TREE

CROSS-REFERENCE TO RELATED APPLICATIONS

[001] This application claims the benefit of priority of U.S. Provisional Patent Application No. 63/270,583, titled “METHOD AND SYSTEM FOR CALCULATING CARBON UPTAKE OF A TREE”, filed October 22, 2021, the contents of which are incorporated herein by reference in their entirety.

FIELD OF THE INVENTION

[002] The present invention relates generally to calculation and characterization of plant metabolism processes. More specifically, the present invention relates to a system and method of calculating tree carbon uptake.

BACKGROUND OF THE INVENTION

[003] The rising relevance of environmental topics such as the effect of carbon emissions and global warming have presented new technological challenges, such as the need to easily, and efficiently monitor carbon emission and carbon intake. Such calculation is required for example, for determining carbon credits. Various methods and techniques for calculating carbon uptake in trees are currently available, but are substantially limited by efficiency, accuracy, specificity and/or price.

[004] For example, tree-level carbon uptake can be measured directly from leaf surfaces using an Infra-Red Gas Analyzer (IRGA) instrument, equipped with a small cuvette. While this is a direct measurement of carbon assimilation, it has the following limitations: (1) it provides instantaneous measurement only. (2) it cannot continue for more than a few minutes since conditions in the cuvette cannot fully replicate native conditions. (3) it can only represent the single leaf measured. (4) it is not useful for calculating the whole-tree carbon uptake, since a typical tree has many thousands of leaves, and it’s practically impossible to measure all of them. (5) The IRGA instrument is prohibitively expensive, and can only be operated by well-trained personnel.

[005] Forest-level carbon uptake can be calculated with the eddy covariance method based on combined IRGA and sonic anemometer measurements, taken above a forest canopy. Although this is the method of choice at the global Fluxnet network of research station, it cannot be used to calculate tree-level carbon uptake because it integrates the CO2 exchange over the canopy, mixing many different fluxes, such as carbon uptake of trees of different species, sizes, and ages; carbon uptake of other plants; and respiration from other trees, other plants, animals, and soil microbiota. In addition, this method has the limitations of (1) the eddy covariance equations have many assumptions and are hence regarded as estimations, rather than measurement; (2) IRGA and sonic anemometer measurements are valid only at certain prerequisites of site slope and wind speed; (3) these measurements are valid only for the part of the canopy covered by the instruments; and (4) The IRGA and sonic anemometer instrument are extremely expensive, require the setup of a flux-tower, and can only be operated by well-trained personnel.

[006] A cost-efficient, time-efficient, accurate and target- specific (e.g., pertaining to specific trees or plants) method of calculating carbon uptake is therefore required.

SUMMARY OF THE INVENTION

[007] Embodiments of the invention may include a method of calculating tree-level and/or forest-level carbon uptake by at least one processor. According to some embodiments, the at least one processor may employ or control a heat balance sensor, located at a stand of at least one tree, to obtain one or more heat balance measurements. The at least one processor may calculate a sap flow (SF) value, representing flow of sap in the at least one tree, based on the one or more heat balance measurements. Additionally, or alternatively, the at least one processor may receive (e.g., from an isotope spectrometer) an isotopic signature (6 ¹³ C) value of at least one portion of the at least one tree. As elaborated herein, the at least one processor may calculate a gross tree carbon uptake value, representing gross diurnal carbon uptake of the at least one tree, based on the isotopic signature value and the sap flow value. [008] According to some embodiments, the at least one processor may calculate a transpiration (T) value based on the sap flow value SF, wherein said transpiration value T represents a diurnal amount of water transpired by the at least one tree. It may be appreciated that the sap flow value SF may be equal to the transpiration value T, and the two terms may be used herein interchangeably.

[009] According to some embodiments, the at least one processor may calculate a water use efficiency (WUE) value based on the isotopic signature value. The WUE value may represent an amount of carbon assimilated as biomass in the at least one tree, in relation to an amount of water consumed by the at least one tree. As elaborated herein, the at least one processor may calculate the gross tree carbon uptake value further based on the WUE value and T value.

[0010] Additionally, or alternatively, the at least one processor may receive from one or more climatic sensors, one or more respective climatic values representing climatic conditions at a canopy of the at least one tree. The at least one processor may calculate a Vapour Pressure Deficit (VPD) value, representing VPD at the canopy of the at least one tree, based on the climatic values, the at least one processor may subsequently calculate the gross tree carbon uptake value further based on the VPD value.

[0011] Additionally, or alternatively, the at least one processor may receive one or more tree respiration coefficients. Each tree respiration coefficient may correspond to a specific type of the at least one tree, and may represent a portion of the gross tree carbon uptake value that may be respired from a specific compartment of the at least one tree as CO2. The at least one processor may then calculate a tree-scale net carbon uptake value, based on the one or more tree respiration coefficients and the gross tree carbon uptake value.

[0012] Additionally, or alternatively, the at least one processor may receive one or more bacterial respiration coefficients, representing a portion of the gross tree carbon uptake value that may be respired from the tree as CO2 due to bacterial activity in a soil. The at least one processor may then calculate the tree-scale net carbon uptake value, further based on the bacterial respiration coefficients.

[0013] Additionally, or alternatively, the at least one processor may select the at least one tree from a plurality of trees in a forest, and calculate a forest-scale carbon uptake based on the selected trees.

[0014] For example, the at least one processor may receive statistical forestation data pertaining to the plurality of trees, such as a type of the plurality of trees, a size of the plurality of trees, a number of the plurality of trees, a frequency of each tree type in the plurality of trees, and the like. The at least one processor may select the at least one tree from the plurality of trees as statistically representative of said type, size, number and frequency of the plurality of trees.

