# Biodiversity in temperate silvoarable systems: A systematic review

Florian Kletty, Anne Rozan, Caroline Habold

► To cite this version:

Florian Kletty, Anne Rozan, Caroline Habold. Biodiversity in temperate silvoarable systems: A systematic review. Agriculture, Ecosystems & Environment, 2023, 351, pp.108480. 10.1016/j.agee.2023.108480. hal-04151683

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<figure><img src="image_1.png" /></figure>
Biodiversity in temperate silvoarable systems: a
systematic review

KLETTY Florian* ¹²³, ROZAN Anne<fnref n="3" />, HABOLD Caroline<fnref n="2" />

* Corresponding author:

Florian KLETTY,
FGES Bureau RZ448,
60 Bd Vauban,
59016 Lille Cedex
FRANCE

florian.kletty@univ-catholille.fr

<footnote n="1">¹ FGES, Université Catholique De Lille, F-59000 Lille, France</footnote>

<footnote n="2">² Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France</footnote>

<footnote n="3">³ ENGEES, Geste UMR MA 8101, F-67000 Strasbourg, France</footnote>

<footnote n="4">⁴ Université de Strasbourg, F-67000 Strasbourg, France</footnote>
## Highlights

* SAS are agroforestry systems where trees are closely linked to arable cropping

* SAS are beneficial for biodiversity conservation, and also usually for related ES

* The management of SAS can have a strong impact on biodiversity and associated ES

* The experimental design and protocol have a major influence on the results obtained

* It is possible to promote both biodiversity conservation and ES provision in SAS

## Abstract

Silvoarable systems (SAS) are agroforestry systems (AFS) that combine the cultivation of trees and arable crops. Often, rows of trees delineate crop alleys in a field (alley-cropping system). SAS have the potential to provide many agricultural and environmental benefits, are innovative in their modern form, and are becoming more widespread. These diversified farming systems have the potential to influence biodiversity and related ecosystem services (ES). This systematic review seeks to assess the link between temperate SAS and biodiversity at all main taxonomical levels (bacteria and fungi, plants, invertebrates and vertebrates). We describe the response of biodiversity in terms of abundance, species richness and other diversity indices. This study concerns not only the potential interest of these systems for biodiversity conservation, but also the impacts of living organisms present in the system on ES and eventually ecosystem services.

We obtained 3458 references dealing with both agroforestry and biodiversity from the Web of Sciences database. Among them, 45 articles corresponded to our specific subject and met the selection criteria. These publications were retained for further analysis.

SAS have a positive impact on biodiversity conservation by increasing the abundance or diversity of the different taxonomic groups. Regarding ES, the few papers that studied the effect on pollinators or pollination also showed a positive effect. The majority of studies on natural predators and biocontrol and most of those concerning soil organisms and related supporting services showed a positive effect of SAS. However, some studies found no positive effect or even reported a negative effect in specific conditions. Data is limited for weeds, pests and damage to crop production, and results contrast according to studies and conditions. The
review lists the different parameters that influence biodiversity and the subsequent services. These parameters can be divided into three main groups, namely crop management, the influence of the crop location, and agroforestry management. We also report the influence of the experimental design, for example the use of control and comparison or sampling methods. Moreover, the link with other ES is discussed (mainly in terms of provisioning but also for cultural services). Finally, we suggest future research avenues and propose advice in line with the issues discussed in this work.

## Keywords

Agroforestry, Alley cropping, tree-based intercropping, ecosystem services, biodiversity conservation, agroecosystem, multifunctionality

## Table of contents

Table of contents.................................................................................................................................................. 3

1. Introduction.................................................................................................................................................. 5

2. Methods and search results ........................................................................................................ 8

2.1. Literature screening methodology......................................................................................... 8

2.2. Search results ........................................................................................................................................ 9

2.3. Analyses............................................................................................................................................ 10

3. Response of biodiversity to silvoarable systems (SAS)................................................................. 11

3.1. Biodiversity conservation ........................................................................................................ 13

3.2. Ecosystem Services (ES) and disservices .................................................................................. 14

3.3. Studied taxa.................................................................................................................................... 18

3.4. Diversity indices.................................................................................................................................. 19

3.5. Mechanisms whereby the SAS affects biodiversity.................................................................... 20

3.6. Conclusion on biodiversity response...................................................................................... 23

4. Drivers of biodiversity in SAS........................................................................................................ 24

4.1. Crop management................................................................................................................................ 24

4.2. Agroforestry management........................................................................................................ 28

4.3. Influence of the location ............................................................................................................ 31

4.3.1. Field ............................................................................................................................................ 32

4.3.2. Landscape context.................................................................................................................. 33

5. Influences of experimental design .................................................................................................... 34
<table><tr><td>5.1. Controls and comparisons</td><td>34</td></tr><tr><td>5.2. Sampling period</td><td>35</td></tr><tr><td>5.3. Sampling methods</td><td>36</td></tr><tr><td>5.4. Environmental data</td><td>38</td></tr><tr><td>6. Link with other ES</td><td>38</td></tr><tr><td>6.1. Provisioning services</td><td>38</td></tr><tr><td>6.1.1. Productivity, yields, margins</td><td>38</td></tr><tr><td>6.1.2. Farmers' perception</td><td>40</td></tr><tr><td>6.2. Soil Organic Carbon (SOC) and soil health</td><td>41</td></tr><tr><td>6.3. Cultural services of biodiversity</td><td>42</td></tr><tr><td>7. Prospects for future research</td><td>42</td></tr><tr><td>8. Conclusion</td><td>44</td></tr><tr><td>9. Declaration of Competing Interest</td><td>46</td></tr><tr><td>10. Acknowledgements</td><td>46</td></tr><tr><td>11. References</td><td>46</td></tr><tr><td>Figure S1</td><td>53</td></tr><tr><td>Supplementary document 2: sampling methods</td><td>59</td></tr></table>
# 1. Introduction

Our planet is facing major crises such as climate change and the decline of biodiversity. Agriculture takes up most of the land area and strongly affects the environment. Therefore, a more sustainable agriculture is needed. This transition must permit agriculture to address current challenges, notably food production, energy supply and human welfare. The consideration of biodiversity in this approach is particularly important, for several reasons. First of all, biodiversity has an intrinsic and non-anthropocentric frame of reference (according to the IPBES typology for characterising the values of nature; Díaz et al., 2015). This point is especially important because biodiversity is particularly threatened in agricultural areas (Benton et al., 2002; Bretagnolle and Gaba, 2015; Department for Environment, Food & Rural Affairs, 2019; Heldbjerg et al., 2018; Stanton et al., 2018). Biodiversity is also highly valuable from an anthropocentric point of view, in terms of the benefits it provides to people and the relationship we have with it (instrumental value and relational value, respectively; Díaz et al., 2015). Indeed, biodiversity has the capacity to provide different beneficial ecosystem services (ES) to humans (e.g. Dainese et al., 2019; Lindemann-Matthies et al., 2010), but can also sometimes cause ecosystem disservices such as yield losses due to agricultural pests. The attainment of more sustainable agricultural systems requires the development of diversified systems that consider the biological component of agricultural ecosystems (Beaumelle et al., 2021; Duru et al., 2015). This is the case of several agricultural systems, and more specifically those that seek to reduce inputs and promote crop rotation, semi-natural habitats or intercropping systems (Wezel et al., 2018). Agroforestry systems are a particularly good example (Jose, 2009). Agroforestry is the association of trees with livestock or crops within the same space (Leakey, 1996). It facilitates the development of multifunctional agriculture with many benefits, and combines the goals of agricultural production with ecological and societal sustainability (Smith et al., 2013; Waldron et al., 2017). Agroforestry has the potential to provide many benefits for biodiversity conservation and associated ES (Tropics: Schroth, 2004; Worldwide: Udawatta et al., 2019). The majority of studies on agroforestry (and especially its link to biodiversity) have been carried out in tropical regions, while the number of publications in temperate regions remains more limited (Marsden et al., 2020; Staton et al., 2019).

Although there are several types of agroforestry systems (AFS), the most common are silvopastoral systems (or silvopastures), which combine trees and livestock on the same plot of land, and silvoarable systems (SAS),
where trees are associated with (generally annual) crops. Both AFS and scientific literature about agroforestry refer mainly to silvopastoral systems (general occurrence: Udawatta et al., 2019; ES: Fagerholm et al., 2016; biodiversity: Mupepele et al., 2021). In general, croplands have a great impact on the environment, especially through intensive agriculture. Agricultural management in arable lands usually involves pesticide use, frequent perturbations through tillage, and poor plant diversity (large fields, monoculture, etc.). Such management leads to harsh conditions for organisms living in agroecosystems. In agroforestry, the monitoring of biodiversity in SAS therefore seems particularly interesting to enable the development of more sustainable agricultural systems. Moreover, previous reviews on the link between agroforestry and biodiversity focus on different kinds of AFS, i.e. mostly silvopastoral systems or systems where trees are located on the edges of arable crops. This synthesis focuses on SAS, which correspond to alley-cropping systems in arable environments in most of the available publications, sometimes also called tree-based intercropping systems. An alley-cropping plot is composed of alternating crop alleys, which constitute the arable part of the system, and tree rows, which consist of trees and usually an Understory Vegetation Strip (UVS; Figure 1).

<figure><img src="image_2.png" /><figcaption>**Figure 1:** Representation of a silvoarable system (SAS), with the agroforestry plot (alternance of crop alleys and tree rows in the foreground) and its surrounding landscape.</figcaption></figure>
Two previous meta-analyses were carried out to assess the effect of AFS on biodiversity in Europe. Both found a positive effect of agroforestry on biodiversity, although this effect was not significant in SAS for Torralba et al. (2016), or was considered weak by Mupepele et al. (2021). However, these analyses suffer from limitations that are due to the format of the meta-analysis itself (need for homogeneous data with similar controls). Only a portion of the publications on the topic meet the selection criteria, leading to analysing only partially the existing literature. Furthermore, at least in the case of the study by Mupepele et al. (2021), methodological biases or misleading interpretations have been identified in the previous meta-analysis (Boinot et al., 2022). These analyses are also not specific to SAS but concern AFS in general. Moreover, biodiversity can be influenced by different parameters such as agroforestry design, management or spatial configuration (Jose, 2009). The role of such parameters should be considered when seeking to understand the relations between SAS and biodiversity.

It is therefore necessary to carry out a systematic review that not only includes studies whose results are statistically comparable and analysable, but covers all the diversity of studies and research questions explored to date. This review should make it possible to 1) move away from a binary approach that simply seeks to determine whether or not agroforestry is beneficial to biodiversity, 2) consider all the variability of factors that can impact biodiversity in SAS, and 3) provide avenues for understanding the processes at work and the results obtained. Hence, the objective of this systematic review is to synthesise the knowledge related to biodiversity in SAS (i.e. agroforestry on arable land) in temperate climates (and more specifically, in Europe and North America). This work considers publications dealing with biodiversity conservation or ecosystem services regardless of the taxonomic groups concerned, and thus includes vertebrates, invertebrates, plants and microorganisms. The response of biodiversity to SAS is presented for different biodiversity parameters (biodiversity conservation, different ES or disservices), across taxa or variables studied, and through a description of the mechanisms influencing biodiversity. The drivers of biodiversity in SAS are then addressed with crop, tree row and surrounding management factors. We then discuss influences of experimental design on results obtained, cover the link between biodiversity and provisioning, soil regulating and cultural services, and suggest future research avenues.
## 2. Methods and search results

### 2.1. Literature screening methodology

This systematic review focuses on silvoarable systems (SAS), where a tree component is strongly linked to the crop, i.e. mainly alley cropping (also called tree-based intercropping) systems. This is different to hedgerow systems or buffer margins, where trees have a broader role at the agroforestry landscape level. The term AFS (agroforestry systems) is used throughout this article when reference is made to publications related to agroforestry in general and not specifically SAS. The research was limited to temperate systems, specifically in Europe and North America but including the Mediterranean climates of these areas, and sought to attain a synthesis of knowledge about the effect of SAS under relatively similar climatic conditions.

