Total Canopy Research Articles

Assessment of canopy size using UAV-based point cloud analysis to detect the severity and spatial distribution of canopy decline

This study aimed to validate the use of UAV-based point cloud analysis to detect canopy decline severity and its spatial distribution in vineyards.A new approach to assess canopy decline, caused by Eutypa dieback-like symptoms, using unmanned aerial vehicle (UAV) remote sensing was compared with ground visual assessment in the vineyard. Canopy point cloud captured by UAV-based imagery during the growing season was analysed by a customized program to determine canopy decline severity and spatial distribution in a symptomatic Shiraz vineyard in Eden Valley, South Australia. Experienced assessors performed a ground visual assessment in the vineyard at E-L stage 15. k-means clustering was used to detect reduced canopy volume due to Eutypa dieback-like symptoms. Results from point cloud analysis showed that 12.5 % of the total canopy length in the vineyard had Eutypa dieback symptoms while the ground visual assessment detected 11.4 %. Confusion matrix results showed an accuracy of 87.4 % and a kappa coefficient of 0.43 compared with ground visual assessments. Additionally, automatic analysis of the point cloud was quicker than the ground visual assessment and generated precise geographic coordinates of the symptomatic canopy sections. Point cloud analysis can detect Eutypa dieback-like symptoms and its spatial distribution with 87.4 % accuracy, compared with the ground assessment. Similar to ground visual assessment, E-L stage 15 appears to be a suitable stage to apply point cloud analysis to make Eutypa dieback-like symptom assessments. Grapevine canopy decline, caused by various factors such as Eutypa dieback and inadequate management, can cause yield reduction and threaten vineyard longevity. Compared with tedious ground visual assessments, point cloud analysis can accelerate the assessment of canopy decline in vineyards and help with the planning of remedial practices using precise geographic coordinates of the affected sections.

State of the State Tree: Historical and Modern Ecology of Kukui (Candlenut, Aleurites Moluccanus) in Hawai‘i

Kukui was an important element to indigenous Hawaiian agroforestry and retained some of its importance throughout Hawai‘i's history. We examine the historical ecology and trends of kukui, including a review of the ethnobotany. We use current and historical remote imagery to map kukui canopy on the five largest Hawaiian Islands. Kukui is still widespread through the state, being a significant component in many novel low-land forests. However, kukui is declining, having lost an average of ∼58% of total canopy cover over the last 70 years. Spatial trends suggest that kukui likely did not spread much following the large-scale shifts in Hawaiian socio-ecosystems that accompanied the arrival of colonial powers. We suggest that the footprint of kukui in Hawai‘i closely approximates the extent of indigenous agroforestry and forest alteration.

Error Estimates of Double-Averaged Flow Statistics due to Sub-Sampling in an Irregular Canopy Model

Exploration of the flow inside the roughness sublayer often suffers from sub-sampling of its complex three-dimensional and non-homogeneous flow fields. Based on detailed particle image velocimetry within a randomly-ordered canopy model, we analyze the potential differences between single-location flow statistics and their spatially-averaged values. Overall, higher variability exists inside the canopy than above it, and is two to four times higher than found inside similar, however ordered, canopy arrangements. The local mean absolute percentage error (MAPE), vertically averaged within three different regions (below, above, and at canopy height), provides a measure for quantifying and characterizing the spatial distribution of errors for various flow properties (mean velocity and stresses). We calculated the value of MAPE at predefined farthest-locations based only on geometric considerations (i.e., farther away from surrounding roughness elements), as commonly done in the field. Interestingly, most of the vertical profiles at the farthest locations lie within the interquartile range of the measured spatial variability for all studied flow and turbulent properties. Additionally, our results show that, for at least 23% of the total canopy plan area, the double-averaged streamwise velocity component and its variance inside the canopy can be reproduced from a single measured profile for which the value of MAPE does not exceed 25%. These regions also constitute most of the farthest locations. The property that exhibits the highest MAPE value inside the canopy is the Reynolds stress (up to $$130\%$$ ); however, these errors are dramatically reduced in the upper half of the canopy. Furthermore, at the canopy interface and above it, the errors rarely exceed $$20\%$$ . The variability is also manifested in the computed integral length scales. The single-point velocity autocorrelation always underestimates the length scales obtained from the two-point statistics. These findings have implications for canopy flow and transport modelling inside the roughness sublayer and can help explain and evaluate the source of discrepancies between measurements and transport models.

