Changes In Aboveground Biomass Research Articles

Estimating selective logging impacts on aboveground biomass in tropical forests using digital aerial photography obtained before and after a logging event from an unmanned aerial vehicle

Selective logging is one of the factors contributing to deforestation and forest degradation in tropical forests. A low-cost methodology to monitor selective logging is clearly required. However, this poses a challenge because only a few trees are felled at a given time. Here, we investigate the potential of using repeatedly acquired digital aerial photographs (DAPs) from a lightweight unmanned aerial vehicle (UAV) to detect selective logging in tropical forests in Myanmar. Selective logging was conducted within two 9-ha plots. DAPs were acquired immediately before and after selective logging using a lightweight UAV in this case study. The aboveground biomass (AGB) change related to selective logging was regressed against metrics expressing forest changes calculated at a 0.25-ha resolution from a photogrammetric point cloud created using the DAPs before and after selective logging. The root-mean-square error and coefficient of determination were 0.77 and 9.32 Mg/ha, respectively. This study demonstrates that repeated DAPs taken from a lightweight UAV can be used to estimate changes in the AGB linked to selective logging. This method could be used to quantify the impacts of both legal selective logging and illegal logging in tropical forests.

Effects of endogenous and exogenous processes on aboveground biomass stocks and dynamics in Andean forests

Tropical forests are paramount in regulating the global carbon cycle due to the storage of large amounts of carbon in their biomass. Using repeat censuses of permanent plots located at 15 sites in the Andes Mountains of northwest Colombia, we evaluate: (1) the relationship between aboveground biomass (AGB) stocks, AGB dynamics (mortality, productivity, and net change), and changes in temperature across a ca. 3000-m elevational gradient (≈ 16.1 °C); (2) how AGB mortality and AGB productivity interact to determine net AGB change; and (3) the extent to which either fine-grain (0.04-ha) or coarse-grain (1-ha) processes determine the AGB dynamics of these forests. We did not find a significant relationship between elevation/temperature and biomass stocks. The net AGB sequestered each year by these forests (2.21 ± 0.51 Mg ha−1 year−1), equivalent to approximately 1.09% of initial AGB, was primarily determined by tree growth. Both forest structural properties and global warming influenced AGB mortality and net change. AGB productivity increases with greater inequality of tree sizes, a pattern characteristic of forest patches recovering from disturbances. Overall, we find that global warming is triggering directional changes in species composition by thermophilization via increased tree mortality of species in the lower portions of their thermal ranges and that the inclusion of small-scale forest structural changes can effectively account for endogenous processes such as changes in forest structure. The inclusion of fine-grain processes in assessments of AGB dynamics could provide additional insights about the effects that ongoing climate change has on the functioning of tropical montane forests.

Assessment of a Power Law Relationship Between P-Band SAR Backscatter and Aboveground Biomass and Its Implications for BIOMASS Mission Performance

This paper presents an analysis of a logarithmic relationship between P-band cross-polarized backscatter from synthetic aperture radar (SAR) and aboveground biomass (AGB) across different forest types based on multiple airborne datasets. It is found that the logarithmic function provides a statistically significant fit to the observed relationship between HV backscatter and AGB. While the coefficient of determination varies between datasets, the slopes, and intercepts of many of the models are not significantly different, especially when similar AGB ranges are assessed. Pooled boreal and pooled tropical data have slopes that are not significantly different, but they have different intercepts. Using the power law formulation of the logarithmic relation allows estimation of both the equivalent number of looks (ENL) needed to retrieve AGB with a given uncertainty and the sensitivity of the AGB inversion. The campaign data indicates that boreal forests require a larger ENL than tropical forests to achieve a specified relative accuracy. The ENL can be increased by multichannel filtering, but ascending and descending images will need to be combined to meet the performance requirements of the BIOMASS mission. The analysis also indicates that the relative change in AGB associated with a given backscatter change depends only on the magnitude of the change and the exponent of the power law, and further implies that to achieve a relative AGB accuracy of 20% or better, residual errors from radiometric distortions produced by the system and environmental effects must not exceed 0.43 dB in tropical and 0.39 dB in boreal forests.

