Assessing the spatial variability in peak season CO2exchange characteristics across the Arctic tundra using a light response curve parameterization
Mbufong, H.N. ; Lund, M. ; Aurela, M. ; Molen, M.K. van der - \ 2014
Biogeosciences 11 (2014)17. - ISSN 1726-4170 - p. 4897 - 4912.
carbon-dioxide exchange - net ecosystem exchange - photosynthetically active radiation - growing-season - thermal-acclimation - vascular plants - tussock tundra - climate-change - energy flux - alaska
This paper aims to assess the spatial variability in the response of CO2exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64-74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE-irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (a), (d) NEE when light is at 1000 µmol m-2s-1(Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000and Psat, thus illustrating the potential for upscaling CO2exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.
Effects of climate variability and climate change on crop production in southern Mali
Traore, B. ; Corbeels, M. ; Wijk, M.T. van; Rufino, M.C. ; Giller, K.E. - \ 2013
European Journal of Agronomy 49 (2013). - ISSN 1161-0301 - p. 115 - 125.
west-africa - rainy-season - northern nigeria - semiarid tropics - growing-season - wheat yield - rainfall - onset - temperature - growth
In West Africa predictions of future changes in climate and especially rainfall are highly uncertain, and up to now no long-term analyses are available of the effects of climate on crop production. This study analyses long-term trends in climate variability at N'Tarla and Sikasso in southern Mali using a weather dataset from 1965 to 2005. Climatic variables and crop productivity were analysed using data from an experiment conducted from 1965 to 1993 at N'Tarla and from a crop yield database from ten cotton growing districts of southern Mali. Minimum daily air temperature increased on average by 0.05 degrees C per year during the period from 1965 to 2005 while maximum daily air temperature remained constant. Seasonal rainfall showed large inter-annual variability with no significant change over the 1965-2005 period. However, the total number of dry days within the growing season increased significantly at N'Tarla, indicating a change in rainfall distribution. Yields of cotton, sorghum and groundnut at the NTarla experiment varied (30%) without any clear trend over the years. There was a negative effect of maximum temperature, number of dry days and total seasonal rainfall on cotton yield. The variation in cotton yields was related to the rainfall distribution within the, rainfall season, with dry spells and seasonal dry days being key determinants of crop yield. In the driest districts, maize yields were positively correlated with rainfall. Our study shows that cotton production in southern Mali is affected by climate change, in particular through changes in the rainfall distribution. (C) 2013 Elsevier B.V. All rights reserved.
Quantitative mapping of global land degradation using Earth observations
Jong, R. de; Bruin, S. de; Schaepman, M.E. ; Dent, D. - \ 2011
International Journal of Remote Sensing 32 (2011)21. - ISSN 0143-1161 - p. 6823 - 6853.
net primary production - time-series analysis - terrestrial primary production - difference vegetation index - noaa-avhrr data - spot-vegetation - ndvi data - interannual variability - growing-season - south-africa
Land degradation is a global issue on par with climate change and loss of biodiversity, but its extent and severity are only roughly known and there is little detail on the immediate processes – let alone the drivers. Earth-observation methods enable monitoring of land degradation in a consistent, physical way and on a global scale by making use of vegetation productivity and/or loss as proxies. Most recent studies indicate a general greening trend, but improved data sets and analysis also show a combination of greening and browning trends. Statistically based linear trends average out these effects. Improved understanding may be expected from data-driven and process-modelling approaches: new models, model integration, enhanced statistical analysis and modern sensor imagery at medium spatial resolution should substantially improve the assessment of global land degradation
Analysis of monotonic greening and browning trends from global NDVI time-series
Jong, R. de; Bruin, S. de; Wit, A.J.W. de; Schaepman, M.E. ; Dent, D.L. - \ 2011
Remote Sensing of Environment 115 (2011)2. - ISSN 0034-4257 - p. 692 - 702.
avhrr vegetation index - land degradation - spot-vegetation - growing-season - photosynthetic trends - primary productivity - deciduous forest - plant phenology - carbon-dioxide - high-latitudes
Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.
Carbon exchange of a maize (Zea mays L.) crop: Influence of phenology
Jans, W.W.P. ; Jacobs, C.M.J. ; Kruijt, B. ; Elbers, J.A. ; Barendse, S.C.A. ; Moors, E.J. - \ 2010
Agriculture, Ecosystems and Environment 139 (2010)3. - ISSN 0167-8809 - p. 316 - 324.
