Green-up Period Research Articles

Carbon Allocation to Leaves and Its Controlling Factors and Impacts on Gross Primary Productivity in Forest Ecosystems of Northeast China

Carbon allocation in forest ecosystems is essential for the optimization of growth. However, remote-sensing-based research on the estimation of carbon allocation in forests is inadequate. This article considers forests in northeastern China as the research area and uses leaf area index (LAI) data combined with random forest and structural equation modelling methods to study the spatiotemporal distribution characteristics and driving factors of carbon allocation to leaves (ΔLAI) in deciduous broad-leaved forests (DBF), deciduous coniferous forests (DNF), and mixed forests (MF) during the green-up period (GUP) at a monthly scale during April, May, June, and July from 2001 to 2021, and clarifies the impact of leaf carbon allocation on gross primary productivity (GPP). The ΔLAI was the highest in DBF in April and in DNF and MF in May. The ΔLAI in April with an increasing trend year by year in DBF and MF, and the ΔLAI in May with an increasing trend in DNF. Among all the direct and indirect relationships that affect ΔLAI, temperature (TEM) has the highest path coefficient for DBF’s ΔLAI in April (−1.213) and the start of the season (SOS) has the highest path coefficient for DNF (−1.186) and MF (0.815). ΔLAI in the GUP has a significant positive impact on the GPP. In the MF, the higher ΔLAI in May was most conducive to an increase in GPP. During the critical period, that is April and May, carbon allocation to leaves effectively improves the carbon sequestration capacity of forestland. This information is of great value for the development and validation of terrestrial ecosystem models.

An Earlier Spring Phenology Reduces Vegetation Growth Rate during the Green-Up Period in Temperate Forests

Climatic warming advances the start of the growing season (SOS) and sequentially enhances the vegetation productivity of temperate forests by extending the carbon uptake period and/or increasing the growth rate. Recent research indicates that the vegetation growth rate is a main driver for the interannual changes in vegetation carbon uptake; however, the specific effects of an earlier SOS on vegetation growth rate and the underlying mechanisms are still unclear. Using 268 year-site PhenoCam observations in temperate forests, we found that an earlier SOS reduced the vegetation growth rate and mean air temperature during the green-up period (i.e., from the SOS to the peak of the growing period), but increased the accumulation of shortwave radiation during the green-up period. Interestingly, an earlier-SOS-induced reduction in the growth rate was weakened in the highly humid areas (aridity index ≥ 1) when compared with that in the humid areas (aridity index < 1), suggesting that an earlier-SOS-induced reduction in the growth rate in temperate forests may intensify with the ongoing global warming and aridity in the future. The structural equation model analyses indicated that an earlier-SOS-induced decrease in the temperature and increase in shortwave radiation drove a low vegetation growth rate. Our findings highlight that the productivity of temperate forests may be overestimated if the negative effect of an earlier SOS on the vegetation growth rate is ignored.

The role of root zone soil moisture return on vegetation green-up: A comparison of two degrading permafrost sites

The effects of permafrost degradation on ecological changes have attracted more and more attention, but the underlying interactive mechanisms are still not well understood. From a unique angle of view, this study focuses on the linkage between the freezing-induced root zone soil moisture return (SMR) and vegetation green-up along with climate warming and permafrost degradation. Using 7-year soil-weather monitoring data in the high-altitude and high-latitude permafrost regions, we investigated the changes of root zone SMR in two degrading permafrost sites. Results demonstrate that, as one important water source for vegetation green-up, the ratio of root zone SMR to the soil moisture storage after final thawed, Rsmr, could reach 22.8 % and 10.5 % at the two sites, respectively. In contrast to the negligible change at the high-latitude permafrost site, a rapid increase rate of 7.7 % per decade in Rsmr was found at the high-altitude permafrost site over the monitoring period of 2012–2018. Generally, vegetation green-up definitely benefited from the enrichment of soil moisture storage, but their sensitivities to climate warming and permafrost degradation were different at the two sites. The increase of Rsmr effectively buffered the shrinking trend of soil water availability of the root zone both over the pre-freezing and the green-up period at the high-altitude permafrost site. The changing role of root zone SMR might be threatened during the vegetation green-up in the longer future. Whereas, there would be no water shortage risk for the foreseeable future at the high-latitude permafrost site. Overall, this study emphasized the importance of SMR in enhancing soil water availability for vegetation green-up under the background of quick climate warming and permafrost degradation.

