Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012-2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m-2 yr-1, mean ± SD). Annual NEP ranged from -66 to 77 g C m-2 yr-1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr-1 or rainfall dropped below 280 mm yr-1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Multifractal Analysis of MODIS Aqua and Terra Satellite Time Series of Normalized Difference Vegetation Index and Enhanced Vegetation Index of Sites Affected by Wildfires

The MODIS Aqua and Terra Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series acquired during nearly two decades (2000 to 2020) covering the area burned by the Camp Fire (California) in 2018 is investigated in this study by using the multifractal detrended fluctuation analysis in relation to the recovery process of vegetation after fire. In 2008, the same area was partially burned by two wildfires, the BTU Lightning Complex Fire and the Humboldt Fire. Our results indicate that all vegetation index time series are featured by six- and twelve-month modulating periodicities, with a larger spectral content at longer periods for two-fire-affected sites. Furthermore, two fires cause an increase of the persistence of the NDVI and EVI time series and an increase of the complexity, suggesting that the recovery process of vegetation dynamics of fire-affected sites is characterized by positive feedback mechanisms, driving the growth-generating phenomena, which become even more effective in those sites affected by two fires.

JA, Meng Q, Sanchez-Azofeifa A. Monitoring the Water Stress of an Indoor Living Wall System Using the "Triangle Method"

Living walls are important vertical greening systems with modular prevegetated structures. Studies have suggested that living walls have many social benefits as an ecological engineering technique with notable potential for reconciliation ecology. Despite these benefits, there are currently no mature workflows or technologies for monitoring the health status and water stress of living wall systems. To partially fill the current knowledge gap related to water stress, we acquired thermal, multispectral, and hyperspectral remote sensing data from an indoor living wall in the Cloud Forest of the Gardens by the Bay, Singapore. The surface temperature (Ts) and a normalized difference vegetation index (NDVI) were obtained from these data to construct a Ts-NDVI space for applying the “triangle method”. A simple and effective algorithm was proposed to determine the dry and wet edges, the key components of the said method. The pixels associated with the dry and wet edges were then selected and highlighted to directly display the areas under water-stress conditions. Our results suggest that the proposed algorithm can provide a reasonable overview of the water-stress information of the living wall; therefore, our method can be simple and effective to monitor the health status of a living wall. Furthermore, our work confirms that the triangle method can be transferred from the outdoors to an indoor environment.

Mangrove health along the hyper-arid southern Red Sea coast of Saudi Arabia

Changes in land use and land cover have severely influenced the sustainability of mangrove vegetation, especially in the hyper-arid, hyper-saline Red Sea coastal waters of Saudi Arabia. The present study investigates the effect of effluents released from an adjoining shrimp farm on the sustainability of a nearby mangrove woodland during operation and after closure of the farm. In addition, the consequences of dredging activities to fill coastal waters for land reclamation to develop a mega seaport at Jazan Economic City are explored. A band image-difference algorithm was applied to Landsat 5 Thematic Mapper and Landsat 08 Operational Land Imager satellite images obtained on different dates, which revealed a prominent vigour boom in the mangrove forest while the shrimp farm operated but a gradual decrease in vigour after its closure. During the investigation time frame of 2016 and 2017, spectral vegetation analysis of Sentinel-2A satellite images highlighted a strong negative correlation between dredging operations for seaport construction and the adjacent fragile mangrove forest. Dredging operations were responsible for a reduction of 19.30% in the Normalized Difference Vegetation Index, 27.5% in the Leaf Area Index, and 19.0% in the Optimized Soil Adjusted Vegetation Index. The results clearly show the potential application of spectral vegetation indices in the monitoring and analysis of anthropogenic impacts on coastal vegetation. We suggest strong management efforts for monitoring, assessing, and regulating measures to offset the negative trends in the sustainability of mangroves in Red Sea coastal regions.