The search for publications was carried out on the Web of Science platform (Clarivate Analytics), as the vast majority of peer-reviewed articles in the targeted field are referenced there. We targeted publications that mention both an agroforestry system and a biodiversity component. The search for agroforestry material was broadly conducted to include agroforestry in general and not SAS alone, because these systems are not necessarily described as such. Thus, the terms selected for searches were 'agroforestry', 'alley cropping', 'silvoarable', 'orchard intercropping', 'tree-based intercropping' and their different variants. For biodiversity, the search terms had to relate to biodiversity or the results of biodiversity measures without being based on specific taxa, i.e. terms such as 'diversity', 'biodiversity' and its variants, 'species conservation', 'richness', 'abundance', 'wildlife' or 'fauna'. The search was carried out for titles, abstracts and keywords, i.e. 'Topics' on the search engine. The final search was thus set as follows:

TS=(("Agroforest*" OR "agro forest*" OR "agro-forest*" OR "alley crop*" OR "alley-crop*" OR "silvoarable" OR "silvo-arable" OR "orchard intercrop*" OR "tree-based intercrop*") AND ("*biodivers*" OR "diversity" OR ("species" near/2 "conservation") OR "richness" OR "abundance" OR "wildlife" OR "fauna"))

All publications published before December 31, 2021 (based on the date taken into account by Web of Science) were considered. A first analysis was carried out on the results prior to March 2021, then a complementary search was carried out in March 2022 to include all publications until the end of 2021. We ensured that any publications registered late on the search engine were taken into account by carrying out a complementary
search that covered the period between October 1, 2020 and December 31, 2021, allowing a 5-month overlap
between the initial and complementary analysis.

## 2.2. Search results

The search returned a total of 3458 references matching the criteria. A manual analysis of the publications was then carried out in the following steps: 1) reading of the titles to eliminate publications that were clearly in non-targeted climates, mainly in terms of the location (e.g. Mexico, Atlantic forest) or the species studied (e.g. coffee); 2) reading of titles and overview of abstracts to eliminate publications that are not relevant to the theme, i.e. do not concern agroforestry or biodiversity, and to remove those focusing only on non-silvoarable systems (e.g. silvopastoral systems, riparian buffers); 3) reading of abstracts and overview of the material and methods to check that the publications correspond to the various research criteria, particularly in terms of the location and system studied (only systems with a close link between the tree and the arable component were taken into account, excluding, for example, systems with hedgerows outside the fields), and setting aside publications that were not original publications; 4) reading of the articles for final validation. All analyses were performed by a single person and were therefore performed consistently, without operator bias.

The analysis resulted in the selection of 42 original studies addressing issues related to biodiversity in SAS. Two of these publications focus on systems where the crop was alfalfa (Stamps et al., 2009a, 2009b). Although these studies can only be marginally considered to deal with arable systems, the issues presented are consistent with the other studies; these two publications were therefore considered. Two other publications focus on systems other than alley cropping: one uses a double row of walnut trees at the edge of a plot as a proxy for studying an alley-cropping system due to a lack of mature alley-cropping systems to study (Pardon et al., 2020), and the other was conducted in very small 8 m-wide plots in a Montado agroforestry matrix (Reino et al., 2016). These publications do however correspond to the previously established selection criteria and are included in this review. The analysis of the references found in the publications led us to add three further articles to the list. One was not found by searching the database because it is not referenced on Web of Science (Muhammad et al., 2005); the remaining two were not found with our search string (Klaa et al.,
2005; Park et al., 1994). These 3 articles have been added, resulting in a total of 45 publications for detailed analysis in this review. These 45 publications are underlined throughout this review. The majority of the articles were published very recently, with 24 of the 45 articles published between 2019 and 2021.

## 2.3. Analyses

During the detailed analysis of these articles, the following information was noted: study location, years of the field work, date of creation and the age of the SAS, tree species, type of crops, agricultural practices (pesticides, tillage, etc.), comparisons made in the study (e.g., tree rows vs. crop alleys, effect of distances to tree rows, SAS vs. arable control, or conventional versus organic agriculture), presence of an arable control and a forestry control, focus of the study (biodiversity conservation or ecosystem services), taxa studied, sampling protocol, biodiversity parameters assessed (abundance, richness, diversity, functionality, etc.), and other parameters assessed (yield, soil organic carbon (SOC), etc). Furthermore, the results obtained and their significance were collected for the different possible comparisons: crop alley versus arable control, tree row versus crop alley, proximity of tree row, tree row versus forestry control and studies comparing different system management. When data for differences between the taxa studied and the variables measured were available, we collected them separately to look for possible differences in results.

The data extracted were used to create the figures presented in this review. Figures were created with Adobe Illustrator (26.5) and R (R Core Team 4.1.3, with ggplot2 package, H. Wickham 2016).
<figure><img src="image_3.png" /><figcaption>### 3. Response of biodiversity to silvoarable systems (SAS)</figcaption></figure>
Figure 2: Effect of SAS on different components of biodiversity and their associated services or disservices. 'Biodiversity conservation' gathers publications which specifically seek to assess biodiversity conservation. '+' or '-' or '~' symbols indicate respectively that the parameter is higher or lower or not significant/does not allow a clear conclusion to be drawn for a given biodiversity component. The colour symbols indicate whether the effect can be considered positive (green) or negative (red). The width of the arrows is proportional to the number of publications presenting the parameter concerned. The numbers refer to the publications concerned, as detailed at the end of this figure legend. The variable or parameter considered is abundance or a similar measure (e.g. activity-density, biomass) when available (numbers surrounded by a circle). If this variable was unavailable, other variables were considered (e.g. richness, diversity; numbers surrounded by a square). For '+' and '-', only significant results have been considered, except when no statistics were available (in which case, the numbers are grey instead of black). The comparison made to assess the effect of SAS can be tree row versus arable control or tree row versus crop alley or proximity to crop alley. Numbers that are not related to arrows refer to publications making other comparisons, i.e. system managements or SAS and forestry control. See Figure S1 for a detailed analysis among different possible comparisons.

1) Peng et al., 1993; 2) Park et al., 1994; 3) Griffiths et al., 1998; 4) Price and Gordon, 1998; 5) Akbulut et al., 2003; 6) Klaa et al., 2005; 7) Muhammad et al., 2005; 8) Mungai et al., 2005; 9) Stamps et al., 2009b; 10) Stamps et al., 2009a; 11) Lacombe et al., 2009; 12) Chifflot et al., 2009; 13) Bainard et al., 2011; 14) Bainard et al., 2012; 15) Smits et al., 2012; 16) Varah et al., 2013; 17) Bardhan et al., 2013; 18) Gibbs et al., 2016; 19) Reino et al., 2016; 20) Furze et al., 2017; 21) Sun et al., 2018; 22) Martin-Chave et al., 2019a; 23) Beuschel et al., 2019; 24) Martin-Chave et al., 2019b; 25) Pardon et al., 2019; 26) Cardinael et al., 2019; 27) Boinot et al., 2019a; 28) Boinot et al., 2019b; 29) Pardon et al., 2020; 30) Richard et al., 2020; 31) Beuschel et al., 2020; 32) Imbert et al., 2020a; 33) Imbert et al., 2020b; 34) Beule et al., 2020; 35) D'Hervilly et al., 2020; 36) Varah et al., 2020; 37) Boinot et al., 2020; 38) Staton et al., 2021b; 39) Staton et al., 2021a; 40) Beule and Karlovsky, 2021a; 41) Puskaric et al., 2021; 42) Beule et al., 2021; 43) Beule and Karlovsky, 2021b; 44) Staton et al., 2022; 45) D'Hervilly et al., 2022.

The publications analysed mostly show positive effects of SAS on biodiversity (Figure 2). Forty-three results indicate positive effects, whereas fifteen indicate negative effects. For 12 of the parameters, either no significant results were found or no conclusion could be made due to wide variability among different treatments. Some topics were studied to a much greater extent than others, notably soil organisms and related supporting services, and natural predators and biocontrol (with 22 and 18 related publications, respectively). Pollinators and pollination, pests and damage, and weeds were studied much less (4, 12 and 2
related publications, respectively). Few publications specifically included the assessment of biodiversity conservation (7 publications).

Biodiversity response to presence of trees and associated Understory Vegetation Strips (UVS) in the SAS can be monitored at different levels in the field. A comparison of the responses in tree rows and crop alleys gives information on the effect of both habitats on biodiversity at a small scale. It is also possible to assess the effect of proximity to tree rows by measuring biodiversity variables at different distances from them. Since some SAS effects can be on larger scales and some species can have high dispersion abilities, a proper comparison of SAS to pure arable systems includes an arable control that is distant from the SAS. Comparison can also be made between SAS and a forestry control, or between different SAS managements. The meaning of the results depends on the comparison that is made, a subject that we discuss further in §5.1. (Controls and Comparisons). Results according to the different comparisons are shown in Figure S1.

**3.1. Biodiversity conservation**

The few studies that have specifically investigated biodiversity conservation all show a beneficial effect of SAS (Figure 2), whatever the comparison made or the variable measured (Figure S1). Thus, SAS promote invertebrate abundance (Peng et al., 1993) and more specifically pollinating insects, which are more abundant than in the arable control (Varah et al., 2013). The same is true of richness and abundance of birds in SAS, compared not only to arable control (Gibbs et al., 2016), but also to agricultural abandonment environments (Reino et al., 2016). For small mammals, Klaa et al. (2005) show a higher abundance in crop alleys and *a fortiori* in tree rows compared to arable control and even to forest area.

Other publications present information concerning biodiversity conservation, although they do not specifically address this issue. This is notably the case of publications indicating a favourable effect of SAS on some specific taxonomic or functional groups (Carabids, natural predators of pests, soil organisms, etc.); this effect is detailed in §3.2. Although some groups may be less abundant or diversified in agroforestry systems (e.g. pest species in some publications) and some variations may be observed between studies, the effects identified are mostly favourable to the conservation of biodiversity in agricultural environments. This is in line with the results obtained worldwide for soil fauna (Marsden et al., 2020).
Despite the positive effects observed for biodiversity in general, SAS have so far not proven to specifically benefit rare or endangered species, but very few studies have focused on this topic to date (plants: Boinot et al., 2019a; birds: Gibbs et al., 2016).

## 3.2. Ecosystem Services (ES) and disservices

**Soil organisms and soil supporting services.** Seventeen of the 23 results dealing with soil organisms and related ecosystem services show a beneficial effect of SAS (Figure 2). The proximity of UVS and trees favour earthworm abundance (Price and Gordon, 1998), which may even be significantly more abundant in the crop alleys than they are in the arable control plot (Cardinael et al., 2019). It should be noted, however, that while D'Hervilly et al. (2020) do not show any significant advantage of tree rows for earthworms in general, they do reveal a shift among ecological categories: the group of endogeic species was mainly found in the crop alleys while the group of anecic species was mostly present in the tree rows. Among invertebrates, SAS also promotes nematodes and balances their communities (Puskaric et al., 2021), and tree rows favour some populations of detritivorous arthropods (D'Hervilly et al., 2020; Pardon et al., 2020, 2019; Park et al., 1994).

