Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data.

Background: Deciduous forests in eastern North America experienced a widespread and intense spongy moth (Lymantria dispar) infestation in 2021. This study quantified the impact of this spongy moth infestation on carbon (C) cycle in forests across the Great Lakes region in Canada, utilizing high-resolution (10 × 10 m2) Sentinel-2 satellite remote sensing images and eddy covariance (EC) flux data. Study results showed a significant reduction in leaf area index (LAI) and gross primary productivity (GPP) values in deciduous and mixed forests in the region in 2021. Results: Remote sensing derived, growing season mean LAI values of deciduous (mixed) forests were 3.66 (3.18), 2.74 (2.64), and 3.53 (2.94) m2 m-2 in 2020, 2021 and 2022, respectively, indicating about 24 (14)% reduction in LAI, as compared to pre- and post-infestation years. Similarly, growing season GPP values in deciduous (mixed) forests were 1338 (1208), 868 (932), and 1367 (1175) g C m-2, respectively in 2020, 2021 and 2022, showing about 35 (22)% reduction in GPP in 2021 as compared to pre- and post-infestation years. This infestation induced reduction in GPP of deciduous and mixed forests, when upscaled to whole study area (178,000 km2), resulted in 21.1 (21.4) Mt of C loss as compared to 2020 (2022), respectively. It shows the large scale of C losses caused by this infestation in Canadian Great Lakes region. Conclusions: The methods developed in this study offer valuable tools to assess and quantify natural disturbance impacts on the regional C balance of forest ecosystems by integrating field observations, high-resolution remote sensing data and models. Study results will also help in developing sustainable forest management practices to achieve net-zero C emission goals through nature-based climate change solutions.

Intranational synergies and trade-offs reveal common and differentiated priorities of sustainable development goals in China.

Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development.

Historical and future carbon stocks in forests of northern Ontario, Canada.

BACKGROUND: Forests in the Far North of Ontario (FNO), Canada, are likely the least studied in North America, and quantifying their current and future carbon (C) stocks is the first step in assessing their potential role in climate change mitigation. Although the FNO forests are unmanaged, the latter task is made more important by growing interest in developing the region's natural resources, primarily for timber harvesting. In this study, we used a combination of field and remotely sensed observations with a land surface model to estimate forest C stocks in the FNO forests and to project their future dynamics. The specific objective was to simulate historical C stocks for 1901-2014 and future C stocks for 2015-2100 for five shared socioeconomic pathway (SSP) scenarios selected as high priority scenarios for the 6th Assessment Report on Climate Change. RESULTS: Carbon stocks in live vegetation in the FNO forests remained relatively stable between 1901 and 2014 while soil organic carbon (SOC) stocks steadily declined, losing about 16% of their initial value. At the end of the historical simulation (in 2014), the stocks were estimated at 19.8, 46.4, and 66.2 tCha-1 in live vegetation, SOC, and total ecosystem pools, respectively. Projections for 2015-2100 indicated effectively no substantial change in SOC stocks, while live vegetation C stocks increased, accelerating their growth in the second half of the twenty-first century. These results were consistent among all simulated SSP scenarios. Consequently, increase in total forest ecosystem C stocks by 2100 ranged from 16.7 to 20.7% of their value in 2015. Simulations with and without wildfires showed the strong effect of fire on forest C stock dynamics during 2015-2100: inclusion of wildfires reduced the live vegetation increase by half while increasing the SOC pool due to higher turnover of vegetation C to SOC. CONCLUSIONS: Forest ecosystem C stock estimates at the end of historical simulation period were at the lower end but within the range of values reported in the literature for northern boreal forests. These estimates may be treated as conservatively low since the area included in the estimates is poorly studied and some of the forests may be on peat deposits rather than mineral soils. Future C stocks were projected to increase in all simulated SSP scenarios, especially in the second half of the twenty-first century. Thus, during the projected period forest ecosystems of the FNO are likely to act as a C sink. In light of growing interest in developing natural resources in the FNO, collecting more data on the status and dynamics of its forests is needed to verify the above-presented estimates and design management activities that would maintain their projected C sink status.

Greening drylands despite warming consistent with carbon dioxide fertilization effect.

