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  • Review
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9 September 2026

Tree Proximity Matters: A Novel Framework for Soil Greenhouse Gas Emissions

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1
Balcarce Research Station, National Institute of Agricultural Technology (INTA), Ruta 226 Km 73.5, Balcarce 7620, Argentina
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Mekelle Agricultural Research Center, Tigray Agricultural Research Institute, Mekelle 492, Ethiopia
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Department of Land Resource Management and Environmental Protection, Mekelle University, Mekelle 231, Ethiopia
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Global Research Alliance, CLIFF-GRADS Program, Charles Fergusson Building, 38-42 Bowen St, Wellington 6011, New Zealand
Oxygen2026, 6(3), 27;https://doi.org/10.3390/oxygen6030027
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Abstract

We introduce triproximity, a conceptual framework that organizes tree–soil greenhouse gas (GHG) interactions across three spatial dimensions: (i) horizontal distance from tree stems, (ii) vertical soil profile depth, and (iii) structural position relative to tree components including the stem itself as a gas conduit. This addresses a critical and previously unquantified methodological gap in the literature. Despite the inherent spatial heterogeneity of tree-based agricultural systems, where molecular oxygen gradients structured by root macropore networks, rhizosphere demand, and canopy-mediated moisture redistribution govern CO2, N2O, and CH4 fluxes across distances of just a few meters from the stem, most studies report GHG emissions from single locations without documenting distance from trees, effectively assuming spatial homogeneity where none exists. Following PRISMA guidelines, we systematically reviewed 107 field-based studies identified through a Scopus search (December 2025) of tree-based systems published between 2010 and 2025. Only 37.4% of studies explicitly reported measurement distance from trees, a proportion that has not improved despite a nearly four-fold increase in publication volume since 2020. Through narrative synthesis, we show that CH4 uptake follows the most consistent spatial response, with higher oxidation rates in the near-tree zone across diverse system types; N2O responses are context-dependent and governed by competing substrate availability and moisture controls; and CO2 fluxes show no universal spatial pattern yet respond predictably to specific proximity dimensions once the dominant source term is identified. Stem-level gas transport remains virtually unmeasured across the dataset, likely biasing ecosystem GHG budgets systematically. We propose a minimum triproximity-based sampling protocol for five major tree-based system types and call for journals to adopt spatial reporting as a minimum submission standard. This review was not pre-registered and received no external funding.