An Extended Unit Restriction Model with Environmental Considerations for Forest Harvesting

This paper addresses a forest harvesting problem with adjacency constraints, including additional environmental constraints to protect wildlife habitats and minimize infrastructure deployment costs. To this end, we propose an integer programming model to include those considerations during the optimization of the harvest regime of a Mexican forest. The model considered was based on the Unit Restriction Model, a benchmark approach that merges the management units before the optimization process. The resulting model, namely the Green Unit Restriction Model (GURM) and the benchmark model (URM) from the literature were tested with the forest Las Bayas, using information obtained from the SiPlaFor project from Universidad Juárez. The proposed model was solvable in all tested instances. Furthermore, a sensitivity analysis study over a core data set of test instances was carried out on the different parameters of the GURM model to determine optimal configurations for the specific case study. Several environmental measures were assessed in our experimental work. The parameters evaluated were the distance value between pairs of units harvested in the same period, the distance value between those considered natural reserve units, the timber volume to be harvested, the green-up period, and the minimum forest reserve area. An interesting observation from the experiments was that the maximum area inversely affected the URM and GURM models; larger regions resulted in a reduced number of management units in the URM model, thus reducing the computational time to solve the instance of the problem, but in this case, at the expense of a reduced profit. One of the interesting findings was that, in all experiments under all different factors, harvesting every 5 or 6 years yields better profits than harvesting every 10 or 12 years. The current standard in the Mexican system is to harvest every 10 years.

The weakening of the interannual relationship between the rate of vegetation spring green-up and temperature related to warmer and drier preseason over the northern extratropics

Changes in the rate of spring green-up (RSP) caused by climate change can alter biosphere-atmosphere exchange of carbon, energy, and water cycles. Although the response of RSP to environmental conditions has been frequently discussed, little is known about the dynamic relationship between RSP and environmental variables over time. We investigated the interannual relationships between RSP and various environmental variables using the Ensemble Empirical Mode Decomposition (EEMD) detrending approach and partial correlation analyses. We then used 15-year moving windows to analyze the effects of accumulated green-up period temperature (AGT) on RSP and its temporal variation from 1982 to 2016.We found that: (1) AGT had a positive influence on RSP in 81.08% of the entire study regions and AGT dominated the interannual variation of RSP in 31.31% all pixels; (2) The percentage of moisture-controlled (vapor pressure deficit (VPD) and soil moisture) pixels was 28.71%, indicating that preseason moisture, especially vapor pressure deficit (negative correlations in 65.50% pixels), played critical roles in limiting RSP; (3) The linkage between RSP and AGT (RRSP–AGT) was significantly weakening over the Northern Extratropics with intensity decrease of −0.0017 year−1 (p < 0.05) and extent reduction of −0.4 × 105 km2 year−1 (p < 0.05), suggesting a decreasing influence of AGT on foliar development. (4) The decline in RRSP–AGT coincided with decreased chilling exposure (CE) and enhanced VPD during the preseason over the Northern Extrotrapics and Eurasia, but it only may be related to changes in VPD in the North America. Our findings highlighted the importance of the dynamic response of vegetation spring green-up to ongoing warming, for a better understanding of the vegetation seasonal cycle under climate change.

Contrasting temperature effects on the velocity of early- versus late-stage vegetation green-up in the Northern Hemisphere.

Global vegetation greening has been widely confirmed in previous studies, yet the changes in the velocity of green-up in each month of green-up period (GUP) remains unclear. Here, we defined the velocity of vegetation green-up as VNDVI (the monthly increase of Normalized Difference Vegetation Index [NDVI] during GUP) and further explored its response to climate change in middle-high-latitude Northern Hemisphere. We found that in early GUP, VNDVI generally showed positive trends from 1982 to 2015, whereas in late GUP, it showed negative trends in most areas. Such contrasting trends were mainly due to a positive temperature effect on VNDVI in early GUP, but this effect turned negative in late GUP. The increase of soil moisture also in part explained the accelerated vegetation green-up, especially in the arid and semi-arid ecosystems of inland areas. Our analyses also indicate that the first month of the GUP was the key stage impacting vegetation greenness in summer. Future warming may continuously speed up the early growth of vegetation, altering the seasonal trajectory of vegetation and its feedbacks to the Earth system.