[0015] As elaborated herein, the at least one processor may subsequently calculate a forestscale, or canopy-scale sap flux value, representing diurnal sap flow of the plurality of trees, based on (i) the statistical forestation data and (ii) the sap flow value of the at least one selected tree. [0016] Additionally, or alternatively, the at least one processor may calculate forest scale transpiration value, based on (i) the forest-scale sap flux value and (ii) the statistical forestation data.

[0017] Additionally, or alternatively, the at least one processor may calculate a forest scale gross carbon uptake value, representing diurnal carbon uptake of the plurality of trees, based on (i) the forest scale transpiration value, (ii) the WUE value of the at least one tree, and (iii) the statistical forestation data.

[0018] Embodiments of the invention may include a system for calculating tree carbon uptake. Embodiments of the system may include at least one heat balance sensor, located at a stand of at least one tree; a non-transitory memory device, wherein modules of instruction code are stored; and at least one processor associated with the memory device, and configured to execute the modules of instruction code. Upon execution of said modules of instruction code, the at least one processor may be configured to employ, control or communicate with the at least one heat balance sensor, to obtain one or more heat balance measurements; calculate a sap flow value, representing flow of sap in the at least one tree, based on the one or more heat balance measurements; receive (e.g., from an isotope spectrometer) an isotopic signature (613C) value of at least one portion of the at least one tree; and calculate a gross tree carbon uptake value, representing gross diurnal carbon uptake of the at least one tree, based on the isotopic signature value and the sap flow value.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings in which:

[0020] Fig. 1 is a block diagram, depicting a computing device which may be included in a system for calculating carbon uptake according to some embodiments of the invention;

[0021] Fig. 2 is a block diagram, depicting a system for calculating carbon uptake, according to some embodiments of the invention;

[0022] Fig. 3 is a flow diagram, depicting a method of calculating carbon uptake, according to some embodiments of the invention; [0023] Figs. 4A-4D are graphs showing a comparison between carbon uptake data, in four tree species, as calculated based on an Infra-Red Gas Analyzer (IRGA) instrument (e.g., as known in the art), and carbon uptake data that was calculated according to embodiments of the invention; and

[0024] Figs. 5A and 5B are graphs showing a comparison between forest-level carbon uptake data as calculated based on the eddy covariance method above a forest canopy (as known in the art), and carbon uptake data that was calculated according to embodiments of the invention.

[0025] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

[0026] The terms “tree” and “plant” may be used herein interchangeably, and should be understood in an unlimiting manner, as indicating any type of plant (e.g., including trees, shrubs, grasses, etc.) of interest, that may perform photosynthesis. The terms “forest” and “plot” may be used herein interchangeably, and should be understood in an unlimiting manner, as indicating a location of interest where such plants are located (e.g., a forest, a plantation, a greenhouse, a field, an orchard and the like).

[0027] One skilled in the art will realize the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting of the invention described herein. Scope of the invention is thus indicated by the appended claims, rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

[0028] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention. Some features or elements described with respect to one embodiment may be combined with features or elements described with respect to other embodiments. For the sake of clarity, discussion of same or similar features or elements may not be repeated.

[0029] Although embodiments of the invention are not limited in this regard, discussions utilizing terms such as, for example, “processing,” “computing,” “calculating,” “determining,” “establishing”, “analyzing”, “checking”, or the like, may refer to operation(s) and/or process(es) of a computer, a computing platform, a computing system, or other electronic computing device, that manipulates and/or transforms data represented as physical (e.g., electronic) quantities within the computer’s registers and/or memories into other data similarly represented as physical quantities within the computer’s registers and/or memories or other information non-transitory storage medium that may store instructions to perform operations and/or processes.

[0030] Although embodiments of the invention are not limited in this regard, the terms “plurality” and “a plurality” as used herein may include, for example, “multiple” or “two or more”. The terms “plurality” or “a plurality” may be used throughout the specification to describe two or more components, devices, elements, units, parameters, or the like. The term “set” when used herein may include one or more items.

[0031] Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Additionally, some of the described method embodiments or elements thereof can occur or be performed simultaneously, at the same point in time, or concurrently.

[0032] Embodiments of the present invention may include a method and a system for determining tree-level carbon uptake. As elaborated herein, embodiments of the invention may initially calculate carbon assimilation at the tree scale, from tree water-use and wateruse efficiency. Tree-level carbon assimilation may then be upscaled to the canopy (e.g., forest) scale, to yield the forest Gross primary production. This result can be validated by upscaling of leaf photosynthesis measurements (as discussed e.g., in relation to Figs. 4A- 4D) and/or by downscaling canopy carbon uptake, calculated using the eddy covariance method (as discussed e.g., in relation to Fig. 5).

[0033] Respiratory losses related to tree respiration and bacterial activity on the forest floor and in the soil may then be calculated as a fraction of tree carbon uptake. Subsequently, net tree-level carbon uptake may be calculated as the difference between tree carbon uptake and respiratory losses.

[0034] Reference is now made to Fig. 1, which is a block diagram depicting a computing device, which may be included within an embodiment of a system for calculating tree carbon uptake, according to some embodiments.

[0035] Computing device 1 may include a processor or controller 2 that may be, for example, a central processing unit (CPU) processor, a chip or any suitable computing or computational device, an operating system 3, a memory 4, executable code 5, a storage system 6, input devices 7 and output devices 8. Processor 2 (or one or more controllers or processors, possibly across multiple units or devices) may be configured to carry out methods described herein, and/or to execute or act as the various modules, units, etc. More than one computing device 1 may be included in, and one or more computing devices 1 may act as the components of, a system according to embodiments of the invention.