Aboveground biomass and root/shoot ratio regulated drought susceptibility of ecosystem carbon exchange in a meadow steppe

Nitrogen deposition and altered precipitation regime are likely to change plant growth, biomass allocation and community structure, which may influence susceptibility of ecosystem functions (i.e. ecosystem carbon exchange) to extreme climatic events, such as drought. In a meadow steppe, we deployed a drought treatment on a long-term water and nitrogen addition experiment to investigate resource abundance changes induced variation in the sensitivity of ecosystem carbon exchange to extreme drought. Compared to the control plots, long-term water and nitrogen addition caused a strong increase in biomass, and a reduction in diversity and root/shoot ratio. Net ecosystem CO2 exchange (NEE) in water and nitrogen addition plots were more sensitive to drought stress than the control plots. The enhanced NEE drought sensitivity (SNEE) in nitrogen fertilization habitat is associated with changes in aboveground biomass and root/shoot ratio, rather than variation in species diversity, while SNEE in the unfertilized plots was controlled by root/shoot ratio. Compared to the water and nitrogen addition plots, the control plots had the highest percentage recovery of ecosystem carbon exchange (RNEE) during the rehydration period. RNEE is likely determined by aboveground biomass and level of damage in the photosynthetic organ. These findings suggest that long-term changes in precipitation regimes and nitrogen deposition may significant alter the susceptibility of key ecosystem processes to drought stress.

Restoration of degraded landscapes for ecosystem services in North-Western Ethiopia

Establishing exclosures has become common in Ethiopia, especially in the central and northern highlands, where they serve as a response to persistent forest degradation, affecting forest resources and ecosystem services. We investigated changes in vegetation composition, aboveground biomass and soil properties after establishing an exclosure on degraded communal grazing land in Aba-Gerima watershed, North-Western Ethiopia. We selected 4-yr-old exclosure and paired the selected exclosure with an adjacent communal grazing land. In the exclosure, we recorded 46 plant species representing 32 families, whereas we recorded 18 plant species representing 13 families in the adjacent communal grazing lands. Most of the identified woody species are economically important. We observed significant differences between the exclosure and adjacent grazing land in woody species richness, diversity and evenness. Exclosure displayed higher woody species density, basal area and aboveground woody biomass compared to the adjacent grazing land. Landscape position influenced vegetation composition, richness and diversity in the exclosure and adjacent grazing land. Significant differences between the exclosure and adjacent grazing land in soil properties were detected. The influence of landscape positions on soil properties was not consistent. At foot slope position, in the 0- to 15-cm and 15- to 30-cm depths, soil organic carbon and nitrogen content detected in exclosure were significantly higher when compared to the values observed in the adjacent grazing land. However, differences at mid and upper slope positions were not significant. The results support that the establishment of exclosures on degraded lands could support the restoration of degraded native vegetation and soil properties, which consequently enhance the ecosystem services that can be obtained from degraded lands.

Evaluating the uncertainty of Landsat-derived vegetation indices in quantifying forest fuel treatments using bi-temporal LiDAR data

Forest ecosystems in the American west have long been influenced by timber harvests and fire suppression, and recently through treatments that reduce fuel for fire management. Precisely quantifying the structural changes to forests caused by fuel treatments is an essential step to evaluate their impacts. Satellite imagery-derived vegetation indices, such as the normalized difference vegetation index (NDVI), have been widely used to map forest dynamics. However, uncertainties in using these vegetation indices to quantify forest structural changes have not been thoroughly studied, mainly due to the lack of wall-to-wall validation data. In this study we generated forest structural changes in aboveground biomass (AGB) and canopy cover as a result of fuel treatments using bi-temporal airborne light detection and ranging (LiDAR) data and field measurements in a mixed coniferous forest of northern Sierra Nevada, California, USA. These LiDAR-derived forest structural measures were used to evaluate the uncertainties of using Landsat-derived vegetation indices to quantify treatments. Our results confirmed that vegetation indices can accurately map the extents of forest disturbance and canopy cover changes caused by fuel treatments, but the accuracy in quantifying AGB changes varied by the pre-treatment forest densities and treatment intensity. Changes in vegetation indices had relatively weaker correlations (coefficient of determination < 0.45) to biomass changes in forests with sparse (AGB < 100 Mg/ha) or dense biomass (AGB > 700 Mg/ha), than in forests with moderate-density (AGB between 100 Mg/ha and 700 Mg/ha) before the disturbances. Moreover, understory treatments (canopy height < 10 m) were poorly indicated by changes in satellite-derived vegetation indices. Our results suggest that when relating vegetation indices to AGB changes, researchers and managers should be cautious about their uncertainties in extremely dense or sparse forests, particularly when treatments mainly removed small trees or understory fuels.