Grazing during the grassland greenup period promotes plant species richness in alpine grassland in winter pastures.

Although grazing is the most common use of grassland, the ecological function of grassland far exceeds its productivity. Therefore, the protection of plant diversity is of the utmost importance and cannot be ignored. Existing research on the effect of grazing on grassland mainly focuses on grazing intensity and the type of livestock, but the consequences of the timing of the grazing on the vegetation community remains unclear. We investigated plant community characteristics of winter pastures in alpine meadow with different grazing termination times (grazing before and during the grassland greenup periods) in Maqu County, eastern QTP. The results showed that vegetation height, coverage, aboveground biomass and Graminoid biomass were lower in grassland when grazing happened during the greenup period compared to grassland where grazing was terminated before the greenup period. However, the total plant species richness and forbs richness were higher in grassland with grazing during the greenup period compared to grassland without grazing during the greenup period. Our structural equation modeling reveals a potential indirect implication for the total plant species richness and forbs richness of winter pastures mainly through a decrease in the vegetation coverage and grass biomass abundance. Our findings imply that grazing during the grassland greenup period may facilitate the maintenance of plant diversity in winter pastures. These findings have important implications for grassland ecosystem functioning and for the conservation of plant diversity.

Longer greenup periods associated with greater wood volume growth in managed pine stands

Increasing forest productivity is important to meet future demand for forest products, and to improve resilience in the face of climate change. Forest productivity depends on many things, but the timing of leaf development (hereafter: “plant phenology”) is especially important. However, our understanding of how plant phenology affects the productivity of managed forests, and how silviculture may in turn affect phenology, has been limited because of the spatial scale mismatch between phenological data and field experimental observations. In this study, we take advantage of a new 30 m satellite land surface phenology dataset and stand growth measurements from long-term experimental pine plantation sites in the southeastern United States to investigate the question: is stand growth related to remotely sensed phenology metrics? Multiple linear regression and random forest models were fitted to quantify the effect of phenology and silvicultural treatments on stand growth. We found that 1) Greater wood volume growth was associated with longer green up periods; 2) Fertilization elevated EVI2 measurement values during the whole growing season, especially in the winter; 3) Competing vegetation could affect remotely sensed observations and complicates interpretation of remotely sensed phenology metrics.

Nutrients and water availability constrain the seasonality of vegetation activity in a Mediterranean ecosystem.

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPPmax ). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree-grass ecosystem, we established three landscape-level (24ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green-up and dry-down), slopes during green-up and dry-down period, and seasonal amplitude, were extracted from time series of GPPmax and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPPmax was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green-up period. Yet, both fertilized sites senesced earlier during the dry-down period (17-19days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPPmax during the green-up period and a sharper decline in GPPmax during the dry-down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient-water interaction in such water-limited ecosystems. With the projected warming-drying trend, the positive effects of N fertilization induced by N deposition on GPPmax may be counteracted by an earlier and faster dry-down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water-limited ecosystems.

Satellite detection of varying seasonal water supply restrictions on grassland productivity in the Missouri basin, USA