[0036] Operating system 3 may be or may include any code segment (e.g., one similar to executable code 5 described herein) designed and/or configured to perform tasks involving coordination, scheduling, arbitration, supervising, controlling or otherwise managing operation of computing device 1, for example, scheduling execution of software programs or tasks or enabling software programs or other modules or units to communicate. Operating system 3 may be a commercial operating system. It will be noted that an operating system 3 may be an optional component, e.g., in some embodiments, a system may include a computing device that does not require or include an operating system 3.

[0037] Memory 4 may be or may include, for example, a Random- Access Memory (RAM), a read only memory (ROM), a Dynamic RAM (DRAM), a Synchronous DRAM (SDRAM), a double data rate (DDR) memory chip, a Flash memory, a volatile memory, a nonvolatile memory, a cache memory, a buffer, a short term memory unit, a long term memory unit, or other suitable memory units or storage units. Memory 4 may be or may include a plurality of possibly different memory units. Memory 4 may be a computer or processor non-transitory readable medium, or a computer non-transitory storage medium, e.g., a RAM. In one embodiment, a non-transitory storage medium such as memory 4, a hard disk drive, another storage device, etc. may store instructions or code which when executed by a processor may cause the processor to carry out methods as described herein. [0038] Executable code 5 may be any executable code, e.g., an application, a program, a process, task, or script. Executable code 5 may be executed by processor or controller 2 possibly under control of operating system 3. For example, executable code 5 may be an application that may calculating tree carbon uptake as further described herein. Although, for the sake of clarity, a single item of executable code 5 is shown in Fig. 1, a system according to some embodiments of the invention may include a plurality of executable code segments similar to executable code 5 that may be loaded into memory 4 and cause processor 2 to carry out methods described herein.

[0039] Storage system 6 may be or may include, for example, a flash memory as known in the art, a memory that is internal to, or embedded in, a micro controller or chip as known in the art, a hard disk drive, a CD-Recordable (CD-R) drive, a Blu-ray disk (BD), a universal serial bus (USB) device or other suitable removable and/or fixed storage unit. Data pertaining to measurements in, and at the surroundings of one or more trees may be maintained in storage system 6, and may be loaded from storage system 6 into memory 4 where it may be processed by processor or controller 2. In some embodiments, some of the components shown in Fig. 1 may be omitted. For example, memory 4 may be a non-volatile memory having the storage capacity of storage system 6. Accordingly, although shown as a separate component, storage system 6 may be embedded or included in memory 4.

[0040] Input devices 7 may be or may include any suitable input devices, components, or systems, e.g., a detachable keyboard or keypad, a mouse and the like. Output devices 8 may include one or more (possibly detachable) displays or monitors, speakers and/or any other suitable output devices. Any applicable input/output (RO) devices may be connected to Computing device 1 as shown by blocks 7 and 8. For example, a wired or wireless network interface card (NIC), a universal serial bus (USB) device or external hard drive may be included in input devices 7 and/or output devices 8. It will be recognized that any suitable number of input devices 7 and output device 8 may be operatively connected to Computing device 1 as shown by blocks 7 and 8.

[0041] A system according to some embodiments of the invention may include components such as, but not limited to, a plurality of central processing units (CPU) or any other suitable multi-purpose or specific processors or controllers (e.g., similar to element 2), a plurality of input units, a plurality of output units, a plurality of memory units, and a plurality of storage units. [0042] Reference is now made to Fig. 2, which is a block diagram, depicting a system for calculating carbon uptake, according to some embodiments of the invention.

[0043] According to some embodiments, system 10 may be implemented as a software module, a hardware module, or any combination thereof. For example, system 10 may be or may include a computing device such as element 1 of Fig. 1, and may be adapted to execute one or more modules of executable code (e.g., element 5 of Fig. 1) to calculate tree carbon uptake, as further described herein.

[0044] As shown in Fig. 2, arrows may represent flow of one or more data elements to and from system 10 and/or among modules or elements of system 10. Some arrows have been omitted in Fig. 2 for the purpose of clarity.

[0045] According to some embodiments, system 10 may include a Tree-level, Gross Carbon Uptake (TGCU) calculation module 110 (or TGCU module 110, for short). As implied by its name and elaborated herein, TGCU 110 may be configured to receive one or more input data elements (denoted elements 20A, 30A and 40A in Fig. 2), and calculate a gross carbon uptake of a specific plant or tree of interest TGCU 110A over a predefined period of time, based on the input data elements. TGCU 110A may also be referred to herein as “assimilation”, or “tree-level assimilation”.

[0046] A gross, tree-level CO2 uptake may be written as in equation Eq. 1, below:

Eg. 1

Where A (Assimilation) represents the gross, tree-level CO2 uptake TGCU 110A, in units of [CO2 grams], and T represents water transpiration in units of [H2O grams].

[0047] It may be appreciated that assimilation (A), transpiration (T) may relate to individual trees or plants. In this context, the symbols ‘A’ and ‘Atree’ may be used herein interchangeably, and the symbols ‘T’ and ‘Ttree’ may be used herein interchangeably.

[0048] Since relative humidity inside the leaves is 100%, water transpiration T can be calculated based on equation Eq. 2, below:

Eq. 2

T = g _s x VPD

[0049] In Eq. 2, g _s represents a stomatai conductance of the plant, e.g., a measure of the degree of stomatai opening. VPD represents a vapor pressure deficit, e.g., a difference between the amount of moisture in the air and how much moisture the air can hold when it is saturated, at the plant’s vicinity.

