1 INTRODUCTION

Fast-paced global change is currently impacting a number of crucial ecological factors that trigger plant range shifts. Recently, robustly supported evidences including spatial mismatches among interacting species caused by climate change (Schweiger et al., 2008), natural recolonization of abandoned agricultural lands (Escribano-Avila et al., 2014) or natural expansion (García et al., 2014) have shown plant abilities to naturally regenerate, disperse and colonize new habitats over short time spans. In most cases, a clear involvement of a diverse array of plant–animal interactions has been documented shaping the plant movements. For instance, mutualistic interactions such as animal-mediated seed dispersal are necessary to trigger rapid responses for plants to respond efficiently to global change drivers (González-Varo et al., 2021). However, the role that antagonistic interactions may play in limiting or facilitating plant range shifts in response to these factors is largely unknown.

Plant populations in natural range expansion scenarios are characterized by a mature population that acts as a source of propagules heading towards recently established areas, known as the colonization front (Shigesada & Kawasaki, 2002). Plant