Arthropods are not declining but are responsive to disturbance in the Luquillo Experimental Forest, Puerto Rico

A number of recent studies have documented long-term declines in abundances of important arthropod groups, primarily in Europe and North America. These declines are generally attributed to habitat loss, but a recent study [B.C. Lister, A. Garcia, Proc. Natl. Acad. Sci. USA 115, E10397-E10406 (2018)] from the Luquillo Experimental Forest (LEF) in Puerto Rico attributed declines to global warming. We analyze arthropod data from the LEF to evaluate long-term trends within the context of hurricane-induced disturbance, secondary succession, and temporal variation in temperature. Our analyses demonstrate that responses to hurricane-induced disturbance and ensuing succession were the primary factors that affected total canopy arthropod abundances on host trees, as well as walkingstick abundance on understory shrubs. Ambient and understory temperatures played secondary roles for particular arthropod species, but populations were just as likely to increase as they were to decrease in abundance with increasing temperature. The LEF is a hurricane-mediated system, with major hurricanes effecting changes in temperature that are larger than those induced thus far by global climate change. To persist, arthropods in the LEF must contend with the considerable variation in abiotic conditions associated with repeated, large-scale, and increasingly frequent pulse disturbances. Consequently, they are likely to be well-adapted to the effects of climate change, at least over the short term. Total abundance of canopy arthropods after Hurricane Maria has risen to levels comparable to the peak after Hurricane Hugo. Although the abundances of some taxa have declined over the 29-y period, others have increased, reflecting species turnover in response to disturbance and secondary succession.

Sensitivity of Estimated Total Canopy SIF Emission to Remotely Sensed LAI and BRDF Products

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides new possibilities to estimate terrestrial gross primary production (GPP). To mitigate the angular and canopy structural effects on original SIF observed by sensors (SIF obs ), it is recommended to derive total canopy SIF emission (SIF total ) of leaves within a canopy using canopy interception ( i 0 ) and reflectance of vegetation ( R V ). However, the effects of the uncertainties in i 0 and R V on the estimation of SIF total have not been well understood. Here, we evaluated such effects on the estimation of GPP using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model. The SCOPE simulations showed that the R 2 between GPP and SIF total was clearly higher than that between GPP and SIF obs and the differences in R 2 ( Δ R 2 ) tend to decrease with the increasing levels of uncertainties in i 0 and R V . The resultant Δ R 2 decreased to zero when the uncertainty level in i 0 and R V was ~30% for red band SIF (RSIF, 683 nm) and ~20% for far-red band SIF (FRSIF, 740 nm). In addition, as compared to the TROPOspheric Monitoring Instrument (TROPOMI) SIF obs at both red and far-red bands, SIF total derived using any combination of i 0 (from MCD15, VNP15, and CGLS LAI products) and R V (from MCD34, MCD19, and VNP43 BRDF products) showed comparable improvements in estimating GPP. With this study, we suggest a way to advance our understanding in the estimation of a more physiological relevant SIF datasets (SIF total ) using current satellite products.

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach.

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top of canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the three -dimensional spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top-of-canopy percent N and total canopy N (i.e., the total amount of N [g/m2 ] within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Our resulting maps suggest that, in contrast to top of canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

Sensitivity of Canopy Phenology to Local Urban Environmental Characteristics in a Tropical City