Microbial biomass, diversity or activity can also be enhanced in tree rows compared with crop alleys (Beule et al., 2020; Beule and Karlovsky, 2021a; Beuschel et al., 2019; Mungai et al., 2005), or even in crop alleys compared with arable control fields (Lacombe et al., 2009; Puskaric et al., 2021). More specifically, Arbuscular mycorrhizal fungi (AMF) can be promoted in the crop alleys in comparison with arable control (Bainard et al., 2012). Furthermore, Chifflot et al. (2009) show a higher diversity of AMF in SAS than in a forest control. In comparison with both walnut plantation without arable crop and pure arable cropping system, Puskaric et al. (2021) found that SAS is beneficial to soil organisms (bacteria, fungi and nematodes) and may improve ecosystem stability. A greater abundance or diversity of all these organisms can promote soil functioning and possibly improve the quality of the services provided (see §6.2.: SOC, soil health and erosion). The activity of microorganisms in the soil can be directly assessed by measuring enzymatic activities and respiration rates, and for some parameters indicates a higher activity in the tree rows than in the crop alleys (Beuschel et al.,
2019; Mungai *et al.*, 2005).

Two publications show a negative effect of SAS on microbial biodiversity. In one case, the authors observed a higher biomass at 15 meters from the tree row compared to locations inside or near to it, but they also indicate that combining poplar SAS with organic agriculture is beneficial (Sun et al., 2018). In a second case, the negative effect is linked to one specific tree species, the conifer spruce (Picea abies), where AMF diversity was lower than that recorded with other tree species or even in the absence of trees (Bainard et al., 2011). Apart from this spruce-related effect, these authors did not find any differences between SAS and monocropping control. Similarly, Bardhan et al. (2013) show no differences in the abundance or diversity of microbial communities between tree rows and crop alleys. Sometimes, the results can be different according to the variable measured. For example, Beule and Karlovsky (2021a) found in some sampling sites a higher bacteria abundance in tree rows than in crop alleys but a lower evenness or diversity (Figure S1; see also §3.4. Diversity indices). Finally, Furze et al. (2017), who studied the influence of water stress by comparing SAS and pure arable systems, did not clearly determine if a benefit of agroforestry occurred for microorganisms and their associated services. Although the effect is not always consistent across the sites, years or species studied, most results still highlight the value of SAS for soil organisms and the supporting services they provide.

**Natural enemies and biocontrol.** Eleven publications show a positive effect of SAS on the abundance or biocontrol of natural enemies, although six of these also indicate negative effects of SAS under specific conditions (Figure 2). One study shows a solely negative effect, and four studies did not show any significant trend, at least for abundance as a measured variable (see Figure S1 for more details). The various publications in this field indicate that the tree rows favour the presence of predators of pests (Pardon et al., 2019; Richard et al., 2020), and in particular provide overwintering habitat for many of them (Boinot et al., 2019b). More predators were found in the SAS than in an arable control plot (Akbulut et al., 2003; Peng et al., 1993), and a greater functional diversity was also noted in the SAS (Staton et al., 2021b). However, results can be variable depending on the species or life strategies considered (Boinot et al., 2020; Martin-Chave et al., 2019b; see §3.3.), the time of year (Martin-Chave et al., 2019a; see §5.2.) or the agricultural model (Boinot et al., 2020; see §4.1.).

Effective biocontrol appears to be greater in SAS compared to arable controls, particularly in terms of pest
infection and parasitism (Muhammad et al., 2005; Stamps et al., 2009b). Martin-Chave et al. (2019a) also found a higher predation rate in the condition with little or no pruning compared to the controls with no trees or with heavily pruned trees. However, Imbert et al. (2020b) found varying levels of biocontrol depending on the pest species considered, with some being better controlled in SAS and others in arable control.

In addition to the aforementioned studies showing beneficial effects under some conditions and negative effects under others, only one other study shows a negative effect of SAS on natural enemies and biocontrol. Indeed, Imbert et al. (2020a) found fewer predators and more pests in the fruit tree - vegetables system than in the vegetable control. Different processes come into play with biocontrol, such as ecological niche complementarity, intraguild predation and functional redundancy, which modulate the link between organisms and their effect within the ecosystem (Straub et al., 2008). Thus, current knowledge of this mechanism is still scarce and should be improved.

**Pests and damage.** Three studies were focussed on pest abundance or pest-related damage (Figure 2. They show both positive and negative effects induced by SAS, depending on the taxa considered (see also §3.3.). Smits et al. (2012) did not find any differences for aphids in SAS compared to the arable control, while Imbert et al. (2020a) found a negative effect with more aphids in the SAS. Imbert et al. (2020a), however, conducted their study in a specific context, consisting of a vegetable line within an apple orchard. In contrast, several studies have shown a lower abundance of pest arthropods in the SAS than in the arable control (e.g. Muhammad et al., 2005; Peng et al., 1993; Staton et al., 2021b). Furthermore, Staton et al. (2021a) show that the management modalities of the UVS could strongly modulate the aphid populations observed on apple trees and the damage they cause (see §4.2.2.). Regarding slugs, the two studies that assessed their populations found greater abundance in the SAS than in the arable control (Griffiths et al., 1998; Staton et al., 2021b). Slug dynamics within the SAS remain to be studied, as the UVS does not seem to play a particular role as an overwintering refuge for these pests (Boinot et al., 2019b). Other parameters such as microclimate should therefore explain their higher abundance in the crop alleys in comparison to a pure arable system. Such disparities between studies and conditions have also been reported in a worldwide meta-analysis on pest, disease and weed control in all types of AFS (Pumarino et al., 2015).
**Weeds.** Only two publications have been found that meet the criteria of the systematic search. Staton et al. (2021b) show a 27% increase in weed cover in the SAS compared to the arable control. In contrast, Boinot et al. (2019a) do not show any difference between the two systems for conventional farming (where plant spillover within the crop alleys appears to be very limited), and even show a 12% decrease in weed cover in the SAS where organic farming methods are used. Thus, situations and conditions seem to strongly impact weed-related services or disservices within the SAS (see §4.1.: Pesticides and Organic Agriculture). The fact that the UVS is a refuge for many granivorous carabid beetles or other granivorous taxa (Boinot et al., 2019b) could explain why, under adapted agricultural practices, the SAS can help to mitigate the weed coverage.

**Pollination.** The value of SAS for pollinators and pollination has mainly been assessed in one study, resulting in a first publication with preliminary results and a second with full results (Varah et al., 2020, 2013). This very complete study evaluates different groups of pollinators (bumble bees, solitary bees, and hoverflies) and compares SAS with arable control at six sites that encompass a large variety of contexts over three different years. These authors also used phytometer plants to evaluate (mainly over a one-year period) the pollination carried out by pollinators in the field (evaluation of seed production of California poppies *Eschscholtzia californica*). They were able to demonstrate many favourable effects of SAS for pollinators and pollination, recording levels of abundance in SAS that were at least twice those arable areas for each of the three pollinator groups, as well as higher species richness (especially for solitary bees), and better pollination as a result of pollinator activity.

Another study assessed pollination through apple seed counts, which vary according to pollination levels prior to growth. For one of the two varieties studied, pollination was higher in SAS than in conventional orchards (Staton et al., 2022). In a previous study, the same authors looked at pollinators but compared different types of SAS management rather than the value of the system (Staton et al., 2021a). In particular, they found greater pollination of apple trees in the tree rows of an unmown UVS (measured as the number of flowers visitations) compared to a mown UVS (see §4.2. UVS management).
### 3.3. Studied taxa

A wide range of different species and taxonomic groups are studied in the selected publications (see Figure 5). Some publications highlight differences between species in their response to tree presence (macroinvertebrates: D'Hervilly et al., 2022; natural enemies: Staton et al., 2019). Others highlight an effect of SAS for certain taxa but not for others (microbial diversity: Furze et al., 2017; earthworms: Cardinael et al., 2019). Finally, some authors found different results according to the species considered, like some being favoured in SAS and others in cropped or control areas (carabid beetles: Richard et al., 2020; Boinot et al., 2020; spiders: Martin-Chave et al., 2019b; aerial pest species Imbert et al., 2020a; pests and predators: Staton et al., 2021b). One explanation is the difference in ecological requirement for each species. Since ecological conditions can be modulated by SAS, the species best suited to one habitat are often not suited to another. Thus, the effect of agroforestry on biodiversity is determined not only by the taxon, but also by the ecological characteristics of the species and the relations between taxa. This issue can be studied through a focus on functional traits of the organisms (see §3.4. Diversity indices). The study of a single taxonomic group is usually insufficient to obtain a global picture of ecosystem functioning or to assess the provision of ecosystem services (Bengtsson, 1998). In this latter case, it may be useful to carry out a direct assessment of not only the species present, but also the services they provide (see §5.3 Sampling methods). It seems also important to extend the study of ecological relations between species beyond predator-prey (or parasites) interactions to the consideration of intraguild interactions such as competition or complementarity (Martin-Chave et al., 2019a). For instance, competition seems to occur between the predators carabids and spiders in some studies (Martin-Chave et al., 2019b) but is not observed in other studies, where authors hypothesise that competition may occur between carabids and rodents (Stamps et al., 2009b).

Some taxa are poorly represented in the literature, including groups that play a crucial role in the food chain. This is the case for vertebrates such as birds, terrestrial mammals and bats. Such species have the potential to affect pest species populations as well as their natural enemies (Imbert et al., 2020a). Other taxa like weevils can cause significant damage, and parasitic wasps or fungal pathogens have a strong biocontrol potential (Stamps et al., 2009a). Further studies on such taxa would bring valuable information.
### 3.4. Diversity indices

Various analyses can be carried out from the data collected on organisms living in SAS. First, these data can be analysed according to classic biodiversity metrics, notably abundance, species richness and other diversity indices. We noted the use of the abundance metric (or related parameters such as the activity density or the biomass, depending on the taxon considered) in 33 of the 45 publications analysed. Specific richness (or a determination of the phylotype for microorganisms) was used in 19 studies, and diversity indices (including community structure diversity for microorganisms) in 20 studies. Evenness was only presented in 6 publications. Abundance is the most studied variable, but cannot provide complete information on biodiversity response to SAS when it is the only variable considered. The same can be said for the sole consideration of species richness, which is not sufficient to describe the effect of agroforestry on biodiversity (Boinot et al., 2022). Furthermore, different studies among those considered here found a significant effect of SAS on biodiversity for either abundance or richness, but not both (e.g. Bainard et al., 2012; Beule and Karlovsky, 2021b; Cardinael et al., 2019; Figure S1). The inclusion of several of these measures or indices is important as they provide partially different and complementary information. This was notably shown for natural enemies and pollinator populations in agroecosystems in relation to yield outcomes in a synthesis of 89 different studies (Dainese et al., 2019). Richness, evenness, Shannon or other diversity indices each give different information about the diversity of the system. It is however possible to obtain a more global view through the use of biodiversity profiles. Such biodiversity profiles jointly assess different diversity orders, with different weights given to rare or common species (Leinster and Cobbold, 2012; Marcon, 2015) and we recommend their use to describe the diversity in SAS. Still, it is mostly alfa biodiversity that is studied, while complementary and valuable information could be brought by studying beta and gamma diversity.