Estimating aboveground biomass of Pinus densata-dominated forests using Landsat time series and permanent sample plot data

Southwest China is one of three major forest regions in China and plays an important role in carbon sequestration. Accurate estimations of changes in aboveground biomass are critical for understanding forest carbon cycling and promoting climate change mitigation. Southwest China is characterized by complex topographic features and forest canopy structures, complicating methods for mapping aboveground biomass and its dynamics. The integration of continuous Landsat images and national forest inventory data provides an alternative approach to develop a long-term monitoring program of forest aboveground biomass dynamics. This study explores the development of a methodological framework using historical national forest inventory plot data and Landsat TM time-series images. This method was formulated by comparing two parametric methods: Linear Regression for Multiple Independent Variables (MLR), and Partial Least Square Regression (PLSR); and two nonparametric methods: Random Forest (RF) and Gradient Boost Regression Tree (GBRT) based on the state of forest aboveground biomass and change models. The methodological framework mapped Pinus densata aboveground biomass and its changes over time in Shangri-la, Yunnan, China. Landsat images and national forest inventory data were acquired for 1987, 1992, 1997, 2002 and 2007. The results show that: (1) correlation and homogeneity texture measures were able to characterize forest canopy structures, aboveground biomass and its dynamics; (2) GBRT and RF predicted Pinus densata aboveground biomass and its changes better than PLSR and MLR; (3) GBRT was the most reliable approach in the estimation of aboveground biomass and its changes; and, (4) the aboveground biomass change models showed a promising improvement of prediction accuracy. This study indicates that the combination of GBRT state and change models developed using temporal Landsat and national forest inventory data provides the potential for developing a methodological framework for the long-term mapping and monitoring program of forest aboveground biomass and its changes in Southwest China.

Progressively excluding mammals of different body size affects community and trait structure of ground beetles

Mammalian grazing induces changes in vegetation properties in grasslands, which can affect a wide variety of other animals including many arthropods. However, the impacts may depend on the type and body size of these mammals. Furthermore, how mammals influence functional trait syndromes of arthropod communities is not well known.We progressively excluded large (e.g. red deer, chamois), medium (e.g. alpine marmot, mountain hare), and small (e.g. mice) mammals using size‐selective fences in two vegetation types (short‐ and tall‐grass vegetation) of subalpine grasslands. We then assessed how these exclusions affected the community composition and functional traits of ground beetles (Coleoptera, Carabidae), and which vegetation characteristic mediated the observed effects.Total carabid biomass, the activity densities of carabids with specific traits (i.e. small eyes, short wings), the richness of small‐eyed species and the richness of herbivorous species were significantly higher when certain mammals were excluded compared to when all mammals had access, regardless of vegetation type. Excluding large and medium mammals increased the activity density of herbivorous carabid species, but only in short‐grass vegetation. Similarly, excluding large mammals (ungulates) altered carabid species composition in the short‐, but not in the tall‐grass vegetation. All these responses were related to aboveground plant biomass, but not to plant Shannon diversity or vegetation structural heterogeneity.Our results indicate that changes in aboveground plant biomass are key drivers of mammalian grazers’ influence on carabids, suggesting that bottom–up forces are important in subalpine grassland systems. The exclusion of ungulates provoked the strongest carabid response. Our results, however, also highlight the ecological significance of smaller herbivorous mammals. Our study furthermore shows that mammalian grazing not only altered carabid community composition, but also caused community‐wide functional trait shifts, which could potentially have a wider impact on species interactions and ecosystem functioning.