netto ecosysteem uitwisseling - koolstofvastlegging - fenologie - rogge - maïs - zea mays - organische meststoffen - nederland - net ecosystem exchange - carbon sequestration - phenology - rye - maize - zea mays - organic fertilizers - netherlands - gross primary production - rain-fed maize - ecosystem respiration - dioxide exchange - eddy covariance - soil respiration - growing-season - use efficiency - united-states - phase-change
A study was carried out to quantify the carbon budget of a maize (Zea mays L.) crop followed by a rye cover crop in the Netherlands, and to determine the importance of the phenological phases and the fallow phase when modelling the carbon budget. Measurements were made of carbon fluxes, soil respiration, biomass and Plant Area Index (PAI). On the basis of PAI the annual cycle was subdivided into 5 phases: juvenile-vegetative, adult-vegetative, reproductive, senescence and fallow. To model the annual carbon budget, it should be sufficient to assess the light response in the juvenile-vegetative phase, the growing season and the fallow phase, combined with the length of these phases and the PAI development. We conclude that emphasis should be put on determining off-season fluxes while the growing season can be estimated from radiation only. During the cultivation period (from sowing to harvest) 5.97 tC ha−1 was sequestered by the maize crop. The amount of carbon exported from the field was 7.5 tC ha−1, and the estimated amount of carbon imported by organic fertilizer was 0.51 tC ha−1, resulting in a carbon loss of 1.02 tC ha−1 from the soil. The fallow phase, with a rye cover crop at the field, decreased the amount of carbon fixed in the cultivation period by 2.65 tC ha−1 (44% reduction). To enable determination of the carbon sequestration or emission of croplands, farmers should be required to analyze, apart from the nitrogen content, also the carbon content of organic fertilizers.
A study was carried out to quantify the carbon budget of a maize (Zea mays L) crop followed by a rye cover crop in the Netherlands, and to determine the importance of the phenological phases and the fallow phase when modelling the carbon budget. Measurements were made of carbon fluxes, soil respiration, biomass and Plant Area Index (PAI). On the basis of PAI the annual cycle was subdivided into 5 phases: juvenile-vegetative, adult-vegetative, reproductive, senescence and fallow. To model the annual carbon budget, it should be sufficient to assess the light response in the juvenile-vegetative phase, the growing season and the fallow phase, combined with the length of these phases and the PAI development. We conclude that emphasis should be put on determining off-season fluxes while the growing season can be estimated from radiation only. During the cultivation period (from sowing to harvest) 5.97 tC ha(-1) was sequestered by the maize crop. The amount of carbon exported from the field was 7.5 tC ha(-1), and the estimated amount of carbon imported by organic fertilizer was 0.51 tC ha(-1), resulting in a carbon loss of 1.02 tC ha(-1) from the soil. The fallow phase, with a rye cover crop at the field, decreased the amount of carbon fixed in the cultivation period by 2.65 tC ha(-1) (44% reduction). To enable determination of the carbon sequestration or emission of croplands, farmers should be required to analyze, apart from the nitrogen content, also the carbon content of organic fertilizers. (C) 2010 Elsevier B.V. All rights reserved.
Spatial variation in growth, condition and maturation reaction norms of the Baltic herring Clupea harengus membras
Vainikka, A. ; Mollet, F.M. ; Casini, M. ; Gardmark, A. - \ 2009
Marine Ecology Progress Series 383 (2009). - ISSN 0171-8630 - p. 285 - 294.
marine fish - countergradient variation - pumpkinseed sunfish - sprattus-sprattus - growing-season - rapid growth - north-sea - atlantic - age - size
Understanding of spatial patterns in life-history traits can help fisheries management focus on biologically and functionally relevant stock units. In the present study, we examined life-history variation in growth, condition and maturation of the Baltic herring Clupea harengus membras among different areas of the Baltic Sea. As expected based on environmental gradients, herring grew faster in southern than in northern areas. The condition factor for young individuals was higher in the north, but higher for older individuals in the south. Probabilistic maturation reaction norms (PMRNs) based on age, length and condition indicated counter-gradient variation: young herring in the northern areas reached the size at which they had a 50% probability of maturing when they were comparatively smaller than the southern specimens. However, the north-south differences in PMRNs were reversed in older age groups. This indicated that maturation of herring in the north was more size dependent (zero PMRN slope) than it was for herring in the south, where maturation was predominantly determined by age (negative PMRN slope). The geographical differentiation in maturation schedules would potentially translated into divergent changes in recruitment in response to changes in density-dependent growth and, hence, also fishing patterns.