Fifteen studies deal (sometimes marginally) with functional traits and diversity of sampled organisms. Boinot et al. (2019b) showed, for example, that the overwintering stage of carabids is a key functional trait to explain how these organisms respond to agricultural disturbances (large and granivorous species overwintering at adult stage were associated to tree rows). Puskaric et al. (2021) linked the better balance observed between nematode functional groups (bacterivorous versus fungivorous species) to bacterial and fungal abundance and to a better ecosystem stability in the SAS, in comparison with arable control or pure walnut plantation areas.
Boinot et al. (2019a) studied the functional traits of plants and indicated that species that are sensitive to disturbances in agricultural environments are a better indicator of environmental quality than species richness. Moreover, Staton et al. (2021b) showed that the study of functional traits made it possible to highlight differences between SAS and arable control, whereas this was not possible with the abundance, richness or diversity indices usually used. Boinot et al. (2020) showed a benefit of SAS under organic farming for spiders, granivorous and omnivorous carabids but not for carnivorous carabids, indicating that different trophic levels may be influenced in different ways. Taking into account the functional characteristics of the organisms studied thus allows a better understanding of their place and role within the agroecosystem (e.g. Hoehn et al., 2008; Martin and Isaac, 2015; Philpott et al., 2009), a particularly important factor in the study of SAS. Moreover, the study of functional diversity is also important when considering the provision of agroecosystem services (Moonen and Bàrberi, 2008), which is predominantly the case in SAS studies. It is therefore possible to carry out different analyses with the same data. A limited consideration of these parameters can generate misleading conclusions (Boinot et al., 2022).

**3.5. Mechanisms whereby the SAS affects biodiversity**

**Habitat and resources.** Tree rows are an environment with permanent vegetation (trees and often UVS), semi-natural habitats and lower levels of disturbance (generally no tillage and no chemicals directly applied) than those found on arable land. Tree rows thus provide a habitat or refuge for many species, which could explain the positive effects on many taxonomic groups observed in SAS. For example, this environment provides an overwintering habitat for carabids that are sensitive to agricultural disturbances, usually large granivorous species that are overwintering in their adult stage Boinot et al. (2019b). It is also a good overwintering and nesting habitat for many pollinators (Bentrup et al., 2019). If managed appropriately, tree rows can also allow the seasonal continuity of resources, especially for pollinators, and thus favour many species and the pollination services they provide (Staton et al., 2019). In AFS, pollinators not only benefit from the provision of pollen and nectar, but also use tree resin for nest construction or antipathogen properties (propolis; Bentrup et al., 2019). Tree rows are the main habitat of some species. This is the case for plants that are sensitive to agricultural disturbance, for which the UVS represents a refuge (Boinot et al., 2019a). Tree rows are also the main habitat for certain invertebrates such as Nebria brevicollis, an abundant species of carabid
beetle that Richard et al. (2020) has only found in or close to tree rows. Although some species are most commonly found in crop alleys rather than tree rows (Boinot et al., 2019b; Richard et al., 2020), greater heterogeneity in SAS probably increases beta-diversity. Indeed, with the combined presence of tree rows and crop alleys, SAS support a greater habitat complexity than pure arable systems. This diversity of habitats and vegetation allow the development of a greater diversity of species within the SAS (e.g. Beule and Karlovsky, 2021a; Peng et al., 1993). According to the 'enemies hypothesis', this greater diversity would permit more effective pest control by natural enemy populations within the SAS (Russell, 1989; Smits et al., 2012). Indeed, the different parts of the SAS allow the development of natural enemies with different functional traits, which would facilitate biocontrol through better niche complementarity (Boinot et al., 2020, 2019b). However, Staton et al. (2021b) indicate that pest suppression is also strongly modulated by a habitat effect, and that pest control issues are different in SAS compared to arable control. Furthermore, the biological traits of the pests considered influence pest control issues. The development of pest populations and the biocontrol thereof thus differ between mobile species such as root flies or pollen beetles and less mobile species such as slugs, and also differs between arable control and SAS.

The attractive habitat provided by tree rows for many species could, however, have a retention effect, i.e. limit or delay the colonisation of the adjacent crop alley by beneficial arthropods and thus delay the resulting biocontrol (Boinot et al., 2020; Imbert et al., 2020a), but this possible phenomenon remains to be studied to better understand its importance.

**Microclimate.** The presence of trees modifies the microclimate around the tree rows and even throughout the field by reducing wind speed, moderating temperatures and improving the water regime (Bentrup et al., 2019; Quinkenstein et al., 2009). This also affects the soil microclimate and thus the habitat of the species that thrive there (Pardon et al., 2020). Changes in soil microclimatic conditions in SAS are linked to changes in microorganism communities (e.g. Mungai et al., 2005). Furze et al. (2017) show that fungal communities are more resilient to water stress in SAS than in arable controls. Regarding animals, Muhammad et al. (2005) recorded lower winds in the SAS, which might explain the lower level of crop invasion by pests such as aphids,
whose movement is influenced by air flow (Smits et al., 2012). Muhammad et al. (2005) also measured lower temperatures in the SAS than in the arable control area, which may have limited aphid development in a study conducted in England. In warmer climates such as southern France, Martin-Chave et al. (2019b, 2019a) show that the tree canopy buffered temperature extremes within the SAS, and favoured the activity of certain beneficial arthropods and the resulting biocontrol. Pollinators benefit from both wind and temperature regulation in AFS (Bentrup et al., 2019), although it has not yet been specifically studied in SAS. In contrast, Imbert et al. (2020a) hypothesized that the presumably lower temperature and wind in SAS could explain the increase in pest abundance. Be that as it may, slugs are the main pests that are likely to be favoured by microclimate in crop alleys (Boinot et al., 2019b). In addition to changes in the values of microclimate's parameters due to tree presence, microclimate heterogeneity could also impact the presence of organisms and their distribution. This question however remains to be studied since related data are scarce (some information can be found in Martin-Chave et al. (2019b, 2019a)).

**Vegetation barrier.** The tree rows can have a barrier effect on the movement of certain populations, either due to the tree canopy or the vegetation present within the UVS (Bentrup et al., 2019). This may have contributed to limiting the invasion of aphids in the study by Muhammad et al. (2005), while it does not seem to have played a role in the study by Imbert et al. (2020b). This barrier might also limit the movement of beneficial arthropods in some cases (Smits et al., 2012). Further studies considering the characteristics of tree rows, notably vegetation density and row orientation with respect to the prevailing winds, would be interesting to gain a better understanding of the importance of this barrier effect for different functional groups and the factors that affect it.

**Dilution effect.** In addition to the barrier effect, the presence of tree rows provides a break in a cultivated continuum, diluting the resource and thereby potentially scattering the populations of herbivore pests such as aphids (Root, 1973; Smits et al., 2012; Staton et al., 2019). The response of natural enemies varies according to the species: some are favoured by high pest densities whereas the opposite is true for others (Tylianakis and Romo, 2010).
### 3.6. Conclusion on biodiversity response

Current scientific knowledge clearly shows that SAS promote biodiversity conservation, both in terms of abundance and diversity. Despite the scarcity of studies, ecosystem services and disservices also seem to be particularly favourable for pollinators (at least for their abundance) and pollination services (see also Bentrup et al. (2019) for a review on pollinators in temperate AFS). The only clearly negative effect seems to concern the evolution of slug populations, which would have more favourable developmental conditions in such systems. Except under certain conditions, SAS positively affect soil organisms (earthworms, bacteria, fungi etc.) abundance, and generally also their diversity. Natural enemy abundance is generally favoured as well, and pest populations (excluding slugs) are generally limited in SAS, although this depends on various factors and is variable across taxa. The few existing studies concerning weed cover show variable effects ranging from positive to negative depending on the agricultural practices used.

Many taxa have been studied in SAS, but many others are missing. Studies on other taxa would allow us to improve our knowledge on the role of SAS for biodiversity conservation, or to better understand ecosystem functioning and how to promote ES. Different taxa can have different responses to SAS or its management, which in turn affects community composition. The response of biodiversity in the SAS studies may differ according to the variable measured. This indicates that different facets of biodiversity may respond differently in SAS. The principal variables measured in the studies or to recommend in future research are abundance, richness and other diversity indices and community composition (either functional, taxonomic or genetic).

The changes brought by SAS are the results of the diversification of the system, providing organisms with more diverse food, habitat and microclimate conditions. We can therefore conclude that SAS can provide many benefits, especially in comparison with pure arable systems. However, different parameters modulate the results obtained and the resulting benefits. The different drivers of biodiversity that are involved will be detailed in §4 below, and the influence of experimental design will be explored in §5.
## 4. Drivers of biodiversity in SAS

<figure><img src="image_4.png" /><figcaption>Figure 3: Representation of the different drivers and management practices impacting biodiversity in the SAS. Drivers linked to crop management (agricultural practices) are in red, those linked to tree row disposition and management are in blue and those related to the landscape context of the agroforestry field are in green. The circled numbers refer to publications specifically addressing the issue (see Figure 2 caption for correspondences).</figcaption></figure>

### 4.1. Crop management

**Pesticides and organic agriculture.** None of the selected publications have specifically tested the effects of pesticides (within the crop alleys) or synthetic fertilisers in an SAS. However, several have looked at the differences between conventional and organic farming in relation to SAS.
Firstly, organic farming can modulate some of the effects of agroforestry on microbial communities, with more
differences found in such systems than in conventional agriculture [Sun et al., 2018]. The plant communities
present in crop alleys are strongly affected, as organic farming modulates the functional traits of these species
(Boinot et al., 2019a). The positive effect of UVS on plant biodiversity is much lower in organic farming than in
conventional farming, as disturbance-sensitive species are able to develop within the field and make UVS
refuge less useful (Boinot et al., 2019a). On the other hand, it appears that SAS provides an additional service
in the management of weeds in organic farming, since weed coverage was 12% lower in crop alleys than in
arable controls (Boinot et al., 2019a).

The benefits of organic farming in SAS are more pronounced when looking at animal communities. Boinot et
al. (2020) found a negative effect of agroforestry on carabid populations in conventional agriculture, but a
positive effect in organic agriculture (greater activity--density and complementarity). Pest and weed controls
are thus hypothesized to be enhanced in organic SAS, although this remains to be confirmed. There could
therefore be an antagonism for some animal populations or ES between conventional agriculture and SAS,
and a complementarity or even a synergy with organic agriculture.

**Tillage.** Tillage can have strong effects on organisms in the agricultural environment, as it usually constitutes a major disturbance in the environment. In agroforestry, this effect can be studied at two levels: between the untilled UVS and the tilled crop alleys, or between a conventional cropping system in the crop alleys and a system with reduced or no tillage. In the first case, the effect of tillage is added to other features of the UVS, such as the presence of permanent vegetation or trees. However, the absence of tillage in the UVS is often put forward as a key reason for the differences observed in comparison with the crop alleys, especially in studies related to organisms and soil characteristics (Beule et al., 2020; Beule and Karlovsky, 2021a; Beuschel et al., 2020). Tillage in the crop alleys is also suggested to be a cause for the observed shift in the prevalence of certain communities such as weeds, carabid beetles or earthworms, with functional characteristics favoured (e.g. smaller size, short life-cycle) or hindered by tillage (Boinot et al., 2019a, 2019b; D'Hervilly et al., 2020).
When reduced or no-tillage farming practices are carried out in the crop alleys, this may have consequences and modulate the functioning of the agroforestry system. However, we did not find any publications that directly compare tillage practices in SAS. Clues are provided in the supplementary material of *Cardinael et al.* (2019) to hypothesize a redundant effect between SAS and no-tillage for earthworms, since no-till sites were among the sites with the least differences between SAS and controls. In arable systems, reduced tillage leads to a higher abundance in earthworms or carabids for some species (Briones and Schmidt, 2017; Kennedy et al., 2013). Predators like bats can also have a higher activity with reduced tillage (Barré et al., 2018a), indicating higher invertebrate prey availability. It is thus likely that tillage reduction can promote many species in SAS and have a cumulative or synergistic effect with tree presence. An antagonistic effect between agroforestry and tillage reduction is however also possible and requires further specific studies.