Climate observations indicate more frequent drought in recent years, and model predictions suggest that drought occurrence will continue to rise with global warming. Understanding drought impacts on ecosystem functioning requires accurate quantification of vegetation sensitivity to changes in water supply condition. This is complicated by the seasonal variation in plant structural and physiological response to water stress, especially for semi-arid grasslands with characteristic strong spatial and temporal variability in carbon uptake. Here, we use complementary satellite soil moisture (SM) and total water storage (TWS) observations to delineate plant-accessible water supply variations for natural grasslands in the Missouri basin, USA. We evaluate how water supply influences the spatiotemporal variations in grassland productivity as a function of seasonal timing and climate condition. We identify a 128-day period from mid-June to early October when grassland growth is sensitive to soil moisture changes. We find the strongest SM sensitivity after the peak of the growing season associated with high temperature and VPD. SM limitation can extend to early and late growing season under warm conditions, while grassland sensitivity to SM is generally stronger in the late growth stage than in the green-up period given similar temperature and soil moisture. We find that complementary to the surface SM observations, TWS provides plant-available water storage information from the deeper soil, and both SM and TWS exert a lagged impact on grassland productivity. We find that the lag between the inter-annual variation of SM and associated plant response increases through the season, and overall there is a transition from SM-limitation to TWS-limitation on productivity during the late growing period when the TWS level is near the seasonal low. Future global change projections should account for a seasonally varying vegetation-moisture relationship to accurately assess the impact of the water supply constraint on plant productivity in a warming climate.

Evaluating the utility of various drought indices to monitor meteorological drought in Tropical Dry Forests.

Even though existing remote-sensing-based drought indices are widely used in many different types of ecosystems, their utility has not been widely assessed in tropical dry forests (TDFs). The aim of this study is to evaluate the performance of three remote-sensing-based drought indices, the Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), for meteorological drought monitoring in TDFs using the moderate-resolution imaging spectroradiometer (MODIS) products. The correlation between the VCI, TCI, and VHI and multiple time scales of the Standardized Precipitation Index (SPI) (1, 3, 6, 9, 12, 15, 18, 21, 24months) for each month (January to December) and each season (dry season, dry-to-wet season, wet season and wet-to-dry season) were conducted using the Pearson correlation analysis. We also correlated year-to-year changes of satellite-based drought indices with the changes of the in situ annual SPI (A_SPI) which provides annual information on the mean meteorological drought. The analysis reveals that the ability of these remote-sensing-based drought indices for meteorological drought monitoring varies with timing, and the TCI outperforms the VCI and VHI in terms of seasonal and annual scale. These remote-sensing indices performed well in monitoring meteorological drought in the dry season, poorly in the in the dry-to-wet season, and moderately in the wet season. The TCI performed best in monitoring meteorological drought in the wet-to-dry period, followed by VHI, whereas the VCI performed worst. All of these remote-sensing-based drought indices failed to detect drought in May during the green-up period and in September, October, and November when the water content in the root regions was abundant. Our results indicate that the evapotranspiration of TDFs is more sensitive than canopy greenness to detect meteorological drought. Results from this study increase the ability to provide real-time drought monitoring and early warnings of drought in TDFs.

Study on Soil Respiration Characteristics and Carbon Balance of &amp;lt;i&amp;gt;Kobresia pygmaea&amp;lt;/i&amp;gt; Meadow in Qinghai-Tibet Plateau, China

Although soil respiration is the largest contributor to C flux from terrestrial ecosystems to the atmosphere, our understanding of its characteristics and carbon budget in alpine meadow is rather limited because of extremely geographic situation. This study was designed to examine soil CO2 efflux characteristics of diurnal and seasonal variation, thus obtaining estimates of carbon balance of Kobresia pygmaea meadow in Qinghai-Tibet plateau. The results showed that the soil respiration of diurnal and seasonal rate changed little in growing season and was mainly affected by temperature, and single peak curve that showed afternoon appeared. Composite model which was set by soil respiration rate, soil moisture content and temperature (atmospheric temperature and soil temperature) could explain better the variations of soil respiration rate. The variation range of Q10 ranged from 1.28 to 2.34, which was sensitive to temperature in green-up period and late growth stage, and decreased in growth peak period. Meanwhile, during the growing seasons the observed amount of annual carbon fixation via primary production for Kobresia pygmaea meadow ecosystem was about 120.21 g C·m-2·a-1. The carbon dioxide output via soil heterotrophic respiration was about 37.54 g C·m-2·a-1. So carbon budget had more input than output. The Kobresia pygmaea meadow ecosystem has stronger potential to absorb carbon dioxide, it was a sink of atmospheric CO2, and the plant community had a net carbon gain of 82.67 g C·m-2·a-1.

Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

Acceleration of global vegetation greenup from combined effects of climate change and human land management.