Canopy phenology is sensitive to variability in local environmental settings. In temperate climates, urban phenological processes and their determinants are relatively well understood. Equivalent understanding of processes in tropical urban settings is, however, less resolved. In this paper, we explore the influence of local urban environmental characteristics (that is, degree of urbanization, land cover and urban climate) on canopy phenology of two deciduous tree species (Jacaranda mimosifolia, n = 48, and Tabebuia rosea, n = 24) in a tropical city (Kampala, Uganda). Our study design involved ground monitoring and field sampling in 2017, with a focus on the dry season. We found that both species experienced significantly higher rates of canopy cover decline in heavily built-up neighborhoods (p < 0.05 for both species). Moreover, Jacaranda was more sensitive to differences in the degree of urbanization than Tabebuia, both in terms of total percentage tree canopy cover (p < 0.01) and net leaf loss (p < 0.05). Total percentage tree canopy cover for Jacaranda declined with increasing proportion of impervious cover (that is, roads and paved cover) and was positively related to relative humidity (p < 0.01), a variable correlated with soil moisture. Net leaf loss in Jacaranda increased with the decreasing proportion of pervious land cover and as nighttime air temperature increased (p < 0.01). In contrast, land cover and urban climate had no significant influence on either measure of phenological traits for Tabebuia. These results provide new evidence of the effect of urbanization on canopy phenology of different tree species in the tropics. Such knowledge offers new insights into the spatial and temporal differences in the physiological functional traits of trees and also serves as a proxy for possible species responses under future climate change.

Correcting Clear‐Sky Bias in Gross Primary Production Modeling From Satellite Solar‐Induced Chlorophyll Fluorescence Data

Key Points A practical approach is proposed to correct clear‐sky bias in GPP estimation from satellite clear‐sky SIF data The reduction in GPP due to the decreasing PAR is partly compensated by enhancement of light use efficiency under cloudy conditions Global terrestrial GPP is obtained from total canopy SIF emission after correcting clear‐sky bias

A study of tree crown characteristics and their cooling effects in a subtropical city of Australia

Trees have been found to have significant cooling effect on outdoor thermal environment. This study explores the characteristics of a tree component (crown) that accounts for a large portion of the cooling effect. A field measurement was conducted in the Gold Coast, Australia, which has a subtropical climate (Cfa), according to the Köppen climate classification. The characteristics of the tree crown were indexed by its crown diameter, crown height, sky view factor (SVF), and leaf area index (LAI), based on which four new indicators that describe crown characteristics were proposed: gross canopy index (GCI), leaf layer index (LLI), crown volume index (CVI), and total canopy index (TCI). The former two are basic indicators and the latter two are sophisticated indicators. The results showed that the two sophisticated indicators were significantly associated with the mean radiant temperature beneath the tree crown and that increasing the value of each indicator by 10% could help reduce the mean radiant temperature by 0.67 °C (CVI) and 0.83 °C (TCI) respectively, if other predictors were fixed. Similarly, increasing the value of each basic indicator by 10% could help reduce the mean radiant temperature by 0.78 °C (GCI) and 0.066 °C (LLI) respectively, but their cooling effects were less significant than CVI and TCI. The thermal effect of the two sophisticated indicators was more significant than that of the two basic ones. Among all, TCI was found to be the best predictor of the outdoor thermal environment underneath the tree crown. This study proposes new effective indicators to quantify the cooling effects of trees and provides a rationale for plant selection in tropical/subtropical climates to achieve a more comfortable outdoor thermal environment.

Illuminating den‐tree selection by an arboreal mammal using terrestrial laser scanning in northern Australia

AbstractThere has been a significant decline in arboreal mammals in northern Australia, especially in the lower rainfall region of the tropical savannas. Currently, we lack a fundamental understanding of the habitat requirements of these species to prevent further declines. We investigated how variation in habitat structure influences den‐tree selection by an arboreal, hollow‐dwelling marsupial, the savanna glider (Petaurus ariel; Gould, 1842), in northern Australia from two populations at the climatic extremes of the species’ geographic range. We used traditional habitat surveys complemented by advanced terrestrial Light Detection And Ranging (LiDAR) technology to compare site habitat structure and subsequent den‐tree selection by P. ariel. Canopy height, total canopy cover and tree size were positively correlated with rainfall. At the higher rainfall site, P. ariel selected larger trees for denning than neighbouring trees; mean trunk diameter at breast height was 53.4 cm (95% CI: 49.6–56.8) and 33.8 cm (95% CI: 30.0–37.6), for den and neighbouring trees respectively. At the lower rainfall site, P. ariel den trees were no larger than neighbouring trees but were more likely to be Eucalyptus tectifica than any other available tree species. At both sites, P. ariel selected den trees that were more likely to be hollow bearing (through larger tree size or specific tree species). We found terrestrial LiDAR to be a useful tool for mapping fine‐scale variation in habitat structure which enabled us to account for variation in den‐tree selection between sites. However, we remained dependent on traditional habitat surveys to count hollows and identify tree species. With a better understanding of the relationship between tree size and den‐tree selection, future studies could use terrestrial LiDAR to map the probability of den‐tree availability for hollow‐dwelling species at a landscape scale. We emphasize the importance of protecting hollow‐bearing eucalypt trees for the conservation of arboreal mammals in northern Australia.