Influence of Landscape Heterogeneity and Spatial Resolution in Multi-Temporal In Situ and MODIS NDVI Data Proxies for Seasonal GPP Dynamics

The objective of this paper was to evaluate the use of in situ normalized difference vegetation index (NDVIis) and Moderate Resolution Imaging Spectroradiometer NDVI (NDVIMD) time series data as proxies for ecosystem gross primary productivity (GPP) to improve GPP upscaling. We used GPP flux data from 21 global FLUXNET sites across main global biomes (forest, grassland, and cropland) and derived MODIS NDVI at contrasting spatial resolutions (between 0.5 × 0.5 km and 3.5 × 3.5 km) centered at flux tower location. The goodness of the relationship between NDVIis and NDVIMD varied across biomes, sites, and MODIS spatial resolutions. We found a strong relationship with a low variability across sites and within year variability in deciduous broadleaf forests and a poor correlation in evergreen forests. Best performances were obtained for the highest spatial resolution at 0.5 × 0.5 km). Both NDVIis and NDVIMD elicited roughly three weeks later the starting of the growing season compared to GPP data. Our results confirm that to improve the accuracy of upscaling in situ data of site GPP seasonal responses, in situ radiation measurement biomes should use larger field of view to sense an area, or more sensors should be placed in the flux footprint area to allow optimal match with satellite sensor pixel size.

Measuring Vegetation Phenology with Near-Surface Remote Sensing in a Temperate Deciduous Forest: Effects of Sensor Type and Deployment

Near-surface remote sensing is an effective tool for in situ monitoring of canopy phenology, but the uncertainties involved in sensor-types and their deployments are rarely explored. We comprehensively compared three types of sensor (i.e., digital camera, spectroradiometer, and routine radiometer) at different inclination- and azimuth-angles in monitoring canopy phenology of a temperate deciduous forest in Northeast China for three years. The results showed that the greater contribution of understory advanced the middle of spring (MOS) for large inclination-angle of camera and spectroradiometer. The length of growing season estimated by camera from the east direction extended 11 d than that from the north direction in 2015 due to the spatial heterogeneity, but there was no significant difference in 2016 and 2018.The difference infield of view of sensors caused the MOS and the middle of fall, estimated by camera, to lag a week behind those by spectroradiometer and routine radiometer. Overall, the effect of azimuth-angle was greater than that of inclination-angle or sensor-type. Our assessments of the sensor types and their deployments are critical for the long-term accurate monitoring of phenology at the site scale and the regional/global-integration of canopy phenology data.

Limited effects of early snowmelt on plants, decomposers, and soil nutrients in Arctic tundra soils

In addition to warming temperatures, Arctic ecosystems are responding to climate change with earlier snowmelt and soil thaw. Earlier snowmelt has been examined infrequently in field experiments, and we lack a comprehensive look at belowground responses of the soil biogeochemical system that includes plant roots, decomposers, and soil nutrients. We experimentally advanced the timing of snowmelt in factorial combination with an open-top chamber warming treatment over a 3-year period and evaluated the responses of decomposers and nutrient cycling processes. We tested two alternative hypotheses: (a) Early snowmelt and warming advance the timing of root growth and nutrient uptake, altering the timing of microbial and invertebrate activity and key nutrient cycling events; and (b) loss of insulating snow cover damages plants, leading to reductions in root growth and altered biological activity. During the 3 years of our study (2010-2012), we advanced snowmelt by 4, 15, and 10 days, respectively. Despite advancing aboveground plant phenology, particularly in the year with the warmest early-season temperatures (2012), belowground effects were primarily seen only on the first sampling date of the season or restricted to particular years or soil type. Overall, consistent and substantial responses to early snowmelt were not observed, counter to both of our hypotheses. The data on soil physical conditions, as well interannual comparisons of our results, suggest that this limited response was because of the earlier date of snowmelt that did not coincide with substantially warmer air and soil temperatures as they might in response to a natural climate event. We conclude that the interaction of snowmelt timing with soil temperatures is important to how the ecosystem will respond, but that 1- to 2-week changes in timing of snowmelt alone are not enough to drive season-long changes in soil microbial and nutrient cycling processes.