Savanna turning into forest: concerted vegetation change at the ecotone between the Amazon and “Cerrado” biomes

In the “Cerrado”–Amazon ecotone in central Brazil, recent studies suggest some encroachment of forest into savanna, but how, where, and why this might be occurring is unclear. To better understand this phenomenon, we assessed changes in the structure and dynamics of tree species in three vegetation types at the “Cerrado”–Amazon ecotone that are potentially susceptible to encroachment: open “cerrado” (OC), typical “cerrado” (TC) and dense woodland (DW). We estimated changes in density, basal area and aboveground biomass of trees with diameter ≥ 10 cm over four inventories carried out between 2008 and 2015 and classified the species according to their preferred habitat (savanna, generalist, or forest). There was an increase in all structural parameters assessed in all vegetation types, with recruitment and gains in basal area and biomass greater than mortality and losses. Thus, there were net gains between the first and final inventories in density (OC: 3.4–22.9%; TC: 1.8–12.6%; DW: 0.2–8.3%), in basal area (OC: 8.3–18.2%; TC: 2–12.7%; DW: 2.3–8.9%), and in biomass (OC: 10.6–16.4%; TC: 1–12%; DW: 5.2–18.7%). Furthermore, all vegetation types also experienced net gains in forest and generalist species relative to savanna species. A decline in recruitment of savanna species was a likely consequence of vegetation encroachment and environmental changes. Our results indicate, for the first time based on quantitative and standardized multi-site temporal data, that concerted structural changes caused by vegetation encroachment are occurring at the ecotone between the two largest biomes in Brazil.

Assessing the role of megafauna in tropical forest ecosystems and biogeochemical cycles – the potential of vegetation models

Megafauna (terrestrial vertebrate herbivores &gt; 5 kg) can have disproportionate direct and indirect effects on forest structure, function, and biogeochemical cycles. We reviewed the literature investigating these effects on tropical forest dynamics and biogeochemical cycles in relation to ecology, paleoecology, and vegetation modelling. We highlight the limitations of field‐based studies in evaluating the long‐term consequences of loss of megafauna. These limitations are due to inherent space‐time restrictions of field‐studies and a research focus on seed dispersal services provided by large animals. We further present evidence of a research gap concerning the role of megafauna in carbon cycling in tropical ecosystems. Specifically, changes in aboveground biomass might not be noticeable in short‐term studies because of slow vegetation dynamics requiring decades to respond to disturbance (i.e. defaunation). Nutrient cycling has received even less attention in relation to the role of megafauna in tropical forests. We present an approach to investigate the effects of megafauna from new perspectives and with various tools (notably, vegetation models), which can simulate long‐term dynamics in different environmental and megafauna density scenarios. Vegetation models could facilitate interaction between plant–animal ecology and biogeochemistry research. We present practical examples on how to integrate plant–animal interactions in vegetation models to further our understanding of the role of large herbivores in tropical forests.

Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches

Monitoring of changes in forest biomass requires accurate transfer functions between remote sensing-derived changes in canopy height (ΔH) and the actual changes in aboveground biomass (ΔAGB). Different approaches can be used to accomplish this task: direct approaches link ΔH directly to ΔAGB, while indirect approaches are based on deriving AGB stock estimates for two points in time and calculating the difference. In some studies, direct approaches led to more accurate estimations, while, in others, indirect approaches led to more accurate estimations. It is unknown how each approach performs under different conditions and over the full range of possible changes. Here, we used a forest model (FORMIND) to generate a large dataset (&gt;28,000 ha) of natural and disturbed forest stands over time. Remote sensing of forest height was simulated on these stands to derive canopy height models for each time step. Three approaches for estimating ΔAGB were compared: (i) the direct approach; (ii) the indirect approach and (iii) an enhanced direct approach (dir+tex), using ΔH in combination with canopy texture. Total prediction accuracies of the three approaches measured as root mean squared errors (RMSE) were RMSEdirect = 18.7 t ha−1, RMSEindirect = 12.6 t ha−1 and RMSEdir+tex = 12.4 t ha−1. Further analyses revealed height-dependent biases in the ΔAGB estimates of the direct approach, which did not occur with the other approaches. Finally, the three approaches were applied on radar-derived (TanDEM-X) canopy height changes on Barro Colorado Island (Panama). The study demonstrates the potential of forest modeling for improving the interpretation of changes observed in remote sensing data and for comparing different methodologies.