Tillage practices should also be considered in relation to pests. Boinot et al. (2019a) indicate that differentiated management between the UVS and the crop alleys prevents weed spillover, but that some weeds could cause more problems in no-till systems. A different management should be considered in the latter case, for example by favouring annual plants like forbs rather than perennials grasses within the UVS. Slugs can be favoured in SAS (Staton et al., 2019) but also by tillage reduction (Kennedy et al., 2013). While this is a major limitation to agroforestry adoption (personal observation), the effect of the combining SAS and no-tillage has not yet been studied. Two antagonistic hypotheses can be put forward: a cumulative negative effect leading to a real problem of gastropod management, or on the contrary a better regulation, through a process similar to that observed for weeds in organic farming (see above § Pesticides and organic agriculture).

**Organic matter implementation and fertilisation.** Fertilisation or the addition of organic matter are mentioned as factors that could potentially influence the species present in the SAS (Beule and Karlovsky, 2021a; Boinot et al., 2020; Lacombe et al., 2009). However, no specific study in the scope of this review has tested this hypothesis. The use of ramial chipped wood could explain some specific results obtained, such as a higher abundance of worms in the crop alleys than in the UVS (Cardinael et al., 2019) or the small difference in macroinvertebrate populations in crop alleys compared to tree rows (D'Hervilly et al., 2022).
**Cover crops.** Although cover crops are known to influence biodiversity in agricultural fields and environments, the studies within the scope of this paper have not particularly addressed this subject. Again, one can simply refer to the different sites studied by *Cardinael et al.* (2019) for earthworm populations, where the presence of cover crops seems correlated with reduced differences in earthworm abundance between SAS and pure crop controls. A redundancy between the effect of agroforestry and cover crops should therefore be explored. However, we recommend including the analysis of agricultural practices like cover crops with other practices. Indeed, bird abundance, for instance, only increased with reduced tillage when associated with cover crops as a weed control method (Barré et al., 2018b).

**Crop type.** Biodiversity response in SAS can be modulated by the type of crop. Pardon et al. (2019) show differences in arthropod populations in the SAS between winter cereals and maize, the latter hosting less fauna. Crop type can also explain the differences observed, here for microbial community composition, between sites (Lacombe et al., 2009) or years (Mungai et al., 2005). Some variations in pest predators have also been observed between different cabbage cultivars (Imbert et al., 2020a). Staton et al. found variations in biocontrol and aphid damage (2021a) as well as pollination services (2022), between different apple varieties. The choice of species or cultivars can thus be important to promote biodiversity and the services provided by some taxa. The most favourable crop types in conventional cropping are not necessarily the same as in SAS (Griffiths et al., 1998). Oat, for example, may be particularly well suited to SAS, because crop yields does not appear to be impacted by possible weed competition or slug damage, unlike wheat or barley (Staton et al., 2022).

**Arable intercropping.** SAS are already intercropping systems based on trees, but it is possible to intercrop at a finer scale, i.e. within the crop alleys. The fields studied in organic farming often include a second intercrop species (e.g. pea; Boinot et al., 2020, 2019a). The effects of this practice merge with those of organic farming. More research is needed on the impact this has on biodiversity in an SAS.
## 4.2. Agroforestry management

**Tree management.** The effect on biodiversity is not necessarily the same and can vary according to the tree species constituting the tree component of the SAS. Spruce was identified as negatively affecting AMF communities, diversity and development within the system, due to the lack of mycorrhizal symbioses of coniferous trees (Bainard et al., 2012, 2011). More generally, the composition of microbial communities (Sun et al., 2018), but also earthworm populations (Price and Gordon, 1998) can vary according to the tree species. Fauna and fruit damage have also been shown to differ across apple tree varieties (Staton et al., 2021a). Beyond tree species or varieties, tree diversity may influence the system's ability to host organisms. Some of the studies are however based on a single species, mostly poplar (Populus sp.), walnut (Juglans regia), maple (Acer sp.) or fruit trees. Other studies integrate a greater diversity of species, sometimes 10 or more (e.g. (D'Hervilly et al., 2020; Gibbs et al., 2016).

In several studies, the tree rows of the different fields were composed of hazel trees, in addition to other tall trees (Bramham university experimental site, UK, (Griffiths et al., 1998; Klaa et al., 2005; Muhammad et al., 2005; Peng et al., 1993) and Ontario, Canada (Gibbs et al., 2016)). This provides a more complex tree row structure, with an additional vegetation layer (shrub layer) that probably has an influence on some biodiversity components, but again this remains to be explored. The structure of the tree rows is also determined by tree spacing, number, assembly and management. The influence of structure has been shown for example for hedges and their attractiveness for bird populations (Hinsley and Bellamy, 2000), but only three publications among those selected here have addressed this issue, at three study sites in southern France. Martin-Chave et al. (2019a, 2019b) studied the effect of different tree pruning intensities (four levels studied: control, pollarding, strong pruning and light pruning), at two sites near the city of Auch. They showed that this management has an effect on microclimatic conditions, invertebrate abundance and daily activity period (Martin-Chave et al., 2019b). Strong tree shading can have a positive or a negative impact depending on the animal species considered (Martin-Chave et al., 2019b), but results are also highly variable across seasons (D'Hervilly et al., 2022). The impact of tree presence on species abundance generally followed the gradient of management intensity (Martin-Chave et al., 2019a) but were independent of the distance to tree rows. In another study, SAS was a short rotation coppice system (cropped high-density trees that were regularly
harvested; Beuschel et al., 2020). This type of system creates a totally different tree row structure (dense and low vegetation) than those in the other studies but specific studies would be needed to know the impact on the biodiversity of the SAS. This is especially true since short-rotation coppice-based SAS are receiving increasing attention and can also provide multiple ecological benefits (Tsonkova et al., 2012).

**UVS management.** The UVS can be managed in different ways, and the choice of UVS management strategy influences the biodiversity of the SAS. Four publications have tested the effect of this management. Richard et al. (2020) tested the effect of the presence or absence of decaying branches in the UVS on carabid beetles, but also investigated how the presence or absence of trees (in this case a simple grass strip) affects carabid beetles populations. The UVS only attracted carabids when trees were present, but decaying branches did not make a visible difference to carabid activity/density. Smits et al. (2012) compared populations of wheat aphids and their natural enemies in a chemically weeded UVS with populations in a UVS that had been seeded with a floral mixture. The authors did not find any difference between the two management methods, but these conclusions should be interpreted with caution (the UVS had recently been planted, after ploughing, and did not grow as expected; no difference was observed between SAS and arable control). In contrast, Staton et al. (2021a) show clear differences between management involving a regular mowing of the UVS versus those planted with a floral mixture. They highlight advantages for various taxa, services (pollination, reduced apple damage) and economic feedbacks of the floral mixture, both in the UVS and crop alleys. Finally, Boinot et al. (2019a) studied weeds in systems with fields with different types of UVS management, namely unmanaged, mown twice a year or sown with competitive perennial species. They found that the functional traits of plants in the UVS differed according to the management type, an example being the higher prevalence of animal-dispersed plant species in unmown or sown UVS than in mown ones. Different management options can therefore modulate plant diversity conservation or the risk of plant spillover according to agricultural practices in the crop alleys. UVS have also the ability to enable nitrogen fixation if legume species are present (Beule and Karlovsky, 2021a). UVS management can thus modulate biodiversity and related services, but it must be adapted to the desired objectives (Staton et al., 2019).

The influence of UVS width (and indeed the width of crop alleys) have not been specifically studied. For field margins, the width of the vegetation strips positively affects biodiversity, especially for plants (e.g. Pallavicini
et al., 2020). It is likely that the same effect can be found in SAS. Positive effect of width on biodiversity can be related to higher habitat amount and to higher habitat quality owing to buffering effects, with less agrochemical drifts in the center. The absence of results or the negative results that are sometimes observed may be due to the small size of UVS (e.g. Imbert et al., 2020a).

**Age of the system.** The age of the SAS studied varied greatly from one study to another and from one site to another, ranging from 1 to 41 years (or 69 years if we include Pardon et al. (2020), where the system studied is intended to be a proxy for an alley cropping system). However, a majority of the studies were carried out in young SAS, with almost 80% being less than 13 years old (63/80, see Figure 4). This relatively young nature of the system is regularly discussed as a limiting factor of the studies, either when seeking to explain a limited effect of the system (Beuschel et al., 2019), or because it describes in-transition agroforestry systems rather than mature ones (Beule et al., 2020; Boinot et al., 2022, 2020). Beule et al. have shown that mature poplar alley-cropping systems (at least 10 years old) promote the abundance and diversity of fungal communities (Beule et al., 2021) but very young SAS (0.5 to 1.5 year old) do not, although changes occur in community structure in the tree row within half a year (Beule and Karlovsky, 2021b). The scarcity of mature alley-cropping systems seems to be one of the main explanations for the small number of studies that have been conducted to date (Martin-Chave et al., 2019b; Pardon et al., 2020). However, it would be particularly useful to study older systems and we call for studies at sites that have already been studied in the past. Such studies would make it possible to measure the evolution of the system and its effects on the same site over time, which has not been done so far. SAS ageing can have two types of effects: the expression of processes that take time to develop (e.g. changes in soil functioning and quality), and structural changes brought about by ageing trees (height, canopy density, organic matter production, presence of new ecological niches with dead wood, old bark, cavities, etc.). In the meantime, we must take into account that young SAS are more influenced by UVS than by trees (Staton et al., 2021b).
<figure><img src="image_5.png" /><figcaption>Figure 4: Age of SAS according to the year of the study. Different countries are represented in different colours, with a diamond shaped symbol for North America and a circle shaped symbol for Europe. Each point corresponds to a site in a study (one study with multiple sites is represented with the corresponding number of points; the same site in different studies is represented once for each of them). When studies covered several years, the corresponding point is placed on the average of the study period. For a better representation, points are jittered on x axis.</figcaption></figure>

4.3. Influence of the location

Besides the overall management of the SAS, the location of the system also influences the biodiversity that develops there through different factors such as soil type, climate, exposure, slope and nearby natural and semi-natural areas. The assessment of different study sites permits us to ascertain whether the obtained results can be generalised or if they depend on specific conditions at the study site. Very few of the studies published before 2019 were multi-sites (2 out of 21, each including only two sites). Recent publications explore this context in greater depth, notably for soil microorganisms (1 study on 2 sites and 3 studies on 3 sites) but also include a study on earthworms that was carried out on 13 different sites in France (Cardinael et al., 2019).
another on plants across 8 sites in the south of France (Boinot et al., 2019a) and two others on arthropods, each on 6 sites (Boinot et al., 2020, in the south-west of France, and Pardon et al., 2019, in Belgium).

