought on NPP override any ca-related enhancement of NPP in xeric sites. Future warmer and drier conditions causing a higher evaporative demand by the atmosphere could lead to a NPP decline in temperate conifer forests subjected to episodic droughts.

The change of climate and terrestrial carbon cycle over Tibetan Plateau in CMIP5 models

ABSTRACTSix earth system models from phase 5 of the Coupled Model Inter‐comparison Project (CMIP5) are evaluated over Tibetan Plateau (TP) by comparing the modelled temperature (Tas), precipitation (Pr), net primary production (NPP) and leaf area index (LAI) with the observed Tas, Pr, International Geosphere Biosphere Program (IGBP) NPP and Max–Planck Institute for Meteorology (MPIM) LAI in the historical, and then we analysed the change of climate and carbon cycle and explored the relationship between the carbon cycle and main climatic drivers in the historical and representative concentration pathway 4.5 (RCP4.5) simulation over TP. While model results differ, their region spatial distributions from 1971 to 2000 agree reasonably with observed Tas, Pr and proxy LAI and NPP. The climatic variables, LAI and carbon flux vary between two simulations, the ration of NPP to gross primary production (GPP) does not change much in the historical and RCP4.5 scenarios. The linear trends of LAI and carbon flux show an obvious continuous increase from historical climatic period (1971–2000) to the first two climatic periods (2011–2040; 2041–2700) of RCP4.5, then the trends decrease in the third climatic period (2071–2100) of RCP4.5. The cumulative multi‐model ensemble (MME) net biome production (NBP) is 0.32 kg C m−2 year−1 during 1850–2005 and 1.43 kg C m−2 year−1 during 2006–2100, the TP is a carbon sink during the historical scenario, and TP will uptake more carbon from atmosphere during 2006–2100 than 1850–2005 under RCP4.5 scenario. LAI, GPP, NPP, Ra and Rh appear more related to the Tas than Pr and Rsds, and the Tas is the primary climatic driver for the plant growth and carbon cycle. With the climate change in 21st century under RCP4.5 scenario, Tas still is the primary climate driver for the plant growth and carbon cycle, but the effect of temperature on plant growth and carbon cycle gets weaker.