A ground-validated NDVI dataset for monitoring vegetation dynamics and mapping phenology in Fennoscandia and the Kola peninsula
Beck, P.S.A. ; Jonsson, P. ; Hogda, K.A. ; Karlsen, S.R. ; Skidmore, A.K. ; Eklundh, L. - \ 2007
International Journal of Remote Sensing 28 (2007)19. - ISSN 0143-1161 - p. 4311 - 4330.
satellite sensor data - time-series - data set - surface phenology - species richness - plant phenology - growing-season - climate - responses - index
An NDVI dataset covering Fennoscandia and the Kola peninsula was created for vegetation and climate studies, using Moderate Resolution Imaging Spectroradiometer 16-day maximum value composite data from 2000 to 2005. To create the dataset, (1) the influence of the polar night and snow on the NDVI values was removed by replacing NDVI values in winter with a pixel-specific NDVI value representing the NDVI outside the growing season when the pixel is free of snow; and (2) yearly NDVI time series were modelled for each pixel using a double logistic function defined by six parameters. Estimates of the onset of spring and the end of autumn were then mapped using the modelled dataset and compared with ground observations of the onset of leafing and the end of leaf fall in birch, respectively. Missing and poor-quality data prevented estimates from being produced for all pixels in the study area. Applying a 5 km×5 km mean filter increased the number of modelled pixels without decreasing the accuracy of the predictions. The comparison shows good agreement between the modelled and observed dates (root mean square error = 12 days, n = 108 for spring; root mean square error = 10 days, n = 26, for autumn). Fennoscandia shows a range in the onset of spring of more than 2 months within a single year and locally the onset of spring varies with up to one month between years. The end of autumn varies by one and a half months across the region. While continued validation with ground data is needed, this new dataset facilitates the detailed monitoring of vegetation activity in Fennoscandia and the Kola peninsula.
Functional convergence in regulation of net CO2 flux in heterogeneous tundra landscapes in Alaska and Sweden
Shaver, G.R. ; Street, L.E. ; Rastetter, E.B. ; Wijk, M.T. van; Williams, M. - \ 2007
Journal of Ecology 95 (2007)4. - ISSN 0022-0477 - p. 802 - 817.
kuparuk river-basin - leaf-area index - arctic ecosystems - climate-change - primary productivity - species composition - carex-bigelowii - carbon exchange - growing-season - plant biomass
1. Arctic landscapes are characterized by extreme vegetation patchiness, often with sharply defined borders between very different vegetation types. This patchiness makes it difficult to predict landscape-level C balance and its change in response to environment. 2. Here we develop a model of net CO2 flux by arctic landscapes that is independent of vegetation composition, using instead a measure of leaf area derived from NDVI (normalized-difference vegetation index). 3. Using the light response of CO2 flux (net ecosystem exchange, NEE) measured in a wide range of vegetation in arctic Alaska and Sweden, we exercise the model using various data subsets for parameter estimation and tests of predictions. 4. Overall, the model consistently explains similar to 80% of the variance in NEE knowing only the estimated leaf area index (LAI), photosynthetically active photon flux density (PPFD) and air temperature. 5. Model parameters derived from measurements made in one site or vegetation type can be used to predict NEE in other sites or vegetation types with acceptable accuracy and precision. Further improvements in model prediction may come from incorporating an estimate of moss area in addition to LAI, and from using vegetation-specific estimates of LAI. 6. The success of this model at predicting NEE independent of any information on species composition indicates a high level of convergence in canopy structure and function in the arctic landscape.
Interannual variability of plant phenology in tussock tundra: modelling interactions of plant productivity, plant phenology, snowmelt and soil thaw
Wijk, M.T. van; Williams, M. ; Laundre, J.A. ; Shaver, G.R. - \ 2003
Global Change Biology 9 (2003). - ISSN 1354-1013 - p. 743 - 758.
net primary production - climate-change - arctic tundra - carbon-dioxide - atmospheric co2 - growing-season - responses - growth - balance - forest
We present a linked model of plant productivity, plant phenology, snowmelt and soil thaw in order to estimate interannual variability of arctic plant phenology and its effects on plant productivity. The model is tested using 8 years of soil temperature data, and three years of bud break data of Betula nana . Because the factors that trigger the end of the growing season of arctic vegetation are less well known than those of the start of the growing season, three hypotheses were formulated and tested for their effects on productivity and its sensitivity to climate change; the hypothesised factors determining the end of the growing season were frost, photoperiod and periodic constraints. The performance of the soil thermal model was good; both the onset of soil thaw in spring and the initiation of freezing in autumn were predicted correctly in most cases. The phenology model predicted the bud break date of Betula nana closely for the three different years. The soil thaw model predicted similar growing season start dates under current climate as the models based on sum of temperatures, but it made significantly different predictions under climate change scenarios, probably because of the non-linear interactions between snowmelt and soil thaw. The uncertainty about the driving factors for the end of the growing season, in turn, resulted in uncertainty in the interannual variability of the simulated annual gross primary productivity (GPP). The interannual variability ranged from - 25 to + 26% of the mean annual GPP for the frost hypothesis, from - 20 to + 20% for the photoperiod hypothesis and only from - 7 to + 7% for the periodic hypothesis. The different hypotheses also resulted in different sensitivity to climate change, with the frost hypothesis resulting in 30% higher annual GPP values than the periodic hypothesis when air temperatures were increased by 3 degreesC.