Higher canopy transpiration rates induced dieback in poplar (Populus × xiaozhuanica) plantations in a semiarid sandy region of Northeast China

Poplar (Populus × xiaozhuanica) plantations play an important role in controlling desertification in semiarid sandy regions of Northeast China, but their dieback occurs frequently in extreme drought years due to greater water loss by transpiration than water uptake. However, little is known about dynamics of canopy transpiration in poplar plantations, which limits our understanding of dieback mechanisms and proper management of these poplar plantations. Here, canopy transpiration and canopy conductance in 18-year-old poplar plantations were quantified by sap flow measurements in combination with monitoring of concurrent environmental variables during two consecutive growing seasons in normal and wet years (2018 and 2019). Results showed that daily canopy transpiration averaged 1.2 mm d−1 (between 0.3 and 1.9 mm d−1) and 1.5 mm d−1 (between 0.2 and 2.4 mm d−1) in 2018 and 2019, respectively. Solar radiation explained more variability of daily canopy transpiration than vapor pressure deficit (VPD) in both years, indicating that canopy transpiration was more controlled by radiation than by VPD. Total canopy transpiration during the growing seasons in 2018 and 2019 was 184.1 mm and 235.9 mm, respectively, accounting for 47.1 % and 44.2 % of precipitation over the same period. Sum of canopy transpiration, soil evaporation and change in soil water storage was higher than precipitation in most months, indicating that trees took up water from deep soil layer (>1.0 m) and groundwater. Additionally, canopy conductance averaged 1.4 m s−1 and 1.9 m s−1 in 2018 and 2019, respectively, and decreased significantly with increasing VPD. However, sensitivity of canopy conductance to VPD decreased from 0.62 in 2018 to 0.27 in 2019, indicating a shift from more to less strict stomatal regulation. These findings indicate that poplar plantations are vulnerable to dieback during extreme drought years with decline in groundwater level due to utilization of groundwater for higher canopy transpiration rate.

Field assessment of a newly-designed pneumatic spout to contain spray drift in vineyards: evaluation of canopy distribution and off-target losses.

The efficacy and environmental sustainability of pesticide application largely depend on maximizing target coverage, while minimizing off-target losses. Recently, laboratory-based measurements were used to develop new cannon-type spout to increase the droplet size spectra produced by a pneumatic vineyard sprayer. The study described below evaluated the effectiveness of the new device to reduce off-target losses (both in-field and off-field ground losses), and to distribute an adequate canopy spray. Field trials were conducted to measure canopy spray deposition, canopy coverage, and off-target losses from a multiple-row pneumatic sprayer equipped with newly-designed spout under three different positional configurations. The configurations were defined by the variation of liquid release positions from the inner to the outer part of the cannon-type spout: conventional, alternative, and extreme. Each configuration was tested in a vineyard by applying a solution of water and yellow-dye tracer. It was confirmed that the increased droplet size corresponding to the alternative and extreme liquid release positions has no effect on total canopy deposition or coverage. The alternative and extreme configurations produced reduced off-field losses, up to 75% and 83%, respectively, by increasing the droplet size spectra. These reduced off-field losses imply increased in-field losses of 13% and 16%, respectively. The newly-designed pneumatic spout offers the first effective option for environmentally-friendly pneumatic spray pesticide application with the guarantee of canopy spray deposition and coverage levels similar to those obtained with conventional pneumatic application. © 2020 Society of Chemical Industry.