### 4.3.1. Field

**Soil type.** The influence of soil type is mainly considered in the literature dealing with soil organisms. Beule and Karlovsky (2021a) and Lacombe et al. (2009) only observed differences in microbial organisms between the agroforestry system and the arable control at one study site per study and not at other ones. They hypothesized that these differences in the effect of SAS were due to differences in soil composition between the sites. In contrast, Beule et al. (2020) and Beuschel et al. (2019) observed variations in microbial biodiversity between three sites regardless of their soil composition. Given these conflicting results, the relatively small number of sites and soils studied and the lack of replication of the same soil type on different sites, it is still premature to draw conclusions on the effect of soil type on microbial biodiversity, and a fortiori, on biodiversity as a whole.

**Climate.** The SAS changes the microclimatic conditions within the field compared to arable control. The effect of these changes on biodiversity is dependent on climate and related issues. Of all the selected studies, only the one by Cardinael et al. (2019) has been carried out at enough sites and at various latitudes to consider the effect of climate (although this subject was not discussed in the publication). Although their results indicate that the two southernmost sites have the lowest earthworm populations at the tree row level, this finding is not sufficient to draw conclusions about the effect of climate within the SAS. Specific studies would be necessary, for example to understand how the SAS impacts species present under drought conditions, or conversely how populations that appreciate wet conditions such as gastropods respond to these systems. This question seems particularly important in the context of climate change that modifies the climate of some regions and increases extreme weather events, leading to crop damage and yield losses.

**Experimental stress.** Furze et al. (2017) experimentally tested the influence of water stress in an SAS on AMF (Arbuscular Mycorrhiza Fungi) communities. They did not observe any changes in the communities following the stress in the arable control, but did observe the occurrence of some changes in the agroforestry system.
Lacombe et al. (2009) studied the effect of heavy metal stress on the overall soil microbial communities in two SAS. On one of the two sites, they found a greater microbial stability under stress in the SAS than in the arable control. Given the importance that stress and disturbances are likely to have in the future within agricultural systems, it seems important to further explore the responses of SAS to stresses, especially under extreme climatic conditions.

**Slope, exposure.** The slope, the exposure and the general topography of the site and its surroundings are parameters that can influence not only the microclimate of the field, but also its hydrology and soil. Only some of the studies carried out at the Leeds University Field Station at Bramham, England, mention these parameters. Peng et al. (1993) indicate that one of the four agroforestry sites studied is more exposed to the wind, potentially explaining wider differences in flying invertebrates compared to the arable control in that site.

### 4.3.2. Landscape context

Landscape context has mostly been addressed through the prevalence of Semi-Natural Habitats (SNH) in the landscape. In the same way as trees and the UVS in SAS, SNH such as hedges, woods or grasslands can influence the biodiversity present in agricultural fields. However, the tree rows are themselves SNH, and their effect on biodiversity can be modulated by other SNHs in the vicinity. For example, proximity to a forest seems to increase aphid biocontrol in the SAS through higher parasitism rates (although further away, the parasitism rate is itself higher than in arable control; Muhammad et al., 2005). Conversely, however, SNH in the landscape favour solitary bees in the arable control but do not seem to affect them in the SAS, where local factors outweighed landscape-scale factors (Varah et al., 2020). The presence and abundance of SNH in the vicinity of the study areas could therefore limit the beneficial effects of SAS (Smits et al., 2012; Staton et al., 2021a, 2019). A similar effect has been reported for other diverse cropping systems such as diversified cover crops, where the benefit of natural predators and biocontrol was particularly present in environments with few SNH (Beaumelle et al., 2021). In some cases or for some species, there could therefore be a cumulative benefit of SNH and SAS, while in others the effect would be redundant.
Landscape context is not limited to SNH. Biodiversity is affected by management not only at field scale but also at landscape scale. Indeed, biodiversity also depends on agricultural practices and farm management, like field size and crop diversity in the landscape, pesticide use, time and intensity of perturbations such as tillage, etc. (e.g. Gaba et al., 2010; Jeliazkov et al., 2016). This question has not however been studied in the range of publications reviewed here, and more attention should be paid to it in the future.

# 5. Influences of experimental design

## 5.1. Controls and comparisons

Three areas can be distinguished in SAS studies: the arable component, the wooded part of the tree rows, and the UVS. Five different main comparisons have been reported among the studies: 1) comparing the SAS fields with arable controls with similar farming practices; 2) comparing the tree rows with the crop alleys; 3) studying the biodiversity of the crop alleys at different distances from the tree rows to assess the effect of tree row proximity; 4) comparing the SAS fields with a forestry control; 5) studying the effects on biodiversity of different management modalities among SAS. The different comparisons used in the 45 studies are detailed in Figure S1.

Trees and UVS within SAS may affect biodiversity and related ES over medium or relatively large distances, especially due to the mobility of the species, and the area of influence of microclimatic changes induced by the system. Studies analysing an SAS without an arable control are not suitable to assess the benefits of this system, even for less mobile species, as AFS can have effects at some distance from the tree row (Boinot et al., 2022). Indeed, less mobile species are not only affected by modifications of pedoclimatic conditions across the field, but also by the impact on mobile species with which they interact, like their predators. However, in the selected cases, only half of the studies (22/45) used a proper arable control to compare with SAS. Two studies used an adjacent crop as a control and six others used an area of the field without trees. When the principal goal of the study is to assess the effect of management practices (e.g. Staton et al., 2021a; Sun et al., 2018), the control needed is not an arable control but a control without the management practice tested. The use or measurement of gradients (e.g. management intensity, shade, pruning) can indeed be recommended
to better understand how UVS and trees affect the cultural system (Marsden et al., 2020). The lack of an arable control in some studies was probably due to the difficulty of finding a suitable control. This control should be a field that had been subjected to the same management and in a similar environment, close enough to limit the effect of location but not adjacent to the SAS field in order to avoid the effect of trees present in the latter. However, studying differences between tree rows and crop alleys or the effect of proximity to tree rows is a helpful means to understand ecosystem functioning in SAS and shed light on how biodiversity responds to tree presence. In addition to an arable control, it may be interesting to study the evolution of SAS over time, beginning before their creation. This approach would provide information on how biodiversity reacts to the creation of the SAS, but above all it would inform on the timing of the changes that occur during the transition. Beule and Karlovsky (2021b) included an initial state in their study comparing fungal communities in agroforestry and arable fields, where the homogeneity of soil composition was tested before the creation of the SAS.

Furthermore, although it is important to replicate the study on different sites to avoid pseudoreplication, few studies have done so (see §4.3. Influence of the location). Once again, this is mainly explained by the lack of suitable agroforestry fields.

## 5.2. Sampling period

Some of the studies were carried out at one time point in the year, while others were carried out over a longer period of time or over several records throughout the year. Where comparisons between months or seasons were possible, the studies often found significant differences. For instance, Bainard et al. (2012) found higher arbuscular mycorrhizal fungi phylotype richness and different community in early summer than later in the season. This seasonal effect may lead to significant results at some times of the year but not at others (Martin-Chave et al., 2019b). In some situations, almost opposite results are possible between sampling dates. Staton et al. (2021a), for example, found a higher abundance, richness and diversity of natural enemies in flowering UVS at the beginning of the year but not later, and even lower levels of abundance and diversity in summer. The time gap between the arrival of pests and their predators or parasites could be involved in such results. Conducting a study at only one time of the year may thus lead to biased results, or simply be unable to show an effect that would be visible at other times (Imbert et al., 2020a; Pardon et al., 2019). In addition, agricultural
practices such as tillage can have a strong impact on the organisms present, but this impact can vary according
to the time of year. The link between seasonality and the effect of practices remains to be studied, but its
consideration is important to understand the effect of SAS on the organisms present (D'Hervilly et al., 2022).
We therefore recommend carrying out surveys that are spread over the year, in line with the objectives of the
study.

**5.3. Sampling methods**

Many different organisms have been studied in SAS, and each taxon can be assessed with different sampling
protocols (Figure 5). Services or disservices linked to the living organisms in the SAS can also be assessed with
different protocols. Details on sampling methods are given in Supplementary Document 2. Different sampling
protocols can provide a different piece of information about the taxa studied. We therefore recommend
combining several protocols to obtain a more complete view of how biodiversity behaves in SAS. This is
especially true since SAS are characterised by higher heterogeneity than pure arable systems. The use of
several protocols is more likely to efficiently assess the differences tested than when only one protocol is used
for each taxon. Finally, few studies have assessed biodiversity-related services or disservices, despite the key
importance of this subject for farmers. When relevant, we recommend performing studies that assess both
biodiversity and its effect in SAS.
<figure><img src="image_6.png" /><figcaption>**Figure 5:** Organisms (outside the red circle) and processes (inside the red circle) studied in the publications with their corresponding sampling methods. Taxa are represented in red font, and they are linked to their corresponding sampling methods. The circled numbers refer to the publications concerned (see Figure 2 for correspondences). Inside the circle, processes are shown in blue font, and their sampling methods in black. In the centre, parameters represented in brackets are only partially linked to living organisms in the ecosystem. See Supplementary Document 2 for more details.</figcaption></figure>
### 5.4. Environmental data

The measurement of environmental conditions in the different experimental situations can provide a better understanding of SAS functioning. Several studies have measured temperature at the field level and found an effect or link between the measured temperature and biological activity in the different experimental conditions (Furze et al., 2017; Martin-Chave et al., 2019a, 2019b; Muhammad et al., 2005; Mungai et al., 2005; Stamps et al., 2009b). Three studies assessed luminosity. Martin-Chave et al. (2019a, 2019b) made hemispherical photographs to measure canopy openness, and related this to other environmental conditions and invertebrate activity. Furze et al. (2017) measured photosynthetically active radiation, but mainly as a control in their experimental water limitation protocol. For the same purpose, they also measured air relative humidity. This was also carried out by Stamps et al. (2009a) in addition to the measurement of soil moisture, thus allowing them to link these two parameters to the abundance of certain groups of natural predators. The importance of wind and the potential effect of its reduction in SAS is discussed by some authors (Muhammad et al., 2005; Peng et al., 1993), but no study has actually investigated this variable along with biodiversity. There are very few studies that measure one or several types of environmental data, yet this information can provide valuable information to understand how variations in SAS affect biodiversity. The development of experimental protocols including such measures would be valuable.

## 6. Link with other ES

Earlier in this synthesis we focused on the importance of biodiversity for regulating services like pollination or biocontrol, and for supporting services such as soil functioning. SAS can bring many benefits linked to other ES, such as provisioning and cultural services. Developing this topic in relation to biodiversity can provide a more complete view of the services brought by biodiversity in SAS.

### 6.1. Provisioning services

#### 6.1.1. Productivity, yields, margins

In farming systems, productivity, yields and margins are central parameters for farmers' management choices. The development of SAS and management modalities are therefore linked to these parameters, and it seems
necessary to take them into account alongside the various benefits that biodiversity can bring. In their literature review on ES supporting crop yield, Garibaldi et al. (2018) highlight that ES are very complementary or synergistic. However, very few of the studies carried out within SAS simultaneously analyse ES and parameters related to agricultural production.