Annual forest aboveground biomass changes mapped using ICESat/GLAS measurements, historical inventory data, and time-series optical and radar imagery for Guangdong province, China

Forest aboveground biomass (AGB) assessments are essential for accurate understanding of carbon accounting under forest disturbance effects and climate change. We mapped AGB data (from 1986 to 2016) by combining the forest inventories and multisource remotely sensed data, including the Ice, Cloud, and Land Elevation Satellite data and Landsat dense time series imagery, and L-band Synthetic Aperture Radar (PALSAR) mosaic data in Guangdong, China. We used random forest (RF) and stochastic gradient boosting (SGB) algorithms to determine the optimal variables of statistical models for mapping and validation of the AGB purpose. Our results showed that the Geoscience Laser Altimeter System (GLAS)-based AGB correlated well (R2adj = 0.89, n = 277, p < 0.001, RMSE = 21.24t/ha) with those obtained using the field-based method that used an RF-based approach, although inevitably, there is a saturation problem. The combined remotely sensed optical and radar imagery and ancillary data sets for mapping AGB using the RF algorithm yielded a stronger (R2adj = 0.86, n = 558, p < 0.001, RMSE = 11.35t/ha) linear correlation with those produced using the GLAS waveform data than that produced using the SGB algorithm. The overall accuracy and Kappa coefficient of mapping forests based on the PALSAR-forest/non-forest Landsat-based phenology for AGB masking were approximately 92.1% and 0.83, respectively. Additionally, the total amount of AGB had increased from 1986 to 2016 by 55.9%. The same increasing trend was observed for total AGB in both mid-subtropical (from 42% to 62%) and south-subtropical (from 38% to 57%) evergreen broadleaved forests, whereas a decreasing trend was witnessed in the tropical forest, particularly after 2010. There was an upward trend of total AGB among the four economic zones of Guangdong; the mountainous area had the highest AGB value distribution, accounting for 58%–70%, followed by the Pearl River Delta region (20%–30%), the western coast of Guangdong (3%–9%), and the eastern coast of Guangdong (2%–7%). The resulting provincial continuous forest AGB maps will provide a better evaluation of carbon dynamic in southern China.

Biomass Growth from Multi-Temporal TanDEM-X Interferometric Synthetic Aperture Radar Observations of a Boreal Forest Site

Forest growth estimation is important in forest research and forest management, but complex to analyze in diverse forest stands. Twelve summertime TanDEM-X acquisitions from the boreal test site, Krycklan, in Sweden, with a known digital terrain model, DTM, have been used to study phase height and aboveground biomass change over 3.2 years based on the Interferometric Water Cloud Model, IWCM. The maximum phase height rate was determined to 0.29 m/yr, while the mean phase height rate was 0.16 m/yr. The corresponding maximum growth rate of the aboveground dry biomass, AGB, was 4.0 Mg/ha/yr with a mean rate of 1.9 Mg/ha/yr for 27 stands, varying from 23 to 183 Mg/ha. The highest relative AGB growth was found for young stands and high growth rates up to an age of 150 years. Growth rate differences relative a simplified model assuming AGB to be proportional to the phase height were studied, and the possibility to avoid a DTM was discussed. Effects of tree species, thinning, and clear cutting were evaluated. Verifications using in situ data from 2008 and a different in situ dataset combined with airborne laser scanning data from 2015 have been discussed. It was concluded that the use of multi-temporal TanDEM-X interferometric synthetic aperture radar observations with AGB estimates of each individual observation can be an important method to derive growth rates in boreal forests.

Impact of exclosures on wood biomass production and fuelwood supply in northern Ethiopia

In the Ethiopian highlands, communal grazing lands are one of the major land uses, and are source of livelihood for the rural people. Free and uncontrolled grazing in the communal grazing lands is the dominant grazing system. The traditional uncontrolled and free grazing system has caused severe degradation of the grazing lands. As a result, communities have started to establish exclosures and support the restoration of degraded communal grazing lands. Studies have shown that exclosures are effective to restoring degraded communal grazing lands and improving ecosystem services. However, studies that investigate the changes in aboveground biomass following the establishment of exclosures and compare it with fuelwood demand of the beneficiaries in our study area is lacking. Therefore, our study aimed at: (1) quantifying yearly biomass accumulation in exclosures and compare it to fuelwood demand of households that manage the exclosures; (2) assessing household energy sources and their consumption levels. To monitor changes in biomass production with over time, replicated (n = 3) 5 and 10 year-old exclosures were sampled. To investigate fuelwood sources and consumption patterns, household surveys, key informant interviews and focus group discussion were conducted. Our results demonstrated that total biomass production increased with exclosure age. In both exclosure, biomass production from Vachellia etbaica was significantly (p < 0.05) greater than that from Euclea. racemosa. Average daily fuelwood consumption per person was (0.63 ± 0.2) kg day−1. This means that the total biomass (27.5 Mg year−1) obtained from 114.6 ha of exclosures covers only 9.4% of yearly fuelwood demand of the residents who manage the sampled exclosures. Nearly all respondents (95%) confirmed that they travel more than 10 km day−1 to gather fuelwood from surrounding degraded forest patches. We recommend plantings of fast growing native tree species within exclosures and around homesteads to provide a sustainable fuelwood supply and using improved stoves to address the problem of fuelwood shortage. District agricultural offices could provide seedlings of native plant species, while communities provide unpaid labour for planting and managing plantations.

The potential activity of soil extracellular enzymes as an indicator for ecological restoration of rangeland soils after agricultural abandonment

Extracellular enzymes play an important role in soil biochemical reactions and biogeochemical cycles. However, the response of soil extracellular enzyme activities to cultivation abandonment and vegetation restoration is poorly studied for the high altitude semi-arid rangeland ecosystems in Central Iran. The objective of this study was to evaluate the influence of cultivation abandonment on soil enzyme activity as an indicator of soil quality and health along a chronosequence of abandoned agricultural fields in a semi-arid rangeland ecosystem. The potential activity of soil enzymes; including invertase, urease, alkaline phosphatase and arylsulphatase was assayed and expressed as activity per unit dry soil mass (i.e., absolute activity) and per unit microbial biomass (i.e., specific activity) along a sequence of cultivated, abandoned for 4–45 years and uncultivated rangelands. After agricultural abandonment, the absolute enzyme activities increased logarithmically. Cultivation abandonment for 45 years, on average, increased invertase activity by 44%, urease activity by 45%, alkaline phosphatase activity by 11% and arylsulfatase activity by 43% in top soil (0–30 cm). Results showed that the geometric mean of enzyme activities (GMea) increased significantly with increasing abandonment time. However, the specific activities of soil enzymes tended to decrease logarithmically, when expressed per unit microbial biomass carbon (MBC). The increases in absolute activities were largely related to changes in plant aboveground biomass, soil organic carbon (SOC), aggregate stability (AS) and MBC whereas the decreases in specific activities could be associated with alterations only in AS and SOC contents. In conclusion, enzymes produced and released by soil microbial communities after cultivation abandonment and natural vegetation restoration would interact with soil organic matter and aggregates. After cessation of rainfed cropping and the recovery of natural vegetation, the increases in soil enzyme activity can result in a higher nutrient cycling in the degraded rangeland ecosystems.

Predicting Volume and Biomass Change from Multi-Temporal Lidar Sampling and Remeasured Field Inventory Data in Panther Creek Watershed, Oregon, USA

Using lidar for large-scale forest management can improve operational and management decisions. Using multi-temporal lidar sampling and remeasured field inventory data collected from 78 plots in the Panther Creek Watershed, Oregon, USA, we evaluated the performance of different fixed and mixed models in estimating change in aboveground biomass ( ∆ AGB ) and cubic volume including top and stump ( ∆ CVTS ) over a five-year period. Actual values of CVTS and AGB were obtained using newly fitted volume and biomass equations or the equations used by the Pacific Northwest unit of the Forest Inventory and Analysis program. Estimates of change based on fixed and mixed-effect linear models were more accurate than change estimates based on differences in LIDAR-based estimates. This may have been due to the compounding of errors in LIDAR-based estimates over the two time periods. Models used to predict volume and biomass at a given time were, however, more precise than the models used to predict change. Models used to estimate ∆ CVTS were not as accurate as the models employed to estimate ∆ AGB . Final models had cross-validation root mean squared errors as low as 40.90% for ∆ AGB and 54.36% for ∆ CVTS .

Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery

Mapping Canada’s forests is a significant challenge given their extent and the interprovincial differences in forest inventories. We created new sets of nationally consistent forest attribute maps for the years 2001 and 2011 by building upon previously published work with the objective to determine if sequential maps of forest attributes could be used to quantify changes over time. We first refined our previously published methodology of using the k nearest neighbors (kNN) prediction method and MODIS spectral reflectance data as predictive variables. The maps were generated using an improved reference dataset and a new analytical kNN workflow. We then evaluated 2001 to 2011 changes in two key attributes, aboveground biomass and percent tree cover, on pixels identified from published sources as having undergone fire, harvest, or postdisturbance regrowth during that period. For all three change types, average changes in both aboveground biomass and percent tree cover between 2001 and 2011 matched expectations relative to the dynamics of Canadian forests. Our results support the use of sequential national maps of forest attributes for evaluating regionally aggregated disturbance-related changes in forest properties. The new forest attribute maps are available from Beaudoin et al. (2017 ; doi: 10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990) at http://ouvert.canada.ca/data/fr/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 .

Normalized Difference Vegetation Index as an Estimator for Abundance and Quality of Avian Herbivore Forage in Arctic Alaska

Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator (R2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI (R2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study demonstrates the importance of matching the scale of NDVI measurements to the vegetation properties of biomass and nitrogen phenology.

Impact of choice of future climate change projection on growth chamber experimental outcomes: a preliminary study in potato.

Understanding the impacts of climate change on agriculture is essential to ensure adequate future food production. Controlled growth experiments provide an effective tool for assessing the complex effects of climate change. However, a review of the use of climate projections in 57 previously published controlled growth studies found that none considered within-season variations in projected future temperature change, and few considered regional differences in future warming. A fixed, often arbitrary, temperature perturbation typically was applied for the entire growing season. This study investigates the utility of employing more complex climate change scenarios in growth chamber experiments. A case study in potato was performed using three dynamically downscaled climate change projections for the mid-twenty-first century that differ in terms of the timing during the growing season of the largest projected temperature changes. The climate projections were used in growth chamber experiments for four elite potato cultivars commonly planted in Michigan's major potato growing region. The choice of climate projection had a significant influence on the sign and magnitude of the projected changes in aboveground biomass and total tuber count, whereas all projections suggested an increase in total tuber weight and a decrease in specific gravity, a key market quality trait for potato, by mid-century. These results demonstrate that the use of more complex climate projections that extend beyond a simple incremental change can provide additional insights into the future impacts of climate change on crop production and the accompanying uncertainty.

Leaf functional traits of abundant species predict productivity in three temperate herbaceous communities along an environmental gradient

We tested how functional traits of abundant species affect such community properties as photosynthetic capacity and above-ground biomass as well as to what extent do both intra-specific variation and species replacement influence community productivity. We studied above-ground biomass (AGB), functional structure and leaf traits in three herbaceous communities which were located along a local environmental gradient in the south taiga zone: steppe – meadow – forest understory. Leaf thickness (LT) and leaf mass per area (LMA), rates of photosynthesis (Amax) and transpiration (E), chlorophyll content (Cab/A), mesophyll surface area per leaf area (Ames/A) and rate of CO2-transfer through the mesophyll surface (TRCO2) were all measured at the level of species and communities. AGB decreased along the light and water gradient from steppe community to forest understory. The change in AGB depended neither on species richness nor on total coverage, but was positively associated with both species-averaged and community-weighted means of Amax and Ames/A. Intra-specific variability affected community properties to a lesser extent than replacement of abundant species which belonged to different plant functional types (PFTs): mesophytic or xerophytic grasses, herbs or small shrubs with different mesophyll anatomy. Xerophytic herbs possessed larger values of Amax and Ames/A in comparison to mesophytic ones; herbs with dorsiventral leaves had higher Amax than shrubs; and shrubs differed from herbs and grasses by low values of TRCO2. Increase in the relative abundance of xerophytic herbs and grasses in the steppe resulted in the enhancement of photosynthetic capacity at the community level, in comparison with meadow and forest understory. We suppose predictive significance of Amax and Ames/A of abundant species for AGB of herbaceous community and suggest an approach based on a ratio of PFTs identified by growth form, ecotype and leaf mesophyll anatomy that will help to predict the photosynthetic capacity and productivity of herbaceous communities.