A research on the botanical composition of Çamlıhemşin-Palovit Plateau

The aim of this study was to determine the rate of botanical composition, canopy covering of plants and the degree of pasture.of the Palovit plateau of Çamlıhemşin district of Rize province, In 2019, 112 plant samples were collected from the lines taken by the Loup method as a result of the field studies carried out in July, when the plateau reached the climax stage of the pasture vegetation. A total of 25 taxa belonging to 22 genus and 15 families were identified as 10 monocotyl and 15 dicotyl. In the research area, from the families are important in terms of botanical composition in determining the status of pastures according to the quality of pasture is represented by Poaceae family 6 taxa and 54.98 % and Fabacaeae family a very low with 1 taxa and 2.88 %. In the research, total botanical composition ratio of 13 families including 18 other taxa was found to be 42.14 %. As a result of the research, 70.75 % of the total canopy cover rate of plants; pasture were found to be weak according to the calculated 2.383 pasture degree.

Rangeland canopy cover estimation using Landsat OLI data and vegetation indices in Sabalan rangelands, Iran

Vegetation canopy cover is an important biophysical indicator for monitoring rangeland condition and rangeland management. The main purpose of this study is to assess the capability of Landsat 8 (OLI) image-derived vegetation indices (VIs) to estimate the vegetation canopy cover (CC) in Sablan rangelands. Field CC measurement was performed using the transect-quadrats method in 12 selected sites on the study area according to three vegetation life-forms canopy cover including, Forbs (FCC), Grasses (GCC), and Shrubs (SHCC) along with a combination of three life-forms as Total canopy cover (TCC). The estimated CCs were correlated and regressed with Landsat OLI reflectance values and vegetation indices. Results revealed that all the slope-based, distance-based, and orthogonal transformation VIs had the highest significant correlations with Grass canopy cover data (mean of R2 = 0.70) at the 95% confidence level. The weakest and insignificant correlations were derived for FCC followed by SHCC. A number of VIs (with mean R2 = 0.6) significantly correlated with TCC. The results of linear regression for GCC, TCC, and SHCC indicated that the reflectance values of spectral bands and vegetation indices were convincingly regressed with CC field data having R2 values in the range of 0.72 to 0.83, while the FCC due to the third-order logarithmic regression models gained the weakest relationship with spectral data and also VIs (R2 = 0.14 and 0.42, respectively). Results of validity test of the regression models declared that the models developed for SHCC are the best predictors followed by those made for TCC, GCC, and FCC, respectively. In this study, there was not observed an obvious difference between the performances of the three groups of VIs in predicting the CC of life-forms in the studied sites. It can be concluded that the studied VIs are more strong predictors of Grass canopy cover as the dominant life-form.

Higher rates of liana regeneration after canopy fall drives species abundance patterns in central Amazonia

Abstract In tropical rainforest, most vascular plants have some capacity to resprout, and lianas are often effective resprouters after canopy fall. However, the diversity of resprouting responses of liana species and the consequence for plant persistence are poorly understood. We hypothesized that variation in regeneration among liana species causes differences in liana species abundance in tropical rainforest through differential resprouting capacity, such that liana species with higher densities produce more resprouts after canopy falls. We applied a manipulative field experiment investigating the effect of different levels of disturbance on the production of resprouts and adventitious roots in 10 liana species of the tribe Bignonieae (Bignoniaceae) with contrasting abundances in central Amazonia. We selected 15 individuals of each species and assigned the lianas to three distinct conditions: (a) total canopy fall with lianas severely damaged and detached from trees; (b) partial fall of lianas, without visible damage; and (c) intact lianas (control). We tested whether liana species regeneration patterns were related to species density. Liana species density was calculated using previous research on liana species distribution in 30 1‐ha plots systematically distributed in a 6 × 6 km2 grid at the Ducke Reserve. The number of aerial resprouts produced by lianas under the total canopy fall treatment was twice that of plants under lower levels of disturbance, while the production of adventitious roots did not differ among treatments. Liana species showed different intensities of resprouting, and species with higher average densities on the forest landscape had more resprouts after the total canopy fall treatment. Synthesis. Our results shed new light on the factors that influence liana species abundance, highlighting the role of resprouting after canopy fall and its variation among liana species. Resprouting mitigates the negative effects of canopy damage, suggesting that the impact of increased tree fall disturbances over time, which has been attributed to Amazonian forests in the literature, may increase already abundant liana species with effective resprouting capacity. We identify liana species that are more resilient to disturbance and may alter forest dynamics during climatic change.

Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence

Quantifying global photosynthesis remains a challenge due to a lack of accurate remote sensing proxies. Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of photosynthetic activity across various spatial scales. However, a global and spatially challenging estimate of terrestrial gross primary production (GPP) based on satellite SIF remains unresolved due to the confounding effects of species-specific physical and physiological traits and external factors, such as canopy structure or photosynthetic pathway (C3 or C4). Here we analyze an ensemble of far-red SIF data from OCO-2 satellite and ground observations at multiple sites, using the spectral invariant theory to reduce the effects of canopy structure and to retrieve a structure-corrected total canopy SIF emission (SIFtotal). We find that the relationships between observed canopy-leaving SIF and ecosystem GPP vary significantly among biomes. In contrast, the relationships between SIFtotal and GPP converge around two unique models, one for C3 and one for C4 plants. We show that the two single empirical models can be used to globally scale satellite SIF observations to terrestrial GPP. We obtain an independent estimate of global terrestrial GPP of 129.56 ± 6.54 PgC/year for the 2015–2017 period, which is consistent with the state-of-the-art data- and process-oriented models. The new GPP product shows improved sensitivity to previously undetected ‘hotspots’ of productivity, being able to resolve the double-peak in GPP due to rotational cropping systems. We suggest that the direct scheme to estimate GPP presented here, which is based on satellite SIF, may open up new possibilities to resolve the dynamics of global terrestrial GPP across space and time.

Evolution of evapotranspiration models using thermal and shortwave remote sensing data

Evapotranspiration (ET) from the land surface is an important component of the terrestrial hydrological cycle. Since the advent of Earth observation by satellites, various models have been developed to use thermal and shortwave remote sensing data for ET estimation. In this review, we provide a brief account of the key milestones in the history of remote sensing ET model development in two categories: temperature-based and conductance-based models. Temperature-based ET models utilize land surface temperature (LST) observed through thermal remote sensing to calculate the sensible heat flux from which ET is estimated as a residual of the surface energy balance or to estimate the evaporative fraction from which ET is derived from the available energy. Models of various complexities have been developed to estimate ET from surfaces of different vegetation fractions. One-source models combine soil and vegetation into a composite surface for ET estimation, while two-source models estimate ET of soil and vegetation components separately. Image contexture-based triangular and trapezoid models are simple and effective temperature-based ET models based on spatial and/or temporal variation patterns of LST. Several effective temporal scaling schemes are available for extending instantaneous temperature-based ET estimation to daily or longer time periods. Conductance-based ET models usually use the Penman-Monteith (P-M) equation to estimate ET with shortwave remote sensing data. A key put to these models is canopy conductance to water vapor, which depends on canopy structure and leaf stomatal conductance. Shortwave remote sensing data are used to determine canopy structural parameters, and stomatal conductance can be estimated in different ways. Based on the principle of the coupling between carbon and water cycles, stomatal conductance can be reliably derived from the plant photosynthesis rate. Three types of photosynthesis models are available for deriving stomatal or canopy conductance: (1) big-leaf models for the total canopy conductance, (2) two-big-leaf models for canopy conductances for sunlit and shaded leaf groups, and (3) two-leaf models for stomatal conductances for the average sunlit and shaded leaves separately. Correspondingly, there are also big-leaf, two-big-leaf and two-leaf ET models based on these conductances. The main difference among them is the level of aggregation of conductances before the P-M equation is used for ET estimation, with big-leaf models having the highest aggregation. Since the relationship between ET and conductance is nonlinear, this aggregation causes negative bias errors, with the big-leaf models having the largest bias. It is apparent from the existing literature that two-leaf conductance-based ET models have the least bias in comparison with flux measurements. Based on this review, we make the following recommendations for future work: (1) improving key remote sensing products needed for ET mapping purposes, including soil moisture, foliage clumping index, and leaf carboxylation rate, (2) combining temperature-based and conductance-based models for regional ET estimation, (3) refining methodologies for tight coupling between carbon and water cycles, (4) fully utilizing vegetation structural and biochemical parameters that can now be reliably retrieved from shortwave remote sensing, and (5) to improve regional and global ET monitoring capacity.