Some studies such as Park et al. (1994) have shown beneficial effects of SAS for biodiversity but report a yield reduction. However, this is not a systematic observation. Akbulut et al. (2003) found higher numbers of beneficial arthropods in the SAS than in the arable control, in the context of a yield decrease for maize, an increase for beans and variable yields for zucchini. Thus, the effect of SAS on crop yields depends on the crop species. Thevathasan and Gordon (2004) show that only crop species with C4 (like maize) but not C3 photosynthesis type had reduced yields in SAS in the experiments conducted in Guelph (Canada), while bird and insect diversity increased. The tree species should also have an effect on crop yields (Reynolds et al., 2007). Yield losses in the vicinity of trees can also be balanced by yield gains at a greater distance (at least for some crops such as wheat; Pardon et al., 2020) or by the services provided by biodiversity. Stamps et al. (2009a) found a favourable economic return in SAS with 24 m-wide crop alleys but not with those that were 12 m wide, with similar biocontrol between the two widths. Furthermore, the value of trees can also be enhanced, e.g. for fruit or timber production. At a site in the south of France (where Boinot et al., 2019b, performed their study and showed the benefits of UVS as overwintering habitat), a study over 20 years pinpoints that total SAS production was higher than for separate arable or forestry controls (Land Equivalent Ratio (LER) 1.3 to 1.6; Lovell et al., 2018). Moreover, crop yield losses along the study averaged only 2% compared to arable control.

SAS can also change the quality of agricultural production. The protein content of grains can be enhanced while increasing the abundance of macro-detritivorous arthropods (Pardon et al., 2020) or may limit colonization with phytopathogenic fungi (Beule et al., 2019). Appropriate management practices can improve apple quality through better biocontrol, without affecting the yields of adjacent crops (Staton et al., 2021a).

The profit margins that farmers can make from a SAS, derived from productivity and costs, are rarely discussed in relation to the living organisms in that environment. We can simply cite Staton et al. (2021a), who made a
financial model for different managements of fruit-tree rows, including pest damage to apples and
corresponding yield and incomes, grants for flower-mix sowing, and mowing costs. They showed that
flowering UVS allowed an overall income increase of 231 GBP (about 314 USD) per hectare compared to
regular mowing, which represents more than 10% of the forecasted gross margin of the SAS. In a later study,
these authors also showed that by considering not only yields and fruit production but also marketable ES
such as carbon storage or the pollination of apple trees and the resulting fruit quality, SAS is cost-effective
within a few years and can compensate for yield losses in the crop (Staton et al., 2022). Such approaches are
important to follow, since it was shown that for most farmers an economic advantage is necessary for them
to develop an SAS (Graves et al., 2017). We can however emphasise that SAS such as alley-cropping systems
are very new systems that do not benefit from many decades of agronomic development. Furthermore, crop
varieties used in SAS have mostly been selected for their performances in pure arable systems. Much work
remains to be done in this field.

6.1.2. Farmers’ perception

Farmers are the actors of field management and the first recipients of provisioning services. Whatever benefits SAS can bring, the development of agroforestry is dependent on the farmers' perception of these benefits. De Jalon et al. (2018) assessed farmers' perception of AFS in general, among more than 300 farmers. The environmental or biodiversity benefit is one of the main positive aspects that emerges from the farmers' perception of agroforestry, while the complexity of the work, the implementation of the system and the administrative burdens are the main hindrances that were identified (AFS in general: De Jalon et al., 2018; SAS: Graves et al., 2017, 2009).

Although the original studies presented here do not specifically measure this perception by farmers, it is
sometimes mentioned, indicating for example that SAS are perceived by some as solutions to wildlife habitats
conservation but by others as reservoirs for weeds (Boinot et al., 2019a). Staton et al. (2021a) recommend
that studies on biodiversity and ES in SAS should also aim to quantify outcomes in a way that is meaningful to
farmers, such as yields or profit. Non-marketable ES benefits are also important in fostering farmers'
perceptions of SAS (Staton et al., 2022). Finally, biodiversity is improved when farmers have better environmental education (Power et al., 2013).

## 6.2. Soil Organic Carbon (SOC) and soil health

Soil characteristics are a major parameter for supporting services provision. SAS promote carbon storage and contribute to the improvement of soil quality and fertility, notably by improving SOC levels, limiting nutrient and pesticide leaching and surface erosion, and improving the water regime (Pavlidis and Tsihrintzis, 2018; Quinkenstein et al., 2009; Torralba et al., 2016; Tsonkova et al., 2012).

A significant number of studies on soil microorganisms have also measured soil physicochemical parameters, mostly SOC or soil organic matter. SOC levels are often linked to variations in microbial communities (D'Hervilly et al., 2020; Sun et al., 2018) and are correlated with their abundance (Beuschel et al., 2020, 2019). This is also very pronounced in studies on invertebrate animals that have measured SOC, since the same evolution has been observed between SOC and invertebrate populations (earthworms: Cardinal et al., 2019; macrodetritivors: Pardon et al., 2020; general invertebrates: Park et al., 1994). Puskaric et al. (2021) have shown that the higher soil organic matter observed in SAS (in comparison with arable control and pure walnut plantation) was linked to soil organism populations (bacteria, fungi and nematodes), and that this globally has the potential to improve ecosystem stability.

Other measures of soil quality are also possible, such as nitrogen and phosphorus contents or the bulk density (Bardhan et al., 2013; Chifflot et al., 2009; D'Hervilly et al., 2020; Mungai et al., 2005). Lacombe et al. (2009) even measured 11 physico-chemical properties of soils including soil moisture and cation content. They showed (on one site) a greater heterogeneity of these physico-chemical properties in the SAS than in the arable control. These parameters may be related to the activity of the organisms. Denitrification genes were for example found in higher abundance in SAS than in arable control, which may impact nitrate content in soils and reduce nitrate leaching (Beule et al., 2020). In this context, recent initial evidence suggests that soil microorganisms contribute to the 'safety-net' role of the trees (Beule et al., 2022). Overall, these different measurements provide a better understanding of soil functioning in SAS and the parameters of the system influencing biodiversity.
### 6.3. Cultural services of biodiversity

AFS can provide several cultural services, including societal benefits (e.g. promoting and diversifying the local economy), recreation, and aesthetic values (Smith *et al.*, 2013). The aesthetic value of forests is notably dependent on the diversity of tree species and their multi-storey stands (Dudek, 2018). The greater diversity of species and habitats that SAS allows is also beneficial to biodiversity overall and it would be interesting to consider these benefits together. The aesthetic and recreational interest of SAS is not only due to the presence of trees but also to the overall biodiversity that develops in these systems. For example, it has been shown that plant diversity in an agricultural ecosystem is a fundamental parameter of people's aesthetic appreciation (Lindemann-Matthies *et al.*, 2010). Furthermore, bird population enhancement in SAS may be favourable for humans, since a more diversified and enhanced soundscape promotes human well-being (Ferraro et al., 2020). However, there do not appear to be any studies assessing both cultural services and biodiversity in SAS reported in the literature to date.

## 7. Prospects for future research

Many factors influence the observed effects of SAS on biodiversity and related services. However, these factors are still poorly understood and have only been addressed by a limited number of studies. Yet the conclusions that can be made about the link between SAS and biodiversity often depend on these numerous factors of influence. Studies considering various parameters and the main elements discussed in this review, as summarised in Figure 6, will allow a better understanding of the real impact of SAS on biodiversity and on the resulting ES, and will help to define the appropriate management modalities for this biodiversity, for agricultural production and for the entire socio-ecosystem. Given the resulting high heterogeneity of results, the information presented in this work is qualitative or presented in a vote-counting form. This is a limitation that could be solved by performing meta-analysis when enough data will be available to take into account the variability discussed (Russell et al., 2009).
Many of these parameters requiring future development have been discussed in the course of this article, but we can highlight some points that seem particularly important. These include the consideration of agricultural practices or models, since different modalities can lead to diametrically opposed results on organisms in SAS, as discussed for example in § 14.1. More generally, it is important to take into account all the potentially favourable factors for the species studied, i.e. favourable agricultural practices (absence of pesticides, no tillage, arable intercropping etc.) but also the presence, connectivity and quantity of SNH in the vicinity, the diversity of the surrounding

An ideal study on biodiversity in SAS:

-> Assesses **different taxa and Ecosystem Services**

-> Is performed at **different times** of the year and over **several years**

-> Is based on **several different protocols**

-> Performs analyses with **different biodiversity variables**, including **functional traits**

-> Evaluates different situations and comparisons:

-> Different locations

-> Different agricultural practices or models
(organic, conventional, conservation agriculture, etc.)

-> Different management of the SAS (mown or flowered UVS; density of woody vegetation, number of stages, etc.)

-> Different SAS (crop type; tree species, fruit and/or timber production, etc.)

-> Exposition to environmental stresses

-> Is performed in **mature SAS**, or evaluates the modifications **across time**

-> Is designed with **good controls and comparisons** (e.g. tree row + crop alley at different distances from the tree row + monocropping control) and **replicates** (however, this is often not possible)

-> Integrates **local variability** (landscape context, microclimate, soil type, etc.)

-> Is carried out jointly with **other disciplines** to have a general view of the problematic (SOC, yields, farmers and social perception, etc.)

-> Goes beyond a scientific publication by **widely disseminating information** (feedback and reports to farmers and all stakeholders, scientific popularisation, etc.)

**Figure 6: Theoretical ideal study on biodiversity and related ES in SAS.** The information presented is a synthesis of the elements identified that can help to carry out valuable studies, although applying them all together is not realistic. **SNH=Semi-Natural Habitats; SOC=Soil Organic Carbon.**

agricultural landscape, etc. Indeed, some practices such as avoiding pesticide use can condition the beneficial effects of SAS (see § 4.1. Pesticides and organic agriculture) while others could be redundant and thus limit the added value of SAS compared to a pure arable system (see § 4.3.2. Semi-natural habitats). Furthermore, synergies or antagonisms could occur between the effects of agroforestry and other practices, which should
be studied in the future. Finally, several practices and environments that favour biodiversity, even if they may
be partly redundant with the effects of SAS, can also allow a better resilience of the agricultural system.

In terms of the species studied, in addition to the existing disparity in the literature, some taxonomic groups
remain to be considered. For instance, we have not found any studies on chiropterans in temperate climates,
even though these species are highly protected (Hutson et al., 2001), are sensitive to changes in agricultural
practices (Barré et al., 2018a) and to tree presence in agricultural areas (Harms et al., 2020), and can play a
role in pest control (Charbonnier et al., 2021; Maslo et al., 2022). Reptiles and amphibians could also benefit
from the implementation of SAS, as tree rows could provide a favourable habitat for them, but this has not
been studied to date and is only mentioned in two publications. Regarding invertebrates, there are many
studies on groups like epigeal fauna, but much fewer publications describe groups such as detritivores and soil
fauna in general. Studies on taxa like springtails could be valuable since they are trophic resources for other
taxa and are good bioindicators of the management intensity of an environment (Heiniger et al., 2014; Perez
et al., 2013; Ponge et al., 2003).

Finally, SAS tree rows are mainly composed of relatively widely spaced monospecific trees. However, various
other tree row structures can be considered, by diversifying the species, the vegetation layers, the planting
density and the type of management that is implemented (see §4.2.1.). It is therefore possible to design tree
rows on a gradient ranging from isolated trees aligned on a grass strip to dense, multi-layer and diversified
hedges in the middle of a field. The associated biodiversity is expected to be higher in these more diverse AFS
(Malezieux et al., 2009). It would therefore be interesting to study the benefits and limitations of the different
modalities along this gradient for biodiversity and ES, but also in relation to agricultural production and other
ES provided by the SAS.