Global warming and human land management have greatly influenced vegetation growth through both changes in spring phenology and photosynthetic primary production. This will presumably impact the velocity of vegetation greenup (Vgreenup, the daily rate of changes in vegetation productivity during greenup period), yet little is currently known about the spatio-temporal patterns of Vgreenup of global vegetation. Here, we define Vgreenup as the ratio of the amplitude of greenup (Agreenup) to the duration of greenup (Dgreenup) and derive global Vgreenup from 34-year satellite leaf area index (LAI) observations to study spatio-temporal dynamics of Vgreenup at the global, hemispheric, and ecosystem scales. We find that 19.9% of the pixels analyzed (n=1,175,453) experienced significant trends toward higher greenup rates by an average of 0.018m2 m-2 day-1 for 1982-2015 as compared to 8.6% of pixels with significant negative trends (p<0.05). Global distribution and dynamics of Vgreenup show high spatial heterogeneity and ecosystem-specific patterns, which is primarily determined by the high spatial variation in Agreenup, while the temporal dynamics of Vgreenup are directly controlled by both changes in Dgreenup and Agreenup. Areas with the largest Vgreenup and largest positive trends are both observed in deciduous and mixed forests as compared to nonforest ecosystems showing both lower Vgreenup and trends. For nonforest ecosystems, human-managed ecosystems (e.g., rangelands and rainfed croplands) exhibited higher Vgreenup and positive trends than those of natural counterparts, suggesting strong imprints of human land management on terrestrial ecosystem functioning. Globally, warming has accelerated Vgreenup in temperature-constrained high latitude forest ecosystems and arctic regions, but decelerated Vgreenup in temperate and arid/semiarid areas. These results suggest that the combined effects of climate change and human land management have greatly accelerated global vegetation greenup, with important implications for changes in terrestrial ecosystem functioning and global carbon cycling.

Response of Land Surface Phenology to Variation in Tree Cover during Green-Up and Senescence Periods in the Semi-Arid Savanna of Southern Africa

Understanding the spatio-temporal dynamics of land surface phenology is important to understanding changes in landscape ecological processes of semi-arid savannas in Southern Africa. The aim of the study was to determine the influence of variation in tree cover percentage on land surface phenological response in the semi-arid savanna of Southern Africa. Various land surface phenological metrics for the green-up and senescing periods of the vegetation were retrieved from leaf index area (LAI) seasonal time series (2001 to 2015) maps for a study region in South Africa. Tree cover (%) data for 100 randomly selected polygons grouped into three tree cover classes, low (&lt;20%, n = 44), medium (20–40%, n = 22) and high (&gt;40%, n = 34), were used to determine the influence of varying tree cover (%) on the phenological metrics by means of the t-test. The differences in the means between tree cover classes were statistically significant (t-test p &lt; 0.05) for the senescence period metrics but not for the green-up period metrics. The categorical data results were supported by regression results involving tree cover and the various phenological metrics, where tree cover (%) explained 40% of the variance in day of the year at end of growing season compared to 3% for the start of the growing season. An analysis of the impact of rainfall on the land surface phenological metrics showed that rainfall influences the green-up period metrics but not the senescence period metrics. Quantifying the contribution of tree cover to the day of the year at end of growing season could be important in the assessment of the spatial variability of a savanna ecological process such as the risk of fire spread with time.

Large herbivores surf waves of green-up during spring.

The green wave hypothesis (GWH) states that migrating animals should track or 'surf' high-quality forage at the leading edge of spring green-up. To index such high-quality forage, recent work proposed the instantaneous rate of green-up (IRG), i.e. rate of change in the normalized difference vegetation index over time. Despite this important advancement, no study has tested the assumption that herbivores select habitat patches at peak IRG. We evaluated this assumption using step selection functions parametrized with movement data during the green-up period from two populations each of bighorn sheep, mule deer, elk, moose and bison, totalling 463 individuals monitored 1-3 years from 2004 to 2014. Accounting for variables that typically influence habitat selection for each species, we found seven of 10 populations selected patches exhibiting high IRG-supporting the GWH. Nonetheless, large herbivores selected for the leading edge, trailing edge and crest of the IRG wave, indicating that other mechanisms (e.g. ruminant physiology) or measurement error inherent with satellite data affect selection for IRG. Our evaluation indicates that IRG is a useful tool for linking herbivore movement with plant phenology, paving the way for significant advancements in understanding how animals track resource quality that varies both spatially and temporally.