Testing of Automated Photochemical Reflectance Index Sensors as Proxy Measurements of Light Use Efficiency in an Aspen Forest

Commercially available autonomous photochemical reflectance index (PRI) sensors are a new development in the remote sensing field that offer novel opportunities for a deeper exploration of vegetation physiology dynamics. In this study, we evaluated the reliability of autonomous PRI sensors (SRS-PRI) developed by METER Group Inc. as proxies of light use efficiency (LUE) in an aspen (Populus tremuloides) forest stand. Before comparisons between PRI and LUE measurements were made, the optical SRS-PRI sensor pairs required calibrations to resolve diurnal and seasonal patterns properly. An offline diurnal calibration procedure was shown to account for variable sky conditions and diurnal illumination changes affecting sensor response. Eddy covariance measurements provided seasonal gross primary productivity (GPP) measures as well as apparent canopy quantum yield dynamics (α). LUE was derived from the ratio of GPP to absorbed photosynthetically active radiation (APAR). Corrected PRI values were derived after diurnal and midday cross-calibration of the sensor’s 532 nm and 570 nm fore-optics, and closely related to both LUE (R² = 0.62, p < 0.05) and α (R² = 0.72, p < 0.05). A LUE model derived from corrected PRI values showed good correlation to measured GPP (R² = 0.77, p < 0.05), with an accuracy comparable to results obtained from an α driven LUE model (R² = 0.79, p < 0.05). The automated PRI sensors proved to be suitable proxies of light use efficiency. The onset of continuous PRI sensors signifies new opportunities for explicitly examining the cause of changing PRI, LUE, and productivity over time and space. As such, this technology represents great value for the flux, remote sensing and modeling community.

Net ecosystem exchange of CO2 with rapidly changing high Arctic landscapes

High Arctic landscapes are expansive and changing rapidly. However, our understanding of their functional responses and potential to mitigate or enhance anthropogenic climate change is limited by few measurements. We collected eddy covariance measurements to quantify the net ecosystem exchange (NEE) of CO2 with polar semidesert and meadow wetland landscapes at the highest latitude location measured to date (82°N). We coupled these rare data with ground and satellite vegetation production measurements (Normalized Difference Vegetation Index; NDVI) to evaluate the effectiveness of upscaling local to regional NEE. During the growing season, the dry polar semidesert landscape was a near-zero sink of atmospheric CO2 (NEE: -0.3 ± 13.5 g C m(-2) ). A nearby meadow wetland accumulated over 300 times more carbon (NEE: -79.3 ± 20.0 g C m(-2) ) than the polar semidesert landscape, and was similar to meadow wetland NEE at much more southerly latitudes. Polar semidesert NEE was most influenced by moisture, with wetter surface soils resulting in greater soil respiration and CO2 emissions. At the meadow wetland, soil heating enhanced plant growth, which in turn increased CO2 uptake. Our upscaling assessment found that polar semidesert NDVI measured on-site was low (mean: 0.120-0.157) and similar to satellite measurements (mean: 0.155-0.163). However, weak plant growth resulted in poor satellite NDVI-NEE relationships and created challenges for remotely detecting changes in the cycling of carbon on the polar semidesert landscape. The meadow wetland appeared more suitable to assess plant production and NEE via remote sensing; however, high Arctic wetland extent is constrained by topography to small areas that may be difficult to resolve with large satellite pixels. We predict that until summer precipitation and humidity increases enough to offset poor soil moisture retention, climate-related changes to productivity on polar semideserts may be restricted.