The rising atmospheric CO2 concentration leads to a CO2 fertilization effect on plants-that is, increased photosynthetic uptake of CO2 by leaves and enhanced water-use efficiency (WUE). Yet, the resulting net impact of CO2 fertilization on plant growth and soil moisture (SM) savings at large scale is poorly understood. Drylands provide a natural experimental setting to detect the CO2 fertilization effect on plant growth since foliage amount, plant water-use and photosynthesis are all tightly coupled in water-limited ecosystems. A long-term change in the response of leaf area index (LAI, a measure of foliage amount) to changes in SM is likely to stem from changing water demand of primary productivity in water-limited ecosystems and is a proxy for changes in WUE. Using 34-year satellite observations of LAI and SM over tropical and subtropical drylands, we identify that a 1% increment in SM leads to 0.15% (±0.008, 95% confidence interval) and 0.51% (±0.01, 95% confidence interval) increments in LAI during 1982-1998 and 1999-2015, respectively. The increasing response of LAI to SM has contributed 7.2% (±3.0%, 95% confidence interval) to total dryland greening during 1999-2015 compared to 1982-1998. The increasing response of LAI to SM is consistent with the CO2 fertilization effect on WUE in water-limited ecosystems, indicating that a given amount of SM has sustained greater amounts of photosynthetic foliage over time. The LAI responses to changes in SM from seven dynamic global vegetation models are not always consistent with observations, highlighting the need for improved process knowledge of terrestrial ecosystem responses to rising atmospheric CO2 concentration.

Satellite detection of cumulative and lagged effects of drought on autumn leaf senescence over the Northern Hemisphere.

Climate change has substantial influences on autumn leaf senescence, that is, the end of the growing season (EOS). Relative to the impacts of temperature and precipitation on EOS, the influence of drought is not well understood, especially considering that there are apparent cumulative and lagged effects of drought on plant growth. Here, we investigated the cumulative and lagged effects of drought (in terms of the Standardized Precipitation-Evapotranspiration Index, SPEI) on EOS derived from the normalized difference vegetation index (NDVI3g) data over the Northern Hemisphere extra-tropical ecosystems (>30°N) during 1982-2015. The cumulative effect was determined by the number of antecedent months at which SPEI showed the maximum correlation with EOS (i.e., Rmax-cml ) while the lag effect was determined by a month during which the maximum correlation between 1-month SPEI and EOS occurred (i.e., Rmax-lag ). We found cumulative effect of drought on EOS for 27.2% and lagged effect for 46.2% of the vegetated land area. For the dominant time scales where the Rmax-cml and Rmax-lag occurred, we observed 1-4 accumulated months for the cumulative effect and 2-6 lagged months for the lagged effect. At the biome level, drought had stronger impacts on EOS in grasslands, savannas, and shrubs than in forests, which may be related to the different root functional traits among vegetation types. Considering hydrological conditions, the mean values of both Rmax-cml and Rmax-lag decreased along the gradients of annual SPEI and its slope, suggesting stronger cumulative and lagged effects in drier regions as well as in areas with decreasing water availability. Furthermore, the average accumulated and lagged months tended to decline along the annual SPEI gradient but increase with increasing annual SPEI. Our results revealed that drought has strong cumulative and lagged effects on autumn phenology, and considering these effects could provide valuable information on the vegetation response to a changing climate.

Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems.

Climate change is lengthening the growing season of the Northern Hemisphere extratropical terrestrial ecosystems, but little is known regarding the timing and dynamics of the peak season of plant activity. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations and atmospheric CO2 concentration and δ13 C isotope measurements at Point Barrow (Alaska, USA, 71°N) to study the dynamics of the peak of season (POS) of plant activity. Averaged across extratropical (>23°N) non-evergreen-dominated pixels, NDVI data show that the POS has advanced by 1.2 ± 0.6 days per decade in response to the spring-ward shifts of the start (1.0 ± 0.8 days per decade) and end (1.5 ± 1.0 days per decade) of peak activity, and the earlier onset of the start of growing season (1.4 ± 0.8 days per decade), while POS maximum NDVI value increased by 7.8 ± 1.8% for 1982-2015. Similarly, the peak day of carbon uptake, based on calculations from atmospheric CO2 concentration and δ13 C data, is advancing by 2.5 ± 2.6 and 4.3 ± 2.9 days per decade, respectively. POS maximum NDVI value shows strong negative relationships (p < .01) with the earlier onset of the start of growing season and POS days. Given that the maximum solar irradiance and day length occur before the average POS day, the earlier occurrence of peak plant activity results in increased plant productivity. Both the advancing POS day and increasing POS vegetation greenness are consistent with the shifting peak productivity towards spring and the increasing annual maximum values of gross and net ecosystem productivity simulated by coupled Earth system models. Our results further indicate that the decline in autumn NDVI is contributing the most to the overall browning of the northern high latitudes (>50°N) since 2011. The spring-ward shift of peak season plant activity is expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.