No two are the same: Assessing variability in broad-leaved savanna tree phenology, with watering, from 2012 to 2014 at Nylsvley, South Africa

Ecologists and modellers are yet to fully understand and design accurate models simulating the unpredictable green-up of savanna ecosystems, possibly due to the lack of long-term, phenological monitoring of this biome. In this study, we observed the percentage of leaf age class (new, fully expanded and mature) phenology of two dominant, broad-leaved savanna trees at a weekly scale over the green-up period (August–November) and a monthly scale during the rest of the growing season (December–May) between August 2012 and May 2015 at the Nylsvley Nature Reserve, South Africa. We used an irrigation experiment, commencing in the dry season, to determine whether the simulation of a 20mm rainfall event for several weeks prior to the start of rainfall, could influence the leaf phenology of Burkea africana and Terminalia sericea. Each observed season experienced different environmental conditions from early onset average rainfall (2012), to late-onset high (2013) or low rainfall (2014). Irrigation of T. sericea in 2012 increased green-up rates and in combination with a late season fire during September 2013, resulted in a delayed green-up of the watered trees. Early-greening of B. africana was only observed during the 2014 season. Terminalia sericea showed faster maturation rates than B. africana which indicates the use of a facultative-greening strategy, while B. africana had faster green-up rates after the fire when competition for available nutrients was low. This study has demonstrated that using fine-scale phenological measurements can provide a clearer picture of how trees are greening up in the early stages of the green-up period and showcases the seasonal variability in savanna tree phenology. Investment into long-term phenological monitoring across southern Africa's savannas is needed if we intend to understand cues and predict phenology accurately in the future.

Using phase-spaces to characterize land surface phenology in a seasonally snow-covered landscape

In seasonally snow-covered environments, snow significantly impacts upon vegetative phenology. As such, there is a need to derive land surface phenological descriptors that are free of the influence of snow-cover. The presence of on-ground snow-cover influences the phenological descriptors produced using some remotely sensed vegetation indices. This study proposes a method that uses both the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Infrared Index (NDII) to obtain dates for the start and end of the growing season. The method operates in the phase-spaces (sometimes referred to as feature- or band-spaces) created by the intersection of the NDVI–NDII data-space of individual pixels and can be used to derive descriptors for the start and end of the growing period as well as period corresponding with the end of green-up. This paper describes the origins and rationale for the method, which was applied to a MODIS image time-series of Australia's alpine bioregion for 2000–mid-2001. The results were validated against descriptors derived using the method of Delbart et al. (2005). For the start of the growing period, the validation indicated there was moderate correlation (r=0.51, p≤0.001) between the descriptors. Noise in the NDII time-series used resulted in little, or no, correlation for the end of the growing period (r=−0.13, p≤0.001), and the correlation for the end of the green-up period was somewhat limited (r=0.24, p≤0.001). In contrast to traditional NDVI threshold methods, the phase-space algorithm proposed here provided for a clear set of definitions that correspond with biophysical phenomena of the land surface, such as the offset and on-set of seasonal snow-cover.

Paspalum vaginatum drought tolerance and recovery in adaptive extensive green roof systems