Greater deciduous shrub abundance extends tundra peak season and increases modeled net CO2 uptake

Satellite studies of the terrestrial Arctic report increased summer greening and longer overall growing and peak seasons since the 1980s, which increases productivity and the period of carbon uptake. These trends are attributed to increasing air temperatures and reduced snow cover duration in spring and fall. Concurrently, deciduous shrubs are becoming increasingly abundant in tundra landscapes, which may also impact canopy phenology and productivity. Our aim was to determine the influence of greater deciduous shrub abundance on tundra canopy phenology and subsequent impacts on net ecosystem carbon exchange (NEE) during the growing and peak seasons in the arctic foothills region of Alaska. We compared deciduous shrub-dominated and evergreen/graminoid-dominated community-level canopy phenology throughout the growing season using the normalized difference vegetation index (NDVI). We used a tundra plant-community-specific leaf area index (LAI) model to estimate LAI throughout the green season and a tundra-specific NEE model to estimate the impact of greater deciduous shrub abundance and associated shifts in both leaf area and canopy phenology on tundra carbon flux. We found that deciduous shrub canopies reached the onset of peak greenness 13 days earlier and the onset of senescence 3 days earlier compared to evergreen/graminoid canopies, resulting in a 10-day extension of the peak season. The combined effect of the longer peak season and greater leaf area of deciduous shrub canopies almost tripled the modeled net carbon uptake of deciduous shrub communities compared to evergreen/graminoid communities, while the longer peak season alone resulted in 84% greater carbon uptake in deciduous shrub communities. These results suggest that greater deciduous shrub abundance increases carbon uptake not only due to greater leaf area, but also due to an extension of the period of peak greenness, which extends the period of maximum carbon uptake.

A mobile system for quantifying the spatial variability of the surface energy balance: design and application

We present a mobile device for the quantification of the small-scale (a few square meters) spatial variability in the surface energy balance components and several auxiliary variables of short-statured (<1 m) canopies. The key element of the mobile device is a handheld four-component net radiometer for the quantification of net radiation, albedo and infrared surface temperature, which is complemented with measurements of air temperature, wind speed, soil temperature and soil water content. Data are acquired by a battery-powered data logger, which is mounted on a backpack together with the auxiliary sensors. The proposed device was developed to bridge between the spatial scales of satellite/airborne remote sensing and fixed, stationary tower-based measurements with an emphasis on micrometeorological, catchment hydrological and landscape-ecological research questions. The potential of the new device is demonstrated through four selected case studies, which cover the issues of net radiation heterogeneity within the footprint of eddy covariance flux measurements due to (1) land use and (2) slope and aspect of the underlying surface, (3) controls on landscape-scale variability in soil temperature and albedo and (4) the estimation of evapotranspiration based exclusively on measurements with the mobile device.

Soil respiration response to climate change in Pacific Northwest prairies is mediated by a regional Mediterranean climate gradient

Soil respiration is expected to increase with rising global temperatures but the degree of response may depend on soil moisture and other local factors. Experimental climate change studies from single sites cannot discern whether an observed response is site-dependent or generalizable. To deconvolve site-specific vs. regional climatic controls, we examined soil respiration for 18 months along a 520 km climate gradient in three Pacific Northwest, USA prairies that represents increasingly severe Mediterranean conditions from north to south. At each site we implemented a fully factorial combination of 2.5-3 °C warming and 20% added precipitation intensity. The response of soil respiration to warming was driven primarily by the latitudinal climate gradient and not site-specific factors. Warming increased respiration at all sites during months when soil moisture was not limiting. However, these gains were offset by reductions in respiration during seasonal transitions and summer drought due to lengthened periods of soil moisture limitation. The degree of this offset varied along the north-south climate gradient such that in 2011 warming increased cumulative annual soil respiration 28.6% in the northern site, 13.5% in the central site, and not at all in the southern site. Precipitation also stimulated soil respiration more frequently in the south, consistent with an increased duration of moisture limitation. The best predictors of soil respiration in nonlinear models were the Normalized Difference Vegetation Index (NDVI), antecedent soil moisture, and temperature but these models provided biased results at high and low soil respiration. NDVI was an effective integrator of climate and site differences in plant productivity in terms of their combined effects on soil respiration. Our results suggest that soil moisture limitation can offset the effect of warming on soil respiration, and that greater growing-season moisture limitation would constrain cumulative annual responses to warming.

Mapping monkeypox transmission risk through time and space in the Congo Basin

Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.

