The originality of this work lies first and foremost in the combination of different approaches to characterizing the dynamics of organic matter in an original agroforestry system combining fruit trees and vegetables. Another innovative aspect is the consideration of spatial variability (distance from the fruit tree) in order to assess the extent to which the fruit tree can have a positive impact on soil biological activity.
4.1 Litter inputs, plot configuration and management practices all affect the distribution of SOC in a garden-orchard system
The litterfall distribution measured in our study is consistent with Thevathasan and Gordon (1997) who highlighted that around 80% of leaves fell within 2.5 m from the trees in a 6yearold poplar AFS. Furthermore, we found a difference between the eastern and the western parts of the plot as the litterfalls in B1E or B2E were significantly lower than those in B1W or B2W, although these beds were located at the same distance from the tree rows. This could be due to two main factors. The first explanation is related to the effects of wind on leaf dispersal, as reported by Swieter et al. (2021). Indeed, we recorded prevailing west winds during autumn, for both years (Figure S4, Supplementary material). Accordingly, the leaves from the western tree rows (RW) fell into the inter-row while those from the eastern rows (RE) were mostly transported out of the plot and were not quantified. Therefore, the prevailing wind direction is an important criterion to consider in GOS design, as it can significantly influence litter distribution and consequently the distribution of SOM. Secondly, the two rows were not composed of the same varieties of apple trees. Trees did not have exactly the same canopy structure, which influences the quantity of litter returned to the soil (Morffi-Mestre et al. 2020; Mayer et al. 2022). The strong and positive correlation between the litterfall supply and the SOM, TOC and soil N we found in our study suggests that the higher litter contribution close to the tree rows could have been an important contributing factor for the greater accumulation of SOM, TOC and N at these locations, as observed in several agroforestry and forestry context studies (Tesfay et al. 2020; Suhaili et al. 2021; Eddy and Yang 2022; An et al. 2023, Rinady et al. 2023). However, the differences in TOC between the tree rows and the vegetable beds are quite high, especially between RW/RE and the B2 and C beds. Such a difference would take several decades to establish and could not be attributed exclusively to litter inputs. We can also offer some explanations as to the distribution of soil TOC due to the historical use of the plot.
Until 2016, this was a classic apple orchard with herbaceous cover in the inter-row. Since then, vegetable beds have been installed. We assume that such a transformation has led to a decrease in SOC in the inter-row, and more contrasting differences in SOC between the apple tree rows and the vegetable beds. Furthermore, since the change in land use, the vegetable beds have been repeatedly ploughed. According to Poeplau and Don (2013), the conversion from natural vegetation to cropland may lead to a depletion of the SOC stock due to soil disturbance, especially soil tillage.
4.2 SOM enrichment and microclimatic conditions increase litter decomposition rate near the trees, up to 1.5 m
We have shown good repeatability of decomposition rates calculated from one year to the next in RW. These values are very similar to those investigated in apple orchards in Italy (0.012 day− 1, Tagliavini et al., 2007).
Litter decomposition was faster in apple tree rows. This result is partially linked to the SOM enrichment and the nutrient status of the soil, as we found a strong and positive correlation between the litter decomposition rate and SOM, soil N and soil TOC (Fahad et al. 2022). Several studies have shown that the decomposition rate is controlled by the chemical properties of the soil, especially SOM content and nutrient availability (Krishna and Mohan 2017; Zhou et al. 2008; Ngaba et al. 2024). Hobbie and Vitousek (2000) highlighted that fresh litter may contain insufficient nutrients to meet the growth and maintenance requirements of decomposers (i.e. fauna and microbes). Differences in litter decomposition rate can also be explained by the microclimatic conditions which has been measured between the tree row and the vegetable beds. Air temperature and relative humidity are abiotic factors that play an important part in the rate of litter decomposition. Pandey et al (2007) showed a variability of 68% in forest ecosystems. Karungi et al. (2018) point out that such microclimatic conditions play a major role in regulating the microbial population and macrofauna, and hence their activities. The differences in temperature and humidity recorded between RW, B1W and C are related to the shading effects of the trees, as discussed by Ramananjatovo et al. (2021) and Ngaba et al. (2024). In either the tree rows and the vegetable beds, and for both years, we did not find positive correlation between decomposition rate and temperature, only with relative humidity, suggesting that decomposition is limited by humidity first. This is what Petraglia et al. (2019) have also shown in 6 agroecosystems.
4.3 Microbial activities would be more intensive near the trees, up to 3 m, but remain highly dependent on microclimatic conditions
Soil respiration is closely correlated with microbial biomass and activities (Jenkinson et al. 1976). The patterns of distribution in soil basal respiration in our study indicate that the microbial community is more active near the apple tree rows, suggesting a higher potential capacity for decomposition and mineralization near the trees. Moreover, the strong SIR rates in RW, RE and B1E clearly indicate a higher active microbial biomass response to glucose addition near the tree rows. The weakest qCO2 under the trees, especially in RW, reveals a C limitation for microbes, and indicate that the microbial biomass is more conservative (i.e. lower CO2 release by microbial biomass unit) than in vegetable beds. Guillot et al. (2021) also observed twice the microbial activity in the tree rows of a walnut-based agroforestry system. The higher C and N contents in the soil beneath the tree rows partly explain the higher SIR in this area, as we found a positive correlation between SIR and soil TOC, and SIR and soil N (An et al. 2023). Bae et al. (2013) reported the same correlations in agroforestry systems in the Philippines and according to Teklay et al. (2006), microbial activity is driven primarily by available organic C and total soil N. However, the lack of correlation between BR and soil C and N content in our work suggests that there might be other variables that were not considered in the study, and which would present a gradient of heterogeneity along the distance from the trees (e.g. soil phosphorus, soil pH).
A low in-situ respiration rate may indicate that soil conditions (nutrient availability, temperature, moisture, etc.) are limiting the biological activities. The kinetics of in-situ CO2 fluxes observed in our study are consistent with Gomes et al. (2016) who compared the hourly evolution of soil respiration between an agroforestry coffee plantation and a monoculture. They found that the fluxes measured during the day were more stable in the agroforestry system (15% increase) than in the monoculture (49% increase) due to a lower amplitude of variation in soil temperature, which is attributed to the shading effects. The temperature and the soil moisture are the most influential abiotic factors for soil respiration (Fang and Moncrieff 2001; Fenn et al. 2010; Gomes et al. 2020; Luo and Zhou 2006; Tang et al. 2006). In the current study, in-situ CO2 fluxes increased exponentially with soil temperature. Our results are in agreement with Carey et al. (2016) who showed that in general, respiration rates increase exponentially with temperature, up to 25°C. In addition, in our experiment, increasing soil water saturation resulted in a decrease in CO2 fluxes. Previous studies have reported that high moisture can decrease soil CO2 emissions by preventing CO2 diffusion to the surface (Melling et al. 2005) and by regulating the physiological processes of aerobic microorganisms (Melling et al. 2014). We found that the individual effects of temperature and soil moisture on soil respiration were lower than the interaction effects of the two factors. This can be explained by the fact that under uncontrolled conditions, the effects of these two variables may interfere with each other. For example, increases in temperature are often accompanied by decreases in soil water content and vice versa. Our results confirm previous work on the effects of temperature and soil water content interactions on soil respiration (Lellei-Kovács et al. 2011 ; Li et al. 2014 ; Sierra et al. 2017 ; Tucker and Reed 2016).