No evidence of widespread decline of snow cover on the Tibetan Plateau over 2000-2015.

Understanding the changes in snow cover is essential for biological and hydrological processes in the Tibetan Plateau (TP) and its surrounding areas. However, the changes in snow cover phenology over the TP have not been well documented. Using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data, we reported daily cloud-free snow cover product over the Tibetan Plateau (TP) for 2000-2015. Snow cover start (SCS), melt (SCM) and duration (SCD) dates were calculated for each hydrological year, and their spatial and temporal variations were analyzed with elevation variations. Our results show no widespread decline in snow cover over the past fifteen years and the trends of snow cover phenology over the TP has high spatial heterogeneity. Later SCS, earlier SCM, and thus decreased SCD mainly occurred in the areas with elevation below 3500 m a.s.l., while regions in central and southwestern edges of the TP showed advanced SCS, delayed SCM and consequently longer SCD. The roles of temperature and precipitation on snow cover penology varied in different elevation zones, and the impact of both temperature and precipitation strengthened as elevation increases.

Changes in vegetation phenology are not reflected in atmospheric CO2 and 13 C/12 C seasonality.

Northern terrestrial ecosystems have shown global warming-induced advances in start, delays in end, and thus increased lengths of growing season and gross photosynthesis in recent decades. The tradeoffs between seasonal dynamics of two opposing fluxes, CO2 uptake through photosynthesis and release through respiration, determine the influence of the terrestrial ecosystem on the atmospheric CO2 and 13 C/12 C seasonality. Here, we use four CO2 observation stations in the Northern Hemisphere, namely Alert, La Jolla, Point Barrow, and Mauna Loa Observatory, to determine how changes in vegetation productivity and phenology, respiration, and air temperature affect both the atmospheric CO2 and 13 C/12 C seasonality. Since the 1960s, the only significant long-term trend of CO2 and 13 C/12 C seasonality was observed at the northern most station, Alert, where the spring CO2 drawdown dates advanced by 0.65 ± 0.55 days yr-1 , contributing to a nonsignificant increase in length of the CO2 uptake period (0.74 ± 0.67 days yr-1 ). For Point Barrow station, vegetation phenology changes in well-watered ecosystems such as the Canadian and western Siberian wetlands contributed the most to 13 C/12 C seasonality while the CO2 seasonality was primarily linked to nontree vegetation. Our results indicate significant increase in the Northern Hemisphere soil respiration. This means, increased respiration of 13 C depleted plant materials cancels out the 12 C gain from enhanced vegetation activities during the start and end of growing season. These findings suggest therefore that parallel warming-induced increases both in photosynthesis and respiration contribute to the long-term stability of CO2 and 13 C/12 C seasonality under changing climate and vegetation activity. The summer photosynthesis and the soil respiration in the dormant seasons have become more vigorous which lead to increased peak-to-through CO2 amplitude. As the relative magnitude of the increased photosynthesis in summer months is more than the increased respiration in dormant months, we have the increased overall carbon uptake rates in the northern ecosystems.

Country-level net primary production distribution and response to drought and land cover change.

Carbon sequestration by terrestrial ecosystems can offset emissions and thereby offers an alternative way of achieving the target of reducing the concentration of CO2 in the atmosphere. Net primary production (NPP) is the first step in the sequestration of carbon by terrestrial ecosystems. This study quantifies moderate-resolution imaging spectroradiometer (MODIS) NPP from 2000 to 2014 at the country level along with its response to drought and land cover change. Our results indicate that the combined NPP for 53 countries represents >90% of global NPP. From 2000 to 2014, 29 of these 53 countries had increasing NPP trends, most notably the Central African Republic (23gC/m2/y). The top three and top 12 countries accounted for 30% and 60% of total global NPP, respectively, whereas the mean national NPP per unit area in the countries with the 12 lowest values was only around ~300gC/m2/y - the exception to this was Brazil, which had an NPP of 850gC/m2/y. Large areas of Russia, Argentina, Peru and several countries in southeast Asia showed a marked decrease in NPP (~15gC/m2/y). About 37% of the NPP decrease was caused by drought while ~55% of NPP variability was attributed to changes in water availability. Land cover change explained about 20% of the NPP variability. Our findings support the idea that government policies should aim primarily to improve water management in drought-afflicted countries; land use/land cover change policy could also be used as an alternative method of increasing NPP.