Enviro-Net: from networks of ground-based sensor systems to a Web platform for sensor data management

Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.

Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

The broad-band normalised difference vegetation index (NDVI) and the simple ratio (SR) were calculated from measurements of reflectance of photosynthetically active and short-wave radiation at two temperate mountain grasslands in Austria and related to the net ecosystem CO₂ exchange (NEE) measured concurrently by means of the eddy covariance method. There was no significant statistical difference between the relationships of midday mean NEE with narrow- and broad-band NDVI and SR, measured during and calculated for that same time window, respectively. The skill of broad-band NDVI and SR in predicting CO₂ fluxes was higher for metrics dominated by gross photosynthesis and lowest for ecosystem respiration, with NEE in between. A method based on a simple light response model whose parameters were parameterised based on broad-band NDVI allowed to improve predictions of daily NEE and is suggested to hold promise for filling gaps in the NEE time series. Relationships of CO₂ flux metrics with broad-band NDVI and SR however generally differed between the two studied grassland sites indicting an influence of additional factors not yet accounted for.

Monitoring plant phenology using digital repeat photography

Repeated observations of plant phenology have been shown to be important indicators of global change. However, capturing the exact date of key events requires daily observations during the growing season, making phenologic observations relatively labor intensive and costly to collect. One alternative to daily observations for capturing the dates of key phenologic events is repeat photography. In this study, we explored the utility of repeat digital photography for monitoring phenologic events in plants. We provide an illustration of this approach and its utility by placing observations made using repeat digital imagery in context with local meteorologic and edaphic variables. We found that repeat photography provides a reliable, consistent measurement of phenophase. In addition, digital photography offers advantages in that it can be mathematically manipulated to detect and enhance patterns; it can classify objects; and digital photographs can be archived for future analysis. In this study, an estimate of greenness and counts of individual flowers were extracted by way of mathematic algorithms from the photo time series. These metrics were interpreted using meteorologic measurements collected at the study site. We conclude that repeat photography, coupled with site-specific meteorologic measurements, could greatly enhance our understanding environmental triggers of phenologic events. In addition, the methods described could easily be adopted by citizen scientists and the general public as well as professionals in the field.

The normalised difference vegetation index obtained from agrometeorological standard radiation sensors: A comparison with ground-based multiband spectroradiometer measurements during the phenological development of an oat canopy

Following the methodology of K. F. Huemmrich and colleagues [Huemmrich et al. (1999) J Geophys Res 104:27,935-27,944], agrometeorological standard radiation sensors, i.e. two photosynthetically active radiation sensors and an albedometer, were used to measure the broadband visible and optical-infrared reflectance of an oat plot during its whole growth period. From these reflectance data - recorded as 15-min averages and pooled to daily means - the seasonal cycle of the normalised difference vegetation index (NDVI) was calculated. In addition, a ground-based multi-channel spectroradiometer was used as a reference to estimate narrowband "green" and "red" NDVIs at weekly intervals near noon. The narrowband "green" NDVI was shown to be consistent with the simultaneous broadband 15-min NDVI. This shows that the configuration of agrometeorological radiation sensors is suitable to adequately track phenological crop dynamics.

Use of digital webcam images to track spring green-up in a deciduous broadleaf forest

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO(2) by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 x 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy (f (APAR)), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis (A(max)), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f (APAR) and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A(max) lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program.

Plants reverse warming effect on ecosystem water balance

Models predict that global warming may increase aridity in water-limited ecosystems by accelerating evapotranspiration. We show that interactions between warming and the dominant biota in a grassland ecosystem produced the reverse effect. In a 2-year field experiment, simulated warming increased spring soil moisture by 5-10% under both ambient and elevated CO2. Warming also accelerated the decline of canopy greenness (normalized difference vegetation index) each spring by 11-17% by inducing earlier plant senescence. Lower transpirational water losses resulting from this earlier senescence provide a mechanism for the unexpected rise in soil moisture. Our findings illustrate the potential for organism-environment interactions to modify the direction as well as the magnitude of global change effects on ecosystem functioning.