The study evaluated the response of Paspalum vaginatum ‘Platinum TE’ turfgrass under adaptive green roof conditions over the course of two years. P. vaginatum was established in six different green roof substrates: (i) S15:Pum60:P20:Z5, (ii) S15:Pum60:C20:Z5, (iii) S15:Pum40:Per20:P20:Z5, (iv) S15:Pum40:Per20:C20:Z5, (v) S30:Pum40:P20:Z10 and (vi) S30:Pum40:C20:Z10 (where S: sandy loam soil; Pum: pumice; Per: perlite; Z: clinoptilolite zeolite; P: peat and C: compost in volumetric proportions that are indicated by their subscript). Two depths of 7.5cm and 15cm were used for each substrate type. During two summer periods, water-stress was applied through deficit irrigation of 60% ETc. The control irrigation consisted of 100% ETc. Measurements included the determination of green turf cover (GTC) utilizing digital image analysis. The data was fitted to a sigmoid variable slope model to determine the GTC50 (number of days to achieve 50% green turf cover) and the slope variable (which defines how rapidly GTC changed over time). Finally, parameter estimates were used to calculate 95% confidence intervals for the number of days required for GTC to reach 1%, 25%, 50%, 75% or 95% during the water deficit and spring green-up periods. It was found that during the drought stress periods turfgrass retained its GTC over longer time intervals when grown in the deeper substrates of 15cm and when combined with the high irrigation regime of 100% ETc. By contrast, the worst drought tolerance turfgrass response was obtained when the swallow substrate (7.5cm) was combined with the deficit irrigation regime of 60% ETc. The remaining treatments had in-between GTC values, while substrate type was indifferent during the water stress period and, thus, GTC values exhibited the following sequence for the substrate depth and irrigation regime treatments under investigation: 15cm−100% ETc>15cm−60% ETc=7.5cm−100% ETc>7.5cm−60% ETc. The GTC50 values were 20.0–26.8d for the 15cm−100% ETc treatment, 14.9–19.9d for the 15cm−60% ETc treatment, 15.5–19.1d for the 7.5cm−100% ETc treatment and 11.7–15.0d for the 7.5cm−60% ETc treatment. During autumn recovery, which occurred just after the termination of water stress periods, the most influential parameter was shown to be substrate type. In that case, the substrates amended with compost provided faster GTC recovery that ranged from 21.6% to 40.9% compared to the peat-amended substrates that reached GTC values from 14.3% to 24.2%. Similarly, a faster spring green-up was determined for substrates amended with compost having a GTC50 of 32.1–64.2d (with a GTC95 of 50.1–113.7d) compared to the 43.1–81.3d of the peat-amended substrates (with a GTC95 of 90.1–117.6d). It was concluded that P. vaginatum should be established in 15cm substrate depth if the latter can be tolerated by the building framework. On the other hand, if the load bearing capacity of the building framework is inadequate, then P. vaginatum could be established in 7.5cm substrate depth, but irrigation should be applied at 100% ETc. However, in those cases when a 15cm substrate depth can be utilized, then irrigation demands could be reduced at 60% ETc resulting in significant water savings. Substrate type is influential only when water is not a limiting factor, and thus compost-amended substrates are preferred.

Comparison of eMODIS and MOD/MYD13A2 NDVI products during 2012–2014 spring green-up periods in Alaska and northwest Canada

Accurate monitoring of vegetation dynamics is required to understand the inter-annual variability and long term trends in terrestrial carbon exchange in tundra and boreal ecoregions. In western North America, two Normalized Vegetation Index (NDVI) products based on spectral reflectance data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are available. The MOD/MYD13A2 NDVI product is available as a 16-day composite product in a sinusoidal projection as global hdf tiles. The eMODIS Alaska NDVI product is available as a 7-day composite geotif product in a regional equal area conic projection covering Alaska and the entire Yukon River Basin. These two NDVI products were compared for the 2012–2014 late May–late June spring green-up periods in Alaska and the Yukon Territory. Relative to the MOD/MYD13A2 NDVI product, it is likely that the eMODIS NDVI product contained more cloud-contaminated NDVI values. For example, the MOD/MYD13A2 product flagged substantially fewer pixels as “good quality” in each 16-day composite period compared to the corresponding MODIS Alaska NDVI product from a 7-day composite period. During the spring green-up period, when field-based NDVI increases, the eMODIS NDVI product averaged 43 percent of pixels that declined by at least 0.05 NDVI between 2 composite periods, consistent with cloud-contamination problems, while the MOD/MYD13A2 NDVI averaged only 6 percent of pixels. Based on a cloudy Landsat-8 scene, the eMODIS compositing process selected 23 percent pixels, while the MOD/MYD13A2 compositing process selected less than 0.003 percent pixels. Based on the results, it appears that the MOD/MYD13A2 NDVI product is superior for scientific applications based on NDVI phenology in the tundra and boreal regions of northwestern North America.