[0050] In instantaneous measurements, T and g _s are measured in units of mol H2O m’ ² s’ ¹ . VPD is thus measured in units of kilo-Pascal (kPa) / kPa, and is therefore unitless.

[0051] By integrating Eq. 1 and Eq. 2, we may obtain equation Eq. 3, below:

Eq. 3

A = T x A/(g _s x VPD)

[0052] As known in the art, A/g _s serves to calculate a plant’s intrinsic water-use efficiency (WUEi). A plant’s WUEi may be intuitively understood as a ratio between (a) the amount of CO2 that was gained or absorbed and (b) an amount of water vapor that was lost or transpired. Therefore, Eq. 3 may be rewritten as equation Eq. 4, below:

Eg. 4

A = T x WUEi/VPD

[0053] As known in the art, 6 ¹³ C is an isotopic signature, representing a ratio of stable carbon isotopes ¹³ C: ¹² C, reported in parts per thousand. As also known in the art, WUEi may be calculated based on a measurement of 6 ¹³ C in terminal branches, as elaborated in equation Eq. 5 below:

Eq. 5

WUEi = F1(6 ¹³ C)

Where Fl(-) represents the Farquhar equation.

[0054] As known in the art, the Farquhar equation may be elaborated as in Eq. 5’ below:

Eq . 5 ’

WUEi = Ca/r x { [b - A - pr * (T* /Ca)] / [b - a + (b - am) x (gs /(r x gi))] } where Ca is the atmospheric CO2 concentration in ppm (continuously published on the web); r is the ratio of the diffusivities of CO2 and water vapor in air (1.6); a, am, b and pr are the leaf-level discriminations against ¹³ C in the diffusion through the stomata (4.4%o), during dissolution and liquid phase diffusion (1.8%o), in biochemical CO2 fixation (29%o), and in photo-respiratory CO2 release (8%o), respectively; A is the tree discrimination against ¹³ C (6 ¹³ C); r* is the temperature-dependent CO2 compensation point of ca. 30-45 ppm; gs/gi is the ratio between stomatai and internal conductance to CO2 respectively. [0055] The use of 6 ¹³ C may rely on the observation that integrated 6 ¹³ C values are representative of the photo-assimilate 6 ¹³ C composition. The mean WUEi at a monthly resolution should be used in the analysis.

[0056] As known in the art, the tree transpiration value T may be calculated diumally for individual trees from Sap Flow (SF) measurements, according to equation EQ. 6, below: Eq. 6

T = F2(SF)

Where F2 is the conversion function of sap flow (SF) to transpiration (T)

[0057] Additionally, or alternatively, sap flow may be equal to transpiration (SF=T). In such embodiments, the terms sap flow and transpiration may be used herein interchangeably.

[0058] By integrating Eq. 4, Eq. 5 and Eq. 6, we may obtain equation Eq. 7, below:

Eg. 7

A = F2(SF) x F1(6 ¹³ C)/VPD

[0059] According to some embodiments, TGCU module 110 may calculate the tree-level Assimilation, or TGCU 110A according to Eq. 7:

[0060] As known in the art, SF may be obtained from, or measured by heat balance sensors. Therefore, as shown in Fig. 2, system 10 may include, or may be communicatively connected to one or more (e.g., a plurality of) heat balancing sensors 30, also referred to herein as SF sensors. Each SF sensor 30 may be configured to obtain an SF measurement 30A, and transmit SF measurement 30A to TGCU module 110, in order to calculate TGCU 110A, based on Eq. 7. SF sensors 30 may transmit SF measurements 30A to TGCU module 110 via any appropriate type of wired or wireless communication, such as a cellular data network, an Internet of Things (loT) network, and the like.

[0061] Additionally or alternatively, SF sensors 30 may be installed on a stem of each tree of a sample of trees, that may be specifically selected to capture a distribution of diameter at breast height (DBH) and height of trees growing at a plot of interest. As elaborated herein, such selection of specific sample trees or plants may serve a purpose of extrapolating carbon uptake measurements and information to a plot of forest scale.

[0062] Additionally or alternatively, system 10 may include, or may be communicatively connected to one or more (e.g., a plurality of) climatic sensors 40. Climatic sensors 40 may be located in the vicinity of the trees or plants of interest. Pertaining to the same example, the term “vicinity” may indicate that climatic sensors 40 may be located at the plot of interest, e.g., at a distance that does not exceed 50 meters (m) from trees of interest (e.g., tree upon which SF sensors 30 are installed).

[0063] As depicted in the example of Fig. 2, climatic sensors 40 may be configured to obtain or measure climatic measurement values of air humidity 40A1, pressure 40A2 and/or temperature 40A3 at the vicinity of the trees or plants of interest, and calculate (e.g., by an embedded processor 41) a VPD value 40A based on the measured humidity 40A1 pressure 40A2 and/or temperature 40A3 values, as known in the art. Climatic sensors 40 may subsequently transmit VPD 40A to TGCU module 110 via any appropriate type of wired or wireless communication.

[0064] Additionally or alternatively, climatic sensors 40 may transmit measured humidity 40A1 pressure 40A2 and/or temperature 40A3 values to TGCU module 110 via any appropriate type of wired or wireless communication, and TGCU module 110 may calculate VPD value 40A based on the measured humidity 40A1 pressure 40A2 and/or temperature 40A3 values, as known in the art.

[0065] In some embodiments, since CO2 uptake is restricted to daytime hours, TGCU module 110 may only sample or calculate VPD value 40A during daytime. Additionally, or alternatively, VPD value 40A may be a mean value of VPD during daytime.

[0066] Reference is also made to Fig. 3, which is a flow diagram, depicting a method of calculating carbon uptake by at least one processor (e.g., processor 2 of Fig. 1), according to some embodiments of the invention.

[0067] According to some embodiments, system 10 may include one or more heat balance sensors 30. In such embodiments, and as shown in step S 1005, processor 2 may employ or control at least one heat balance sensor 30, located at a stand of at least one respective tree of interest, to obtain one or more heat balance measurements 30A, as elaborated herein (e.g., in relation to Fig. 2). Additionally, or alternatively, and as shown in Fig. 2, system 10 may be communicatively connected to the at least one heat balance sensor 30. In such embodiments, processor 2 may receive the one or more heat balance measurements 30A via this communication. Additionally, or alternatively, system 10 may not include, or be communicatively connected to the one or more heat balance sensors 30. In such embodiments, processor 2 may receive the one or more heat balance measurements 30A from corresponding heat balance sensors 30 as input, e.g., via input device 7 of Fig. 1. [0068] As shown in step S1010, processor 2 may calculate an SF value 30A, representing flow of sap in the at least one tree, based on the one or more heat balance measurements. For example, heat balance sensor 30 may apply heat to a first location in a bark of a tree, and measure a temperature in the first location and in another location (e.g., vertically above the first location). Processor 2 may thus calculate flow of sap 30A, given a difference in temperature between the two locations and a known value sap heat capacitance. Additionally, or alternatively, and as shown in the example of Fig. 2, the at least one heat balance sensor 30 may include an embedded processor 31, configured to calculate SF value 30A, and may transmit calculated SF value 30A to processor 2 via appropriate wired or wireless communication.

[0069] According to some embodiments, system 10 may include an isotope spectrometer 20. In such embodiments, processor 2 may employ, or control isotope spectrometer 20 to obtain an isotopic signature (6 ¹³ C) value 20A of at least one portion of the at least one tree of interest. Additionally, or alternatively, and as shown in Fig. 2 and in step S1015, system 10 may be communicatively connected via appropriate wired or wireless communication to isotope spectrometer 20. In such embodiments, processor 2 may receive isotopic signature value 20A of the at least one portion of the tree of interest via this communication. Additionally, or alternatively, system 10 may not include, or be communicatively connected to isotope spectrometer 20. In such embodiments, processor 2 may receive the one or more isotopic signature value 20A from isotope spectrometer 20 as input, e.g., via input device 7 of Fig. 1.

[0070] As shown in step S1020, processor 2 (e.g., TGCU module 110) may calculate a gross tree carbon uptake value (e.g., TGCU 110A of Fig. 2), representing gross diurnal carbon uptake of the at least one tree, based at least in part on the isotopic signature value 20A and the sap flow value 30A (e.g., as elaborated herein, in relation to Eq. 7).

[0071] Additionally, or alternatively, processor 2 (e.g., TGCU module 110) may calculate a transpiration (T) value based on the SF value as elaborated herein, e.g., according to Eq. 6. transpiration (T) value may represent a diurnal amount of water transpired by the at least one tree of interest. Processor 2 (e.g., TGCU module 110) may also calculate a water use efficiency (WUEi) value, based on the isotopic signature value 6 ¹³ C, e.g., according to Eq. 5. The WUEi value may represent an amount of carbon that is assimilated as biomass in the at least one tree of interest, in relation to an amount of water consumed by the at least one tree of interest. As elaborated herein (e.g., in relation to Eq. 7), processor 2 (e.g., TGCU module 110) may calculate the gross tree carbon uptake value 110A further based on the WUEi value and T value.

[0072] Additionally, or alternatively, processor 2 (e.g., TGCU module 110) may receive, from one or more climatic sensors 40 one or more respective climatic values (e.g., 40A1, 40A2, 40A3), which may represent climatic conditions (e.g., temperature, humidity, pressure) at a canopy of the at least one tree, or at a vicinity (e.g., within 50m of the canopy of the at least one tree). Processor 2 (e.g., TGCU module 110) may calculate a VPD 40A value, representing VPD at the canopy of the at least one tree, based on the climatic values 40A1, 40A2 and/or 40 A3. Processor 2 (e.g., TGCU module 110) may subsequently calculate the gross tree-level carbon uptake value 110A further based on the VPD value, as elaborated herein (e.g., according to Eq. 7).

[0073] As shown in Fig. 2, system 10 may include a Tree-level, Net Carbon Uptake (TNCU) calculation module 130 (or TNCU module 130, for short). TGCU 110 may be configured to receive one or more input data elements, such as TGNU 110A and one or more correction factors 60 and calculate a net carbon uptake of a specific plant or tree of interest TNCU 130A (also referred to herein as Ntree) over a predefined period of time, based on the input data elements, as elaborated herein.

[0074] Net tree carbon uptake 130A may be calculated according to equation Eq. 8, below: Eg. 8

Ntree = Atree - Rtree - Rlitter - Rexudation

[0075] In Eq. 8, Ntree represents the net tree carbon uptake 130A; Atree represents treelevel assimilation or TGCU 110A (which may be calculated as elaborated herein by TGCU module 110, according to Eq. 7); Rtree represents tree-level respiration, by which carbon is emitted to the atmosphere, and Rlitter and Rexudation are tree-level respiratory carbon losses, that are related with bacterial activity on the forest floor, and in the soil respectively, and are commonly referred to in the art as litter and exudation.

[0076] According to some embodiments, Rtree may be calculated as a fraction or portion of Atree, which may be empirically, or experimentally selected based on a tree’s type and/or size.

[0077] In other words, system 10 may receive one or more correction factors (CF) 70 (e.g., CF 70A, CF 70B, CF 70C) that are tree respiration coefficients 70, each corresponding to a type and/or size of at least one tree of interest. In such embodiments, correction factors 70 may represent a portion or fraction of the gross tree carbon uptake value TGCU 110A that is respired from a specific compartment of the at least one tree as CO2. TNCU module 130 may calculate a tree-scale net carbon uptake value 130A based on the one or more tree respiration coefficients 70 and the gross tree carbon uptake value 110A.

[0078] Eq. 8 may therefore be rewritten as equation Eq. 9, below:

Eg. 9

Ntree = Atree (1 - CF 70A - CF 70B - CF 70C) where CF 70A represents a tree respiration coefficient, CF 70B represents a litter coefficient and CF 70B represents an exudation coefficient.

[0079] In a first approximation, and based on Eq. 8 and Eq.9, Ntree (TNCU 130A) may be calculated based on the tree aspiration (Atree) and tree respiration. In other words, Ntree may be calculated in a first approximation as Atree (1 - CF 70A). For example, a value of correction factor 70 (e.g., 70A, a tree respiration coefficient) pertaining to a specific tree type and size may be 60%, indicating that 60% of assimilated carbon is extracted from the tree by respiration. In this example, Ntree (TNCU 130A) may be calculated as Atree (1- 0.6) = 0.4 x (TNGU 110A).

[0080] According to some embodiments, TNCU module 130 may use a combination of two approaches, each based on the most validated and widely accepted formulations to reduce the uncertainty related with claculating Rtree (and subsequently, Ntree). In a first approach, TNCU module 130 may calculate Ntree as in Eq. (9), where Rtree may be represented as a function of mean annual temperature (Tmean) at a given site. This corresponds to the observation that Rtree is highly sensitive to site temperature. To ensure robustness of calculation of Ntree, TNCU module 130 may use an ensemble of models, represented by Equations 10 (denoted Eq. 10A - Eq. 10D) below, each based on empirical results, obtained by multiple studies conducted on a variety of tree species or tree types in different forest types.

Eqs.10

Eq. 10A: Ntree = Atree x (1 - 0.012 x Tmean 2 - 0.0263 x Tmean + 0.064) Eq. 10B: Ntree = Atree x (1 - 0.0008 x Tmean 2 - 0.019 x Tmean + 0.691) Eq. 10C: Ntree = Atree x (1 - 0.013 x Tmean 2 - 0.0268 x Tmean + 0.665) Eq. 10D: Ntree = Atree x (1 - 0.013 x Tmean 2 - 0.0281 x Tmean + 0.645) [0081] According to some embodiments, TNCU module 130 may combine the different results of Ntree from Eqs. 10A-10D, to calculate TNCU 130A, based on the first approach. For example, TNCU module 130 may calculate TNCU 130A as a weighted sum, or average of Ntree results from Eqs. 10A-10D.

[0082] According to some embodiments, TNCU module 130 may use a second, complementary approach for calculating Rtree, by modelling respiration of three individual tree compartment components, as elaborated in Equation Eq. 11, below:

Eg.11

Rtree = Rleaf + Rwood + Rroot

Where Rleaf, Rlwood, and Rroot represent respiration at the leaves, stem, and root compartments, respectively.

[0083] The equations for each of the tree components are Eqs. 11A-11C below:

Eq. 11 A: Rleaf = Fl 1 A(CF 70A1, Atree)

Eq. 11B: Rwood = Fl 1B(CF 70A2, Atree)

Eq. 11C: Rroot = Fl 1C(CF 70A3, Atree)

Where each of F11A, Fl IB, and F11C represents a respective function, that is based on Atree (e.g., TNGU 110A, also referred to as tree-level assimilation), and one or more corresponding correction factors 70A1, 70A2, 70A3.

[0084] Based on experimental results, functions F11A, Fl IB, and F11C and correction factors 70A1, 70A2, 70A3 may be replaced by empirical values, resulting in empirical equations 11A’-11C’ below:

Eq. 11A’: Rleaf = 0.16 x Atree

Eq. 11B’: Rwood = 0.16 x Atree

Eq. 11C’: Rroot = 10 ^A (0.87 x log (0.36 x Atree) + 0.2)

[0085] According to some embodiments, TNCU module 130 may calculate TNCU 130A as a combination of the two approaches elaborated above. For example, TNCU module 130 may calculate TNCU 130A as a mean value between (i) Ntree, as calculated based on Eqs. 10A-10D above, and (ii) (Atree-Rtree), where Rtree is calculated according to Eqs. 11, 11A, 1 IB and 11C above.

[0086] The strictest calculation of Ntree needs to exclude respiratory fluxes which occur outside the tree, e.g., those related with bacterial activity on the forest floor and in the soil, namely Rlitter and Rexudation, respectively. This calculation is elaborated herein in relation to Eq. 8 and Eq. 9.

[0087] In other words, TNCU module 130 may receive one or more bacterial respiration coefficients, representing a portion of the gross tree carbon uptake value that is respired from the tree as CO2 due to bacterial activity in a soil (e.g., 70B pertaining to litter and 70C pertaining to exudation), and may calculate the tree-scale net carbon uptake value calculate TNCU 130A, further based on the bacterial respiration coefficients as elaborated herein (e.g., according to Eq. 8 and Eq. 9).

[0088] According to experimental observations, the portion of litter carbon (e.g., 70B) that is respired back to the atmosphere as CO2 is 61 %-83%, depending on tree species. This is in line with evidence that 18% of litter carbon remains stable in the 0-10 cm deep soil layer, and up to 39% leaches as dissolved organic carbon.

[0089] According to experimental observations, the portion of root exudates that are respired back to the atmosphere as CO2 (e.g., 70C) may be calculated based on Rroot (e.g., as calculated by Eqs. 11C, 11C’), as Rexudation = Rroot / 3.55.

[0090] It has been observed that on average, litter decomposition and root exudation are tree carbon fluxes that represent between 5 % and 15% of Atree Therefore, at the whole tree scale, Rlitter and Rexudation may jointly decrease Atree by approximately 14%.

[0091] According to some embodiments, system 10 may include a Forest-scale Gross Carbon Uptake (FGCU) calculation module 150. As elaborated herein, FGCU module 150 may be configured to receive input data such as (i) TGCU 110A of trees in a plot, forest or field of interest, and (ii) statistical forestation data 50A that represents the tree population of the plot of interest, and subsequently calculate gross carbon uptake of the plot of interest (FGCU 150A) based on this input data.

[0092] According to some embodiments, FGCU module 150 may receive statistical forestation data 50A pertaining to the plurality of trees in a plot of interest, including for example: an identification (e.g., an ID number) of each tree of the plurality of trees, a type of the plurality of trees, a size (e.g., height, breadth, etc.) of one or more (e.g., each) of the plurality of trees, a total number of the plurality of trees, a number of each type of trees in the plurality of trees, and the like. In some embodiments, FGCU module 150 may receive statistical forestation data 50A via input device 7 of Fig. 1. Additionally, or alternatively, FGCU module 150 may receive statistical forestation data 50A via wired or wireless communication from one or more computing devices 50 that may be located at the plot of interest, e.g., installed on one or more trees of the plurality of trees.

[0093] According to some embodiments, FGCU module 150 may select a subset of trees (e.g., at least one tree) from the plurality of trees as statistically representative of said type, size, and number of the plurality of trees, based on an underlying task.

[0094] For example, system 10 may be utilized to calculate carbon uptake of specific types of trees in a plot. In this example, FGCU module 150 may only relate to TGCU 110A of trees of the determined type, having statistically representative size as indicated by statistical forestation data 50A.

[0095] Additionally, or alternatively, system 10 may be utilized to calculate carbon uptake of an entire tree population in a plot. In this example, FGCU module 150 may relate to TGCU 110A of trees, having statistically representative size and frequency of population, as indicated by statistical forestation data 50A.

[0096] According to some embodiments, FGCU module 150 may calculate a canopy scale, or forest-level CO2 uptake by accumulating or summing tree-level uptake TGCU 110A of a plurality of individual trees, as elaborated above (e.g., in relation to Eq. 7). To upscale beyond the sample trees, FGCU module 150 may regard the size of all trees in the plot, both measured and unmeasured.

[0097] Sap flow SF scales with tree size, and can be expressed in relation to sapwood area, as written in Eq. 12, below:

Eq.12

SFD = Sd(SF)*l,000/Asw

[0098] In Eq. 12, ‘S’ represents summation over the plurality of individual trees; ‘d’ is a duration (e.g., in days) over which the calculation of Eq. 12 is performed; SF is the sap flow for each individual tree (e.g., SF 30A obtained from heat balancing sensors 30, as elaborated herein); ‘ Asw’ [cm ² ] is the sapwood area of each individual tree; and SFD is a diurnal sap flux density [cm ³ / day x cm ² ], hence SF in kg hr-1 multiplied by 1,000) and. The canopy transpiration flux is calculated, in turn, from SFD rates measured in individual trees. The mean SFD is then multiplied by the total sapwood area per hectare, EAsw.

[0099] FGCU module 150 may be configured to calculate Breast-Height Diameter (DBH) distribution based on statistical forestation data 50A (e.g., from forest inventory surveys) as elaborated in Eq. 13, below: Eq.13

SAsw = sd/ Sf x S (f x ADBH)

[00100] In Eq. 13, ‘sd’ is the stand density (e.g., [number of trees / hectar]); is the frequency of a DBH class (e.g., in 1 cm increments); and ADBH is the sapwood area of a tree at a certain DBH class, considering a measured sapwood depth of 6 cm below the cambium.

[00101] In other words, FGCU module 150 may be configured to (a) categorize trees of a plot of interest, based on tree type and size (e.g., sap wood area Asw); (b) calculate a total sap wood area of trees in the plot or forest; (c) calculate sap flow density (SFD) based on TGCU 110A (of individual, statistically representative trees) and the frequency of each tree category.

[00102] FGCU module 150 may subsequently calculate a total (e.g., forest-scale) SF value, representing diurnal sap flow of the plurality of trees, based on (i) the statistical forestation data and (ii) the sap flow value of the at least one selected tree. Additionally, or alternatively, FGCU module 150 may calculate a forest scale gross carbon uptake value FGCU 150A, representing diurnal carbon uptake of the plurality of trees, based on (i) the forest scale transpiration value, (ii) the WUE value of the at least one tree, and (iii) the statistical forestation data.

[00103] For example, FGCU module 150 may calculate the forest-scale SF value based on SFD, multiplied by the total sap wood area. According to some embodiments, FGCU module 150 may subsequently utilize Eq. 7 to calculate gross carbon uptake (FGCU 150A) of the plot of interest based on the calculate total sap flow SF.

[00104] Additionally, or alternatively, FGCU module 150 may calculate diurnal values of canopy-scale (e.g., forest-level) transpiration (T) , based on (i) the forest-scale sap flux value and (ii) the statistical forestation data. FGCU module 150 may subsequently multiply transpiration (T) by WUE which may also be calculated at a diurnal resolution, to produce the gross canopy-scale CO2 uptake FGCU 150A as explained here (e.g., in relation to Eq. 4).

[00105] According to some embodiments, system 10 may include a carbon credit calculation module 170. Carbon credit calculation module 170 may be configured to receive at least one selected configuration 80, and calculate a net carbon uptake of one or more trees or plants, as a carbon credit value 170A, based on the selected configuration 80. [00106] For example, the at least one selected configuration 80 may require to calculate carbon credit 170A in relation to a specific tree. In such configuration, carbon credit value 170A may be substantially equal to tree-level net carbon uptake value 130A, as elaborated herein.

[00107] In another example, the at least one selected configuration 80 may require to calculate carbon credit 170A in relation to trees of a specific type, in a plot of interest. In such configuration, carbon credit module 170 may calculate carbon credit value 170A by scaling net carbon uptake values 130A of specific trees of the type of interest, in the plot of interest, according to forestation statistic data 50A.

[00108] In yet another example, the at least one selected configuration 80 may require to calculate carbon credit 170A in relation to all trees in a plot of interest. In such configuration, carbon credit module 170 may calculate carbon credit value 170A as a net value of forestlevel carbon uptake 170B. For example, carbon credit module 170 may calculate net forestlevel carbon uptake value 170B by scaling net carbon uptake values 130A for all types of trees in the plot of interest, according to forestation statistic data 50A.

[00109] Reference is now made to Fig. 4, which is a graph showing a comparison between carbon uptake data, in four tree species, as calculated based on an IRGA instrument, as known in the art, and carbon uptake data that was calculated according to embodiments of the invention. Figs. 4A-4B respectively present tree-level carbon uptake along two consecutive years (October 2017-S eptember 2018) in four respective tree types or species (Pinus halepensis, Quercus calliprinos, Cupressus sempervirens, and Ceratonia siliqua) in Yishi Forest, Israel. Black circles are values calculated based on sap flow and intrinsic wateruse efficiency dynamics according to embodiments of the invention, as elaborated herein. Lines represent values upscaled from photosynthesis measurements on leaves.

[00110] As shown in Figs. 4A-4D, tree-level carbon uptake was calculated for four key Mediterranean forest tree species (Pinus halepensis, Quercus calliprinos, Cupressus sempervirens, and Ceratonia siliqua). Calculation was based on monthly measurements in Yishi Forest, Israel, along two consecutive years (October 2017 -September 2018). We compare (i) the tree Carbon uptake values calculated using tree water-use and water-use efficiency according to embodiments of the invention, to (ii) upscaling of leaf-scale photosynthesis measurements performed simultaneously on the same trees. Biennial curves showed the expected seasonal behavior of trees, with peak carbon uptake in late winter-early spring, and low carbon uptake in late summer-early fall in response to the seasonal changes in soil water availability. Seasonal responses were high in the conifers (Pinus and Cupressus), which are relatively shallow-rooted and tall, milder in the broadleaf Quercus, which is shorter and with deeper roots, and low in the deep-rooted Ceratonia. Overall, estimates using methods of the present invention were in close agreement with upscaled leaf photosynthesis measurements, typically within 10% of each other. Exceptions were for Pinus in March 2017 and for Cupressus in December 2017. In the first case, there was an under-estimation, and in the second -an over-estimation. Still, the annual Carbon uptake was within 15% of the leaf upscaling calculation for all species.

[00111] Reference is now made to Figs. 5A and 5B, which are graphs showing a comparison between forest-level carbon uptake data as calculated based on the eddy covariance method above a forest canopy (as known in the art), and carbon uptake data that was calculated according to embodiments of the invention. Figs. 5 A and 5B depict canopylevel carbon uptake (GPP, gross primary productivity in grams of carbon / forest area (m ² ) per day) of Pinus halepensis in Yatir forest in 2005 (a) and in 2009-2010 (b). Black lines represent values calculated by upscaling tree Carbon uptake calculated based on sap flow (SF) and intrinsic water-use efficiency dynamics. Grey Fines represent values calculated by eddy-covariance (EC) from micro-meteorological measurements.

[00112] As shown in Figs. 5A and 5B, diurnal tree carbon uptake calculation using tree water-use and water-use efficiency by embodiments of the invention as elaborated herein was performed for Pinus halepensis trees in Yatir forest, Israel, for 2005 and 2010. Values at the tree scale were upscaled to the canopy scale and were compared to the canopy-scale GPP estimation using the eddy-covariance method. The two methods were highly correlated at all times (GPPSF = 0.99 x GPPEC, r2 = 0.78, RMSE = 0.82, n = 457 days), evidencing the validity system 10 in evaluating tree carbon uptake.

[00113] Embodiment of the invention may include a practical application for calculating gross and/or net carbon uptake of one or more plants, trees and/or plant types in a plot of interest. It may be appreciated that such data may be fundamental for determining various ecological (e.g., carbon uptake) and/or economic characteristics (e.g., carbon credits) of an environment of interest.as elaborated herein, embodiment of the invention may be employed to calculate this information in a manner that is cost-efficient, time-efficient, more accurate and more target- specific (e.g., pertaining to specific trees or plants) in relation to currently available systems of carbon uptake assessment.

[00114] Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Furthermore, all formulas described herein are intended as examples only and other or different formulas may be used. Additionally, some of the described method embodiments or elements thereof may occur or be performed at the same point in time.

[00115] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents may occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

[00116] Various embodiments have been presented. Each of these embodiments may of course include features from other embodiments presented, and embodiments not specifically described may include various features described herein.