Alternate Trait‐Based Leaf Respiration Schemes Evaluated at Ecosystem‐Scale Through Carbon Optimization Modeling and Canopy Property Data

AbstractLeaf maintenance respiration (Rleaf,m) is a major but poorly understood component of the terrestrial carbon cycle (C). Earth systems models (ESMs) use simple sub‐models relating Rleaf,m to leaf traits, applied at canopy scale. Rleaf,m models vary depending on which leaf N traits they incorporate (e.g., mass or area based) and the form of relationship (linear or nonlinear). To simulate vegetation responses to global change, some ESMs include ecological optimization to identify canopy structures that maximize net C accumulation. However, the implications for optimization of using alternate leaf‐scale empirical Rleaf,m models are undetermined. Here we combine alternate well‐known empirical models of Rleaf,m with a process model of canopy photosynthesis. We quantify how net canopy exports of C vary with leaf area index (LAI) and total canopy N (TCN). Using data from tropical and arctic canopies, we show that estimates of canopy Rleaf,m vary widely among the three models. Using an optimization framework, we show that the LAI and TCN values maximizing C export depends strongly on the Rleaf,m model used. No single model could match observed arctic and tropical LAI‐TCN patterns with predictions of optimal LAI‐TCN. We recommend caution in using leaf‐scale empirical models for components of ESMs at canopy‐scale. Rleaf,m models may produce reasonable results for a specified LAI, but, due to their varied representations of Rleaf,mfoliar N sensitivity, are associated with different and potentially unrealistic optimization dynamics at canopy scale. We recommend ESMs to be evaluated using response surfaces of canopy C export in LAI‐TCN space to understand and mitigate these risks.

From Canopy‐Leaving to Total Canopy Far‐Red Fluorescence Emission for Remote Sensing of Photosynthesis: First Results From TROPOMI

AbstractSolar‐induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI), which has substantially improved spatial and temporal resolutions, will improve the global estimations of gross primary production (GPP) than previous satellite SIF data. However, the canopy‐leaving SIF observed by sensors (SIFobs) represents only a portion of the total canopy SIF emission (SIFtotal). This portion is sensitive to the canopy structure and observation direction, resulting in uncertainties in GPP estimations using SIFobs. Here we used the spectral invariant theory to derive global soil‐resistant SIFtotal (SIFtotal‐SR) from TROPOMI SIFobs and evaluated the SIFtotal‐SR performance in estimating GPP. We found that the clear differences in SIFobs between needleleaf forest and crops diminished for SIFtotal‐SR. SIFtotal‐SR increased the coefficient of determination (R2) by 0.09 and 0.11 against the flux tower instantaneous and daily GPP, respectively. This derived SIFtotal‐SR can be used to develop more robust GPP models and better constrain carbon cycle models.

Yards increase forest connectivity in urban landscapes

Tree canopy connectivity is important for supporting biodiversity. In urban landscapes, empirical examinations of habitat connectivity often overlook residential land, though yards and gardens often comprise a large portion of urban forests. We quantify structural composition (patches and paths), connectivity and fragmentation of an entire tree canopy network spanning 1220 Boston’s neighborhoods to assess the configuration of the urban forest potentially affecting tree-dependent wildlife species, such as some birds and arboreal mammals. The urban landscape was classified by land use, and residential yards were further subdivided into front yards, backyards, and corner yards. Structural composition, connectivity and fragmentation of the tree canopy was assessed using morphological spatial pattern and network analysis. Canopy metrics were then related to the land use of 349,305 property parcels. Back yard tree canopy cover was 65.23%. The majority of canopy links were on residential land (60.95% total), and particularly in backyards. Back yards contained the highest number of canopy fragments (48.65% total). Fragmentation of the canopy network peaked at ~ 23% of total canopy cover. Canopy fragmentation, distance among patches and their shape complexity were lower in neighborhoods with more tree canopy. The important role that yards have in sustaining canopy connectivity across urban landscapes poses challenges and opportunities. Urban land management and planning need to protect connectivity links within urban forests when located on private residential realm. A prioritization strategy aimed at expanding urban tree cover could focus on yards to ensure that urban landscape connectivity is maintained and increased.