**8. Conclusion**

Current scientific knowledge on temperate SAS indicates that agroforestry in these arable environments has
a high potential to enhance biodiversity while providing various other ES to agricultural production, as well as
to the environment and to society. The introduction of trees within the fields and the associated UVS change
the conditions within the system, including the microclimate and the vegetation that are present, thus creating
a diversity of habitats for living organisms. This agricultural model is therefore beneficial for many taxa and
also has the potential to favour beneficial organisms (natural predators of pests, pollinators) and their services.

However, the benefits for ES are not systematic but may depend on certain parameters or management
modalities of SAS. Existing knowledge about what can modulate these benefits is relatively limited. It seems
that some parameters related to intensive practices (e.g. pesticide use) may be antagonistic and limit the
beneficial effects of SAS. Other parameters are either complementary (additive effect) or rendered redundant
by the beneficial effects of SAS. Furthermore, it would be necessary to assess how SAS could increase the
resistance or resilience of agricultural ecosystems in the case of redundant benefits.

The mechanisms involved in such diverse ecosystems are complex, and the results of studies that address
them depend on their quality and the way they are implemented. The species studied, the study protocols
and data analyses are therefore decisive elements, and it is important to adapt them to the research question
and make them as complete as possible.

The implementation of SAS has overall beneficial effects not only on biodiversity but also on many other
environmental and socio-economic parameters. The joint consideration of biodiversity, economics, agronomic
and climatic issues, resilience of the agricultural system and societal perception is still rare in the scientific
literature related to SAS and especially in original studies. However, it seems particularly important to make
the link between these different disciplines when seeking to meet the challenges and fulfil the goals of SAS
development.

AFS, and specifically SAS, are multifunctional agricultural systems that have the potential to provide significant
food and energy production, while delivering various benefits to farmers, promoting biodiversity, contributing
to environmental conservation and improving the living environment of citizens. Future studies on these
systems (see Figure 6) will need to support the achievement of these benefits and their development and
adoption by local stakeholders.
## 9. Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could be seen to influence the work reported in this paper.

## 10. Acknowledgements

We thank the two anonymous reviewers, and especially reviewer 2, for their fruitful comments, which have helped to significantly improve this review. We thank Joanna Lignot from Munro Language Services for her great help revising the English language of this article. We thank Thomas Vanneste for his reading and comments on this work.

This work was supported by The French Agence de l'Éau Rhin-Meuse and the Syndicat des Eaux Alsace-Moselle.

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<figure><img src="image_7.png" /><figcaption>Figure S1</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Figure S1
b)</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>Figure S1

(c)</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>Figure S1
d)</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>Figure S1 e)</figcaption></figure>
**Figure S1.** Response of different components of biodiversity and their associated services or disservices in SAS. Comparisons made are **a)** crop alley versus arable control, **b)** tree row versus crop alley, **c)** proximity of tree row, **d)** tree row versus forestry control or **e)** comparison of different system managements. 'Biodiversity conservation' gathers publications which specifically seek to assess biodiversity conservation. From **a)** to **d)**, '+' or '-' orapprox' symbols indicate respectively that the parameter is higher or lower or not significant/does not allow clear conclusion to be drawn, for a given biodiversity component. The colour symbols indicate whether the effect can be considered positive (green) or negative (red). In **e)**, 'V' symbol indicate an effect of the management considered in the publication. The width of the arrows is proportional to the number of publications presenting the parameter concerned. The numbers refer to the publications concerned, as detailed at the end of this figure legend. Numbers surrounded by a circle or a square or both indicate respectively that the variable reported is abundance or related measurement (e.g. activity-density, biomass), or other variables (e.g. richness, diversity), or both. For '+', '-' and 'V', only significant results have been considered, except when no stats were available (in that case, numbers are in grey instead of black). In **a)**, numbers with a grey background indicate that the arable control is not distant from SAS but adjacent or in a treeless part of the same field. In **d)**, the number with a grey background indicates that the comparison with forestry control is made from crop alley and not tree row.

1) (Peng et al., 1993); 2) (Park et al., 1994); 3) (Griffiths et al., 1998); 4) (Price and Gordon, 1998); 5) (Akbulut et al., 2003); 6) (Klaa et al., 2005); 7) (Muhammad et al., 2005); 8) (Mungai et al., 2005); 9) (Stamps et al., 2009b); 10) (Stamps et al., 2009a); 11) (Lacombe et al., 2009); 12) (Chifflot et al., 2009); 13) (Bainard et al., 2011); 14) (Bainard et al., 2012); 15) (Smits et al., 2012); 16) (Varah et al., 2013); 17) (Bardhan et al., 2013); 18) (Gibbs et al., 2016); 19) (Reino et al., 2016); 20) (Furze et al., 2017); 21) (Sun et al., 2018); 22) (Martin-Chave et al., 2019a); 23) (Beuschel et al., 2019); 24) (Martin-Chave et al., 2019b); 25) (Pardon et al., 2019); 26) (Cardinael et al., 2019); 27) (Boinot et al., 2019a); 28) (Boinot et al., 2019b); 29) (Pardon et al., 2020); 30) (Richard et al., 2020); 31) (Beuschel et al., 2020); 32) (Imbert et al., 2020a); 33) (Imbert et al., 2020b); 34) (Beule et al., 2020); 35) (D'Hervilly et al., 2020); 36) (Varah et al., 2020); 37) (Boinot et al., 2020); 38) (Staton et al., 2021b); 39) (Staton et al., 2021a); 40) (Beule and Karlovsky, 2021a); 41) (Puskaric et al., 2021); 42) (Beule et al., 2021); 43) (Beule and Karlovsky, 2021b); 44) (Staton et al., 2022); 45) (D'Hervilly et al., 2022)
**<u>Supplementary document 2: sampling methods</u>**

**Methods used in the publications analysed.** Biodiversity in agroecosystems can be measured with many different methods, depending on the target species. A summary of the main methods used in the selection of publications is shown in Figure 5, with respect to the taxonomic groups concerned. Certain methods are used very frequently, in particular pitfall trapping to study epigean arthropods. This is also the case for the most obvious method of biodiversity monitoring that is visual observation. It is used in many studies but its implementation depends on the objective and the target species. For animals, this can be done on vehicle transects for the observation of large organisms (birds: _Reino et al., 2016_), walking transects (birds: _Reino et al., 2016_; pollinators: _Varah et al., 2020, 2013_), fixed spots (birds: _Gibbs et al., 2016_; pollinators: _Staton et al., 2021a_; flying predators of pests: _Imbert et al., 2020a_), targeted observation of host plants (invertebrate pests: _Imbert et al., 2020a, 2020b_; _Muhammad et al., 2005_; _Staton et al., 2021b, 2021a_; predators of pests: _Imbert et al., 2020a_; _Muhammad et al., 2005_; _Staton et al., 2021a_; damage: _Griffiths et al., 1998_; _Staton et al., 2021a_), plant sampling (pollination: _Staton et al., 2021a_; non flying pests and predators: _Smits et al., 2012_) or animal hosts sampling (sampling and rearing of weevils to determine their rate of parasitism and mortality: _Stamps et al., 2009a_).

**Limits of the studies.** Several methods are generally available to study one taxon, each one presenting advantages and limitations (see McCravy, 2018, for a review of the different methods of studying arthropods). Methods such as pitfall traps measure for example a parameter integrating both the abundance of individuals and their activity (activity-density; Greenslade, 1964) whereas attractive traps attract particular taxa (McCravy, 2018). _Staton and collaborators (2021a)_ indicate that the sticky traps they used can generate a bias due to competition with the surrounding floristic resource. When measurements are made at a specific time or only part of the day, a bias due to the nychthemeral
activity of the organisms may occur (Stamps et al., 2009), especially when it is the activity-density that
is measured. To take this into account, Martin-Chave and collaborators (2019b) carried out
measurements with dry pitfall traps placed throughout the whole of a nychthemeral cycle and made
records every few hours. They were thus able to demonstrate a modification of the activity periods of
the carabid beetles according to the environmental conditions and the impact of the trees or their
management. To overcome the limitations of sampling methods, it is interesting to carry out
measurements using several different methods. Some studies have made this choice to broaden the
range of species measured and the representativeness of the data collected (e.g. Akbulut et al., 2003;
Bainard et al., 2012; Beuschel et al., 2020; Imbert et al., 2020a; Staton et al., 2021b, 2021a). Griffiths
and collaborators (1998) sampled slugs using three different methods: pipe traps, refuge traps and
pitfall traps. Pipe traps were found to be not very effective in terms of capture efficiency, but refuge
and pitfall traps gave similar results. For the study of soil microbial populations, there are a large
number of methods (see Figure 5). Given the size of these organisms, most of them are indirect
measures of the abundance or diversity of the populations. These include methods of genetic analysis
or nucleic acid composition (qPCR, sequencing, TRFLP (Terminal Restriction Fragment Length
Polymorphism), Denaturating Gradient Gel Electrophoresis), methods of analysis of the composition
of specific molecules (PhosphoLipid Fatty Acid analysis, amino sugars, glomalin), or of enzymatic
activity. The profiles obtained or the presence and abundance of certain molecules thus make it
possible to evaluate the abundance, relative diversity or overall diversity of certain microbial
populations, depending on the protocol. Beule and collaborators (2021) highlight that amplicon
sequencing, which allows the determination of the relative abundance of different groups of
microorganisms, can lead to erroneous conclusions if performed alone. They indicate that it is
necessary to couple these methods with absolute quantification methods like qPCR, allowing the size
of each population to be assessed. Some other methods estimate the total microbial biomass in C or
N (fumigation-extraction) or directly evaluate the abundance or characteristics of the organisms, for
fungi in particular (spore density, hyphal length, root colonisation). Thus, several methods can also be
used together to obtain a more complete picture of soil microbial populations and their response to
cropping systems. Other methods not reported in the considered publications can also be used and of
interest. Camera traps are a good tool to assess the activity of vertebrates (Meek et al., 2014; Trolliet
et al., 2014). Nesting boxes occupancy can give valuable information on bird but also mammal
populations and facilitate further studies on individuals (capture-mark-recapture, reproduction
success, etc.; Fokidis and Risch, 2005; Stier et al., 2016). Finally, environmental DNA brings information
on many populations of organisms present in ecosystems, and has become time and cost effective
(Deiner et al., 2017; Hassan et al., 2022)

**Methods to study biological processes.** The abundance or diversity of organisms within an ecosystem is not necessarily directly related to the services or disservices provided. It is therefore important to complete population surveys with measures of their impact on the agroecosystem, i.e. effective biocontrol, pollination, crop damage or even soil functioning. As mentioned by Marsden and collaborators (2020), such measures are scarce in the scientific literature linked to our subject. They are however performed in some studies within SAS (see Figure 5). For example, Griffiths and collaborators (1998) showed that slug damage to crops was correlated with slug numbers measured in pitfall and pipe traps. Muhammad and collaborators (2005) observed both that there were more aphids and that they were less parasitized in the arable control than in the arable lane. However, Martin-Chave and collaborators (2019a) measured higher predation under the influence of trees but the relationship with the predator populations present was less clear. Varah and collaborators (2020) have shown a better pollination in SAS, linked to a higher abundance of different groups of pollinators. Finally, concerning soils, Beuschel and collaborators (2019) have shown that the presence of trees in relation to the arable environment generates a shift in the composition of microbial populations and their functional diversity, and that this is concomitant with greater microbial activity (respiration and enzymatic activity). Parameters such as yields, production quality or SOC are strongly influenced by the activity of organisms within the ecosystem, but they are also influenced by other parameters (inputs, climatic conditions, soil type, etc.).
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