Global vegetation productivity response to climatic oscillations during the satellite era.

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30 years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time.

Satellite chlorophyll fluorescence measurements reveal large-scale decoupling of photosynthesis and greenness dynamics in boreal evergreen forests.

Mid-to-high latitude forests play an important role in the terrestrial carbon cycle, but the representation of photosynthesis in boreal forests by current modelling and observational methods is still challenging. In particular, the applicability of existing satellite-based proxies of greenness to indicate photosynthetic activity is hindered by small annual changes in green biomass of the often evergreen tree population and by the confounding effects of background materials such as snow. As an alternative, satellite measurements of sun-induced chlorophyll fluorescence (SIF) can be used as a direct proxy of photosynthetic activity. In this study, the start and end of the photosynthetically active season of the main boreal forests are analysed using spaceborne SIF measurements retrieved from the GOME-2 instrument and compared to that of green biomass, proxied by vegetation indices including the Enhanced Vegetation Index (EVI) derived from MODIS data. We find that photosynthesis and greenness show a similar seasonality in deciduous forests. In high-latitude evergreen needleleaf forests, however, the length of the photosynthetically active period indicated by SIF is up to 6 weeks longer than the green biomass changing period proxied by EVI, with SIF showing a start-of-season of approximately 1 month earlier than EVI. On average, the photosynthetic spring recovery as signalled by SIF occurs as soon as air temperatures exceed the freezing point (2-3 °C) and when the snow on the ground has not yet completely melted. These findings are supported by model data of gross primary production and a number of other studies which evaluated in situ observations of CO2 fluxes, meteorology and the physiological state of the needles. Our results demonstrate the sensitivity of space-based SIF measurements to light-use efficiency of boreal forests and their potential for an unbiased detection of photosynthetic activity even under the challenging conditions interposed by evergreen boreal ecosystems.

Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Accelerating forest growth enhancement due to climate and atmospheric changes in British Colombia, Canada over 1956-2001.

Changes in climate and atmospheric CO2 and nitrogen (N) over the last several decades have induced significant effects on forest carbon (C) cycling. However, contributions of individual factors are largely unknown because of the lack of long observational data and the undifferentiating between intrinsic factors and external forces in current ecosystem models. Using over four decades (1956-2001) of forest inventory data at 3432 permanent samples in maritime and boreal regions of British Columbia (B.C.), Canada, growth enhancements were reconstructed and partitioned into contributions of climate, CO2 and N after removal of age effects. We found that climate change contributed a particularly large amount (over 70%) of the accumulated growth enhancement, while the remaining was attributed to CO2 and N, respectively. We suggest that climate warming is contributing a widespread growth enhancement in B.C.'s forests, but ecosystem models should consider CO2 and N fertilization effects to fully explain inventory-based observations.

Citizen science: best practices to remove observer bias in trend analysis.

Citizen science, time series records over long periods of time, and wide geographic areas offer many opportunities for scientists to answer questions that would otherwise be impractical to investigate. Citizen scientists currently play active roles in a wide range of ecological projects; however, observer biases such as varying perception of events or objects being observed and quality of observations present challenges to successfully derive interannual variability and trend statistics from time series records. It is recommended that citizen science records, particularly those involving events such as plant phenology, should not be directly averaged across sites. The interannual variability expressed as an anomaly and trend expressed as a regression slope should be calculated for each site. Only the site level anomaly and regression slopes should be averaged to suppress observer biases.

Citizen Science: linking the recent rapid advances of plant flowering in Canada with climate variability.

The timing of crucial events in plant life cycles is shifting in response to climate change. We use phenology records from PlantWatch Canada 'Citizen Science' networks to study recent rapid shifts of flowering phenology and its relationship with climate. The average first flower bloom day of 19 Canadian plant species has advanced by about 9 days during 2001-2012. 73% of the rapid and unprecedented first bloom day advances are explained by changes in mean annual national temperature, allowing the reconstruction of historic flower phenology records starting from 1948. The overall trends show that plant flowering in Canada is advancing by about 9 days per °C. This analysis reveals the strongest biological signal yet of climate warming in Canada. This finding has broad implications for niche differentiation among coexisting species, competitive interactions between species, and the asynchrony between plants and the organisms they interact with.