1. Introduction

The cycling of greenhouse gases (GHGs) in soils is fundamentally regulated by molecular oxygen. Aerobic conditions favor CO2 production through root and microbial respiration and CH4 oxidation by methanotrophs, while restricted O2 availability promotes anaerobic pathways including denitrification and methanogenesis, which are the primary sources of N2O and CH4 from soils [1,2,3]. Trees alter the local oxygen regime through multiple, spatially structured mechanisms: deep root systems create macropore networks that enhance gas diffusion [4], root oxygen demand generates radial O2 gradients in the rhizosphere [5], and canopy interception modifies soil moisture and hence gas-filled porosity [6]. Consequently, both the O2 landscape and the entire GHG balance of a tree-based system are not uniform but structured around the tree itself. Distances of just a few meters from the stem can separate aerobic, CH4-consuming rhizosphere soils from wetter inter-row soils where episodic anaerobiosis drives N2O and CH4 pulses [1,7]. These spatially structured redox transitions make tree-based systems fundamentally different from row-crop or grassland systems and demand a spatially explicit measurement approach that has, to date, been largely absent from the literature.
In tree systems, these microenvironmental gradients develop progressively as trees increase their trunk diameter, plant height, and overall below- and aboveground structural complexity as they mature. Early establishment stages are characterized by root expansion and rhizosphere development, while later development stages involve sustained organic matter inputs from litter and fine root turnover, leading to long-term changes in soil physical and biochemical properties [4,6,8]. These processes reinforce tree-driven controls over soil moisture, temperature buffering, bulk density, and aeration, thereby influencing the spatial distribution of microbial activity and the GHG fluxes across both horizontal and vertical dimensions.
The integration of trees into agricultural landscapes, including orchards, agroforestry systems, shelterbelts, riparian buffers, and silvopastoral systems, provides multiple ecosystem services such as carbon sequestration, microclimatic regulation, biodiversity enhancement, and improved system resilience [9]. However, the spatial heterogeneity resulting from tree incorporation makes interpretation of soil GHG measurements more challenging, as fluxes may differ substantially across positions under the same tree canopy and from these compared to within root zones, inter-row areas, and adjacent open fields. Numerous studies have reported either decreases [10,11,12] or increases [13,14,15,16] in the fluxes of CO2, N2O, and CH4 near trees depending on species, management practices, soil water status, and environmental conditions. These contradictions are mechanistically explainable once spatial context is considered. For N2O, for example, high nitrogen inputs in intensively fertilized orchards concentrate denitrification substrate in the near-tree zone through fertigation or banding, driving elevated emissions beneath the canopy [17]; in contrast, low-input agroforestry systems dominated by plant nitrogen uptake show the opposite pattern, with lower N2O near trees where roots compete with denitrifiers for available nitrate [18]. Similarly, CH4 oxidation is enhanced near well-aerated, root-macropore-rich rhizosphere soils but suppressed in compacted inter-row zones with restricted gas diffusion [1], a distinction invisible to single-point measurement designs. These opposing responses are not contradictions but predictable outcomes of spatially structured biogeochemical processes; their apparent inconsistency in the literature is a direct consequence of ignoring the proximity dimension.
Despite the recognized importance of spatial heterogeneity in tree-based systems, most studies measuring soil GHG emissions report fluxes from a single location or from positions whose distance from trees is poorly described or not reported at all. Such a practice implicitly assumes spatial homogeneity of emissions within heterogeneous systems, potentially introducing substantial uncertainty in comparisons across studies and in the upscaling of fluxes from plot to landscape scales. Our systematic screening of the literature revealed that explicit reporting of measurement distance from trees is uncommon, and that studies employing spatial gradients or transects relative to tree position remain the exception rather than the rule [6,19,20,21,22].
Our overall objective was to address this methodological gap by introducing the concept of triproximity, a conceptual framework that considers tree–soil interactions across three spatial dimensions: (i) horizontal distance from tree stems, (ii) vertical soil profile depth, and (iii) structural position relative to tree components (soil surface, rhizosphere, and stem). This framework recognizes that GHG fluxes in tree-based systems are shaped by multi-dimensional proximity effects rather than by a single point measurement (Figure 1).
Figure 1. The triproximity framework for greenhouse gas measurements in tree-based systems. (A) Conceptual representation of the three spatial dimensions of proximity to trees influencing soil greenhouse gas fluxes showinghorizontal distance from the tree trunk (X-Axis; tree row–alleyway–open field), vertical soil depth (Y-Axis), and aboveground stem emissions relative to tree components. (B) Conceptual gradients illustrating how CO2, N2O, and CH4 fluxes may vary along horizontal and vertical proximity dimensions, highlighting the rhizosphere as a hotspot of biogeochemical activity.
The triproximity framework does not attribute spatial GHG gradients exclusively to root processes. Above-ground tree components such as canopy interception modifying soil moisture and temperature, litterfall concentrated beneath the crown, and stemflow redistributing water inputs operate along the same horizontal gradient as root density and rhizodeposition and contribute independently to the proximity signal. In practice, these drivers are rarely separable in field measurements, and the framework captures their combined spatial expression. Future studies employing experimental manipulations (e.g., litter exclusion, root trenching, shade screens placed at defined distances) could use the triproximity spatial design to partition these contributions, a research direction we consider a productive extension of the framework presented here.
We systematically reviewed soil GHG studies in tree-based systems reporting spatial proximity to trees and distance-dependent patterns, examining diverse land use systems such as commercial orchards, agroforestry, shelterbelts, and riparian environments to identify consistent spatial trends and major knowledge gaps. We discuss the implications of insufficient spatial reporting for modeling and upscaling emissions and highlight how spatially explicit measurements informed by the triproximity framework could improve the design of climate-smart tree-based agricultural systems.

2. Materials and Methods

We conducted a systematic literature review focused on soil N2O, CH4, and CO2 emission studies, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [23] to ensure scientific transparency. This systematic review was not pre-registered and no formal protocol was prepared prior to the review. The literature search used Scopus to retrieve articles from the last fifteen years. RStudio (version 4.4.3) and the rscopus v0.9 package [24] were used to support the search process.
The search was carried out in December 2025 using the following Scopus query string:
  • TITLE-ABS-KEY(“agroforestry” OR “alley cropping” OR “tree row” OR “hedgerow” OR “riparian buffer” OR “shelterbelt” OR “tree-based system” OR “silvoarable” OR “silvopastoral” OR “fruit trees” OR “woody crops” OR “orchards”) AND TITLE-ABS-KEY(“nitrous oxide” OR “methane” OR “greenhouse gas” OR “GHG flux” OR “soil gas flux”) AND TITLE-ABS-KEY(“soil” OR “nutrient cycling” OR “nitrogen cycling” OR “carbon cycling” OR “denitrification” OR “nitrification”) AND TITLE-ABS-KEY(“proximity” OR “influence” OR “tree-soil interaction” OR “effect” OR “spatial variability”) AND PUBYEAR > [start_year]
Inclusion criteria were defined a priori as follows: (i) peer-reviewed original research articles published in English between 2010 and 2025; (ii) field-based measurements of at least one of CO2, N2O, or CH4 fluxes using static closed chambers or equivalent in situ flux methods; (iii) study system containing one or more woody perennial species integrated into an agricultural or managed landscape context; and (iv) sufficient methodological detail to assess chamber placement relative to trees. Studies were excluded if they: (i) were laboratory incubation experiments, greenhouse pot studies, or purely modeling exercises without field flux data; (ii) did not report original flux measurements (reviews, meta-analyses, book chapters); (iii) lacked a digital object identifier (DOI) or accessible full text; or (iv) were conference proceedings. No geographic or climatic restrictions were applied. The screening and data extraction were performed independently by three reviewers (G.S.C., G.D. and E. D. A.), with discrepancies resolved by consensus. For each included study, the following data were extracted: publication year, geographic location, system type, GHGs measured, chamber placement description, whether distance from trees was reported quantitatively, whether distance was used as an analytical variable, and whether stem-level or subsoil (>50 cm) measurements were included. The search yielded 1680 records, of which 1305 were exact duplicates. During eligibility assessment, records were excluded based on document type and relevance criteria: 3 conference reviews, 40 review articles, 3 books, and 33 book chapters were removed, leaving 299 records for further evaluation. Subsequently, 6 records lacking DOI information, 5 conference papers, and 3 conference reviews were excluded, as were records that implicitly indicated review content in the title, studies not relevant to the topic, and laboratory incubation experiments. This process resulted in 125 potentially eligible studies. A final duplicate check identified 18 additional duplicates, yielding a final dataset of 107 studies included in the analysis (Figure 2).
Figure 2. Diagram of identified, excluded, and included studies following the PRISMA protocol. n = number of records.

3. Results

The systematic review yielded 107 studies published between 2010 and 2025 that measured soil GHG emissions in tree-based agricultural systems. The dataset spans five major system types: shelterbelts, agroforestry, orchards, silvopastoral systems, and riparian buffers. These systems were distributed across temperate, subtropical, and arid climates. Studies from East Asia (primarily China) were the most numerous, followed by Europe and North America, although tropical and subtropical regions were underrepresented relative to their global extent of tree-based land use. Table 1 summarizes the temporal, geographic, and thematic distribution of the included studies.
Table 1. Characteristics of the 107 studies included in the systematic review. The first panel describes the temporal distribution by publication year. The second panel shows the geographic distribution by region. The third panel characterizes studies by agroecosystem type. The fourth panel shows the distribution by greenhouse gas measured (CO2, N2O, CH4, or combinations thereof).
Spatial reporting practices were markedly deficient across the literature. Of the 107 studies, only 40 (37.4%) explicitly reported the distance between measurement chambers and the nearest tree; 64 studies (59.8%) provided no quantitative spatial information, effectively treating tree-based systems as spatially homogeneous units. A further 3 studies (2.8%) offered qualitative positional descriptions only (e.g., ‘under canopy’ or ‘tree row’). Reporting varied markedly by system type: shelterbelt studies consistently incorporated spatial gradients—with several employing transects extending beyond 100 m from tree rows—while orchard fertilization trials rarely documented chamber position despite inherently spatial management practices. Geographic differences were also pronounced: studies from North America reported spatial context more frequently than those from East Asia, suggesting that methodological conventions, rather than ecological constraints, drive current reporting practices.
Analytical engagement with spatial information was limited even among studies that did report distances. Only 32 studies (29.9%) included distance as an explanatory variable in their analyses, and just 11 (10.3%) employed explicit spatial gradients with three or more sampling positions. Twenty-one studies (19.6%) used pairwise comparisons between two fixed positions (e.g., tree row vs. alley center). Vertical sampling below 50 cm was rare, recorded in only 7 studies (6.5%), and stem-level flux measurements were virtually absent across the entire dataset, with a single study (0.9%) reporting N2O fluxes from tree trunks. A temporal analysis revealed that although the absolute number of publications increased sharply after 2020 (77.6% of all included studies published between 2021 and 2025), the fraction explicitly reporting measurement distance from trees did not increase proportionally, indicating methodological stagnation. The full breakdown of spatial reporting characteristics is presented in Table 2. The 11 studies that met criteria for spatially explicit reporting consistent with the triproximity framework are identified in Table 3.
Table 2. Summary of spatial reporting practices across the 107 studies included in the systematic review. The upper panel describes how studies reported (or failed to report) measurement distance from trees. The lower panel describes the degree to which distance was used as an analytical variable, the extent of vertical soil sampling, and the occurrence of stem-level GHG measurements. Percentages are calculated relative to the total number of included studies (n = 107).
Table 3. The “Golden Eleven”: studies from the reviewed literature that explicitly reported GHG flux measurements across multiple spatial positions consistent with the triproximity framework, documenting at least horizontal distance from trees, soil depth, and system structural context. GHG: greenhouse gas measured. H = tree height. ↓ = decrease; ↑ = increase.
Proximity-dependent patterns of GHG fluxes differed markedly among gases. Methane uptake showed the most consistent spatial response, with higher oxidation rates near trees documented across diverse climates and system types, most likely reflecting root-mediated improvements in soil aeration and enhanced methanotrophic activity in the rhizosphere. Nitrous oxide emissions exhibited context-dependent responses: elevated near trees in nitrogen-rich or high-moisture systems, but reduced or unchanged in systems dominated by plant nitrogen uptake or improved drainage. Carbon dioxide fluxes showed no consistent directional pattern. The spatial patterns identified for each gas are summarized in Table 4.
Table 4. Summary of reported spatial patterns of soil CO2, N2O, and CH4 fluxes in relation to tree proximity across the 107 studies. Reference numbers correspond to the reference list.

4. Discussion

4.1. Implications of Spatial Heterogeneity Omission

The widespread omission of spatial information in studies of GHG emissions from tree-based systems represents a critical methodological limitation. Tree–soil interactions are inherently spatial processes governed by gradients in root density, organic matter inputs, canopy shading, and soil moisture redistribution [5,6]. Ignoring these gradients assumes homogeneity where none exists and obscures the mechanisms controlling GHG production and consumption. Spatial heterogeneity in soil properties is a defining feature of agroforestry and orchard systems, where tree influence zones create patchy distributions of carbon and nitrogen availability [45].
Our findings indicate that experimental design choices, rather than logistical constraints, drive the lack of spatial reporting. Many studies prioritize treatment comparisons over spatial characterization, placing chambers at representative points without documenting their position relative to trees. This practice may yield valid within-experiment comparisons but undermines cross-study synthesis and predictive model development. Previous syntheses have emphasized that spatially explicit measurements are essential for scaling soil GHG fluxes from plot to landscape levels [2,22].
A further dimension of the omission problem is geographic. The dominance of Chinese studies in this dataset (35.5%; Table 1), concentrated in fruit tree monocultures under intensive fertilization, means that the available evidence on proximity-dependent GHG patterns is heavily weighted toward high-input, nitrogen-saturated systems. Of the 38 Chinese studies in this dataset, 26 (68.4%) were conducted in fertilized fruit tree monocultures (mainly apple, citrus, and pear orchards) with reported nitrogen application rates typically exceeding 200 kg N ha−1 yr−1, substantially above global averages for rainfed agroforestry or silvopastoral systems. North American and European studies, which report spatial context more frequently, are disproportionately represented among the Golden Eleven (Table 3). This geographic imbalance in methodological rigor means that generalizations about proximity effects, particularly for N2O, may reflect the nitrogen-rich conditions of intensively managed East Asian orchards rather than the full range of tree-based agricultural contexts globally. Future triproximity-based studies should prioritize spatially explicit designs in underrepresented regions, particularly tropical agroforestry systems in sub-Saharan Africa and South/Southeast Asia, where tree-based land use is extensive and proximity effects on GHG emissions remain virtually uncharacterized.

4.2. Methane Uptake Patterns

The consistent enhancement of methane uptake near trees suggests that tree-mediated improvements in soil aeration and microbial community structure create favorable conditions for methanotrophic activity. In aerobic soils not permanently flooded, negative CH4 fluxes are expected, indicating net consumption [46], unless a fermentation source is present such as fresh cattle feces [47], sewage sludge [48], or organic waste.
Tree roots can increase soil porosity and oxygen diffusion, thereby promoting methane oxidation [1]. Similar patterns have been reported in agroforestry systems where tree rows function as hotspots of methane consumption due to enhanced microbial activity and altered soil physical structure [49]. These patterns have been confirmed in subtropical agroforestry systems with good soil aeration conditions [50].
Studies in temperate agroforestry and shelterbelt systems have consistently documented higher CH4 uptake near trees [32,36,37]. However, some studies in olive and litchi orchard systems have reported less consistent patterns [38,39], suggesting that species-specific root characteristics and management practices can modify the magnitude of methane uptake.
Framed within the triproximity dimensions, the CH4 uptake patterns reported across the Golden Eleven (Table 3) reveal a consistent horizontal proximity signal: uptake rates in the near-tree zone (0–3 m) were systematically higher than in mid-alley or open-field positions in all shelterbelt and agroforestry studies that reported explicit distances [17,33,40]. The vertical dimension adds a further layer of nuance: Lang et al. [29] demonstrated that CH4 diffusion rates declined with depth due to moisture-limited gas transport below 30 cm, meaning that surface-only measurements overestimate net oxidation at sites where subsoil anaerobiosis partly offsets surface uptake. The structural dimension represents the least quantified pathway for CH4 in agricultural systems, and its absence from all but one study in this dataset likely biases ecosystem CH4 budgets toward net-sink estimates [10,11].

4.3. Nitrous Oxide Response Complexity

In contrast, nitrous oxide responses are governed by competing controls of carbon supply, nitrogen availability, and soil moisture, resulting in divergent patterns across systems. In nitrogen-rich systems, increased litter inputs and rhizodeposition can stimulate denitrification and elevate N2O emissions near trees, whereas in nitrogen-limited systems, tree uptake may reduce nitrate availability and suppress emissions [2,51]. The addition of fertilizers, animal excreta, and plant residues increases the concentration of mineral nitrogen (NO3− and NH4+) in the soil, thereby driving N2O emissions [47,52]. A study in a pecan orchard in southern New Mexico, USA, found that soil nitrate and moisture influenced N2O emission due to fertigation application, with denitrification as the dominant mechanism [53].
Studies in coffee shade systems, cacao stands, and cork oak forests have reported higher N2O emissions near trees [18,40,41], while shelterbelt studies have documented lower emissions near trees [32,37]. Orchard systems show variable responses depending on management intensity and nitrogen fertilization practices [17,42,43].
A related consideration concerns nitrogen-fixing tree species, common components of tropical agroforestry and silvopastoral systems. Soil N2O flux measured by static chambers reflects the subsequent nitrification and denitrification of fixed nitrogen once it enters the soil mineral pool. In high-moisture conditions, elevated N2O near nitrogen-fixing tree rows would therefore be expected because of enhanced substrate availability. The triproximity horizontal gradient design is well suited to map this proximity-dependent nitrogen enrichment zone simultaneously with its emission footprint, providing spatially explicit evidence relevant to optimizing tree spacing and nitrogen management in agroforestry systems where crops rely on tree-fixed nitrogen.
The triproximity lens clarifies why N2O patterns are so context-dependent: the three proximity dimensions operate in opposing directions depending on system management. Along the horizontal dimension, the near-tree zone concentrates organic nitrogen inputs through litterfall and rhizodeposition, but simultaneously supports higher plant nitrogen uptake, meaning that the net effect on denitrification substrate availability depends on the nitrogen balance of the system. Along the vertical dimension, Bentzon-Tarp et al. [28] demonstrated that topographic position overrides horizontal distance in structuring N2O emissions within a hillslope coffee system, highlighting that vertical soil moisture gradients can be more important than horizontal proximity to the stem. At the structural level, Iddris et al. [41] documented N2O emissions from cacao stems that were comparable in magnitude to soil surface fluxes, illustrating that the omission of the structural proximity dimension leads to systematic underestimation of N2O budgets in woody crop systems.

4.4. Carbon Dioxide Dynamics

Carbon dioxide fluxes integrate the opposing contributions of root respiration, microbial decomposition, and soil moisture redistribution, which is why no universal directional pattern emerges across system types. This integrative nature does not imply, however, that CO2 is insensitive to spatial proximity; rather, the direction and magnitude of the proximity effect depend on which source term dominates in a given system. In shelterbelt and agroforestry systems with high tree biomass and organic matter accumulation, CO2 fluxes are consistently higher near trees than in the open field, driven by root respiration and accelerated decomposition of litter concentrated beneath the canopy [32,37]. By contrast, in silvopastoral systems with lower tree density and in orchards under subsurface drip irrigation, the spatial gradient is reversed: tree-mediated improvements in soil structure and water use efficiency reduce overall soil respiration in the near-tree zone relative to compacted inter-tree areas [26,31].
From a triproximity perspective, the horizontal gradient of CO2 is the most consistently documented dimension in the Golden Eleven (Table 3): Szajdak et al. [32] and Kwak et al. [33] reported monotonic decreases in CO2 flux with increasing distance from the shelterbelt tree row in both systems, with the strongest fluxes in the 0–0.2H zone. The vertical dimension is less studied for CO2 than for the other gases, but Gao et al. [31] demonstrated that subsurface drip irrigation compressed the spatial variability of CO2 by decoupling surface moisture from the proximity gradient, a management interaction with direct implications for flux upscaling in orchard systems. The structural dimension was not captured in any included study despite being a measurable and sometimes substantial component of tree carbon exchange [12]; this represents a gap as important for CO2 as it is for CH4 and N2O.
The fact that CO2 was the most frequently measured GHG in this dataset (88 studies, 82.2%; Table 1) yet generated the least spatially explicit evidence underscores a broader mismatch: CO2 is often measured as an indicator of overall soil biological activity rather than as a target gas for proximity analysis, and chamber placement is correspondingly less deliberate. Reframing CO2 measurement within the triproximity protocol would improve both the mechanistic interpretation of individual flux patterns and the comparability of carbon balance estimates across tree-based systems.

4.5. Management Practice Interactions

Irrigation practices emerged as a key modifier of spatial patterns, particularly in orchard systems where drip irrigation creates localized wet zones that decouple tree proximity from moisture availability. Localized water applications can override natural gradients created by tree roots and canopy interception, generating artificial hotspots of denitrification [1]. N2O emissions can further be boosted by a legacy effect of irrigation decreasing soil pH [54].
This interaction between irrigation design and tree proximity effects is particularly relevant for intensively managed perennial orchards. Future studies in such systems should explicitly document both the irrigation design and the position of gas chambers relative to drip emitters and tree stems, as either factor alone provides insufficient context for interpreting measured fluxes.

4.6. Stem Emissions and Complete Flux Accounting

The near absence of stem flux measurements in agricultural tree systems represents the most acute knowledge gap exposed by this review from a triproximity perspective: the structural proximity dimension is, for practical purposes, unmeasured. Trees can act as physical conduits connecting anaerobic soil layers where CH4 and N2O are produced to the atmosphere, bypassing the surface soil oxidation zones that otherwise attenuate these fluxes [15,16]. In forested wetland ecosystems, stem emissions of CH4 can account for up to 60–80% of total ecosystem emissions [38], and Gauci et al. [16] recently demonstrated that upland trees represent a globally significant pathway for CH4 uptake via bark-associated methanotrophs, a process entirely absent from soil-based accounting. For N2O, Iddris et al. [41] documented that stem emissions from cacao were of similar order of magnitude to soil surface fluxes in a humid tropical agroforestry system, while the single study in our dataset that measured stem N2O in an agricultural context confirmed detectable flux from tree trunks.
The relevance of stem fluxes to agricultural tree systems is not limited to wetland or tropical contexts. In silvopastoral and agroforestry systems where trees develop substantial root biomass in seasonally waterlogged soils, the conditions for anaerobic CH4 and N2O production and subsequent stem transport are met during wet seasons. The absence of stem measurements in 106 of the 107 included studies means that ecosystem GHG budgets for tree-based agricultural systems are, at best, incomplete and, at worst, systematically biased toward underestimation of total emissions or overestimation of net sink strength. Incorporating stem-level measurements at 1.3 m height using semi-rigid chambers [15] as part of the triproximity structural proximity dimension is therefore not an optional refinement but a necessary component of complete flux accounting, particularly in species with aerenchymatous root systems or in systems subject to seasonal waterlogging.

4.7. Toward a Triproximity-Based Sampling Protocol

The evidence synthesized across Section 4.1, Section 4.2, Section 4.3, Section 4.4, Section 4.5 and Section 4.6 consistently points to the same structural deficiency: most studies in tree-based systems measure GHG fluxes without documenting where those measurements were taken relative to trees. Addressing this gap requires a practical reference framework that field researchers can implement without prohibitive logistical costs. Drawing on the triproximity framework, we propose a minimum sampling protocol structured around the three proximity dimensions.
Horizontal proximity: At least three measurement positions along a transect from the tree stem into the open interspace are required to characterize the lateral gradient. For linear systems (orchards, shelterbelts, alley-cropping), transects where chambers are placed should run perpendicular to the tree row, representing the following positions: tree row, 25% of tree spacing (crown area projection) and 50% of tree spacing; for isolated trees (silvopastoral, orchard), a radial design at increasing distances in at least two directions is recommended. Ideally, distances should be reported in absolute meters and normalized by a structural tree dimension (tree height) to enable cross-study comparison. In addition, we recommend including canopy cover (%) as an ancillary variable. We propose two ways of design: one represented in Figure 3 and the other detailed in Table 5.
Figure 3. Proposed triproximity-based spatial positioning of soil greenhouse gas (GHG) measurement chambers in tree-based agricultural systems. (A) In linear systems, including alley-cropping, silvopastoral systems, and orchards, chambers are positioned along a transect perpendicular to the tree line, with sampling locations expressed as fractions of the total alley width (L), from the tree line to the midpoint between adjacent tree rows. (B) For isolated trees, radial transects are established in the horizontal plane, with chamber locations expressed as proportional distances (D) from the tree. This relative-distance approach provides a standardized framework for reporting chamber position across systems with contrasting tree spacing and configurations, facilitating comparison of spatial patterns in soil CO2, CH4, and N2O fluxes among studies.
Table 5. Minimum proposed triproximity-based sampling specifications for soil GHG flux measurements in five major tree-based agricultural system types. H = tree height. All distances in meters from the nearest tree stem. Stem measurements refer to semi-rigid chamber measurements at 1.3 m height. Replicate numbers refer to independent spatial replicates (trees or transects).
Vertical proximity: A minimum two-layer scheme (0–10 cm and 10–30 cm) should replace the near-universal reliance on surface-only measurements. Studies in systems with deep-rooted species or in soils with restricted drainage should add a third layer (30–60 cm) to capture subsoil denitrification dynamics. Auxiliary parameters such as bulk density and water-filled pore space (WFPS) should be reported at each sampled depth (Table 5).
For each depth layer, volumetric soil water content (VSW) or water-filled pore space (WFPS, %) and soil temperature (°C) must be measured at the midpoint of each layer (5 cm for the 0–10 cm layer, 20 cm for the 10–30 cm layer, and 45 cm for the 30–60 cm layer) at each chamber position and at every measurement date.
Structural proximity: Three positional categories should be documented: (i) open soil surface in the reference zone (interrow or open field); (ii) soil surface within the root influence zone (within one canopy radius of the stem); and (iii) stem-level fluxes at 1.3 m height using semi-rigid chambers [15], particularly in species with aerenchymatous roots or in seasonally waterlogged conditions (Table 5).
Management co-documentation: In managed systems, the position of irrigation emitters, fertilizer bands, and grazing pressure relative to measurement chambers must be recorded alongside tree proximity. Without this information, spatially explicit measurements in managed orchards or fertilized agroforestry systems cannot be correctly analyzed and interpreted.
Beyond chamber placement, the protocol requires standardized metadata. At a minimum, publications should report: (i) exact chamber-to-stem distance in meters; (ii) tree age, height, and DBH at measurement time; (iii) soil depth interval sampled; (iv) WFPS or volumetric soil moisture and temperature at each position and date; (v) whether stem-level measurements were taken and, if not, a justification; and (vi) a diagram or map of chamber layout relative to tree positions. We encourage journals publishing soil GHG research in tree-based systems to adopt these as minimum submission requirements, analogous to the PRISMA reporting standard [23] and the established chamber measurement guidelines [55,56,57,58,59].

5. Conclusions

When measuring GHG in tree-based systems, two knowledge gaps demand immediate attention from the field. First, the fraction of studies explicitly reporting measurement distance from trees (37.4%) has not improved despite a near four-fold increase in publication volume since 2020, signaling a methodological drift that requires a coordinated response through standardized spatial reporting guidelines and journal editorial policy. Second, stem-level gas transport the structural proximity dimension of the triproximity framework is measured in only one of the 107 reviewed studies (0.9%), despite compelling evidence from forest, wetland, and even orchard systems that tree trunks are significant conduits for soil-produced CH4 and N2O; their systematic omission biases ecosystem GHG budgets in unknown but likely consequential directions.
This review demonstrates that soil GHG measurements in tree-based systems have proceeded largely without spatial context. Single-point measurements without positional information cannot be reliably compared across studies, upscaled to landscape levels, or incorporated into process-based models. The triproximity framework provides the conceptual and operational foundation to address this deficit. Among the gases reviewed, CH4 uptake showed the most consistent near-tree enhancement, N2O responses were context-dependent, governed by nitrogen availability and moisture, and CO2 showed no universal spatial pattern but was systematically under-characterized despite being the most frequently measured gas. As tree-based agricultural systems gain increasing recognition under national and international climate mitigation frameworks, the credibility of their GHG accounting becomes consequential at a policy scale. Current emission factor methodologies for agroforestry and silvopastoral systems rely heavily on literature averages derived from spatially uncharacterized measurements, the limitations of which this review has documented systematically. The triproximity framework offers a practical corrective: spatially explicit, replicable flux data structured around the three proximity dimensions would provide the empirically grounded inputs needed to reduce uncertainty in agroforestry carbon sink estimates and strengthen the scientific basis of climate mitigation claims associated with tree-based land use transitions.

Author Contributions

Conceptualization, G.S.C.; Methodology, G.S.C.; Formal Analysis, G.S.C., G.D. and E.-D.A.; Investigation, G.S.C., G.D., E.-D.A. and F.F.G.D.L.; Writing—Original Draft Preparation, G.S.C., G.D., E.-D.A., F.F.G.D.L.; Writing—Review and Editing, G.S.C., F.F.G.D.L., M.B., Ö.S.U., E.B. and S.M.; Supervision, G.S.C. and M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors acknowledge the Global Research Alliance on Agricultural Greenhouse Gases (GRA) and, in particular, the Cliff Grads Programme for supporting the training and capacity development of co-authors Girmay Darcha Gebramlak, Emmanuella-Doekoos Awang, and Fernanda Figueiredo Granja Dorilêo Leite, whose participation in this work was facilitated through that initiative. During the preparation of this manuscript, the authors used generative AI tools for the purposes of language refinement, cross-checking references, table formatting and figures illustration. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

Author Martín Battaglia was employed by the company Regenerable LLC. The remaining authors declare that the research was conducted in the absence of an commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GHGGreenhouse gas
WFPSWater-filled pore space
PRISMAPreferred Reporting Items for Systematic Reviews and Meta-Analyses
DBHDiameter at breast height
SOCSoil organic carbon
SDISubsurface drip irrigation
GWPGlobal warming potential
HTree height (used in shelterbelt distance normalization)

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