Reply to Fisher: Nitrogen–albedo relationship in forests remains robust and thought-provoking

Fisher’s primary concerns have overlooked important methodological aspects of our study, whereas other concerns are consistent with our own presentation of the findings. We did not exclude photosynthetically active radiation (PAR) wavelengths, as Fisher states

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Fine tuning Exo2, a small molecule inhibitor of secretion and retrograde trafficking pathways in mammalian cells

The small molecule 4-hydroxy-3-methoxybenzaldehyde (5,6,7,8-tetrahydro[1]benzothieno[2,3- d]pyrimidin-4-yl)hydrazone (Exo2) stimulates morphological changes at the mammalian Golgi and trans-Golgi network that are virtually indistinguishable from those induced by brefeldin A. Both brefeldin A and Exo2 protect cells from intoxication by Shiga(-like) toxins by acting on other targets that operate at the early endosome, but do so at the cost of high toxicity to target cells. The advantage of Exo2 is that it is much more amenable to chemical modification and here we report a range of Exo2 analogues produced by modifying the tetrahydrobenzothienopyrimidine core, the vanillin moiety and the hydrazone bond that links these two. These compounds were examined for the morphological changes they stimulated at the Golgi stack, the trans Golgi network and the transferrin receptor-positive early endosomes and this activity correlated with their inherent toxicity towards the protein manufacturing ability of the cell and their protective effect against toxin challenge. We have developed derivatives that can separate organelle morphology, target specificity, innate toxicity and toxin protection. Our results provide unique compounds with low toxicity and enhanced specificity to unpick the complexity of membrane trafficking networks

Sampling method and sample placement: How do they affect the accuracy of remotely sensed maps?

The accuracy of remotely sensed forest stand maps is traditionally assessed by comparing a sample of the map data with actual ground conditions. Samples most often comprise clusters of pixels within homogeneous areas; thereby avoiding problems associated with accurately mapping edges (e.g., transition areas between two forest types). Consequently, they may well overestimate accuracy, but the degree of overestimation is unknown. This paper examines two important factors regarding accuracy assessment that are not well studied: the effect on estimates Of accuracy of (1) the sampling method and (2) the exact placement of the samples. Overall accuracy, normalized accuracy, and the KHAT statistic are computed from error matrices generated from simple random sampling, stratified random sampling, and systematic sampling using totally random sample placement and samples chosen from homogeneous areas only. The results indicate that Kappa appears to be as appropriate to use with systematic sampling and stratified random sampling as it is with simple random sampling, but suggests that sample placement may have more of an effect on estimates of accuracy than sampling method alone

Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor

Field studies among diverse biomes demonstrate that mass-based nitrogen concentration at leaf and canopy scales is strongly related to carbon uptake and cycling. Combined field and airborne imaging spectrometry studies demonstrate the capacity for accurate empirical estimation of forest canopy N concentration and other biochemical constituents at scales from forest stands to small landscapes. In this paper, we report on the utility of the first space-based imaging spectrometer, Hyperion, for estimation of temperate forest canopy N concentration as compared to that achieved with the airborne high-altitude imaging spectrometer, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Overall accuracy of Hyperion estimates of forest canopy N concentration, as compared with field measurements, were within 0.25% dry mass, and AVIRIS-based estimates were within 0.19% dry mass, each well within the accuracy required to distinguish among forested ecosystems in nitrogen status

Estimating species abundance in a northern temperate forest using spectral mixture analysis

Effective, reliable methods for characterizing the spatial distribution of tree species through remote sensing would represent an important step toward better understanding changes in biodiversity, habitat quality, climate, and nutrient cycling. Towards this end, we explore the feasibility of using spectral mixture analysis to discriminate the distribution and abundance of two important forest species at the Bartlett Experimental Forest, New Hampshire. Using hyper-spectral image data and simulated broadband sensor data, we used spectral unmixing to quantify the abundance of sugar maple and American beech, as opposed to the more conventional approach of detecting presence or absence of discrete species classes. Stronger linear relationships were demonstrated between predicted and measured abundance for hyperspectral than broadband sensor data: R2 = 0.49 (RMSE = 0.09) versus R2 = 0.16 (RMSE = 0.19) for sugar maple; R2 = 0.36 (RMSE = 0.18) versus R2 = 0.24 (RMSE = 0.33) for beech. These results suggest that spectrally unmixing hyperspectral data to estimate species abundances holds promise for a variety of ecological studies

A generalizable method for remote sensing of canopy nitrogen across a wide range of forest ecosystems

A growing number of investigations have shown that remote sensing of foliar nitrogen (N) concentration in plant canopies can be achieved with imaging spectroscopy, or hyperspectral remote sensing, from satellite or airborne sensors. Development of this approach has been fueled by recognition that foliar N is related to a variety of ecological and biogeochemical processes, ranging from the spread of invasive species to the ecosystem effects of insect defoliation events to patterns of N cycling in forest soils. To date, most studies have focused on building site-specific foliar N detection algorithms applied to individual scenes or small landscapes that have been intensively characterized with local field measurements. However, the growing number of well-measured sites, combined with improvements in image data quality and processing methods provide an opportunity to begin seeking more general N detection methods that can be applied to a broader range of sites or to locations that lack intensive field measurements. Here, we combine data from several independent efforts in North America, Central America and Australia, to examine whether development of calibration methods to determine canopy nitrogen concentration across a wide range of forest ecosystems is possible. The analysis included data from 137 individual field plots within eight study sites for which imagery has been acquired from NASA\u27s Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and/or Hyperion instruments. The combined dataset was used to evaluate site-specific calibration results as well as results obtained with data pooled across all sites. We evaluated the accuracy of results using plot- and site-level cross-validation wherein individual plots or entire sites were withheld and used as an independent validation of the resulting algorithms. In instances where all sites were represented in the calibration, canopy-level foliar N concentration was predicted to within 7–15% of the mean field-measured values indicating a strong potential for broadly applied foliar N detection. When whole sites were iteratively dropped from the calibration and predicted by remaining data, predictions were still significant, but less accurate (7–47% of mean canopy-level N concentration). This suggests that further development to include a wider range of ecosystems will be necessary before cross-site prediction accuracy approaches that seen in site-specific calibrations. Nevertheless, we view these results as promising, particularly given the potential value of foliar N estimates, even at a reduced level of confidence, at sites for which there is no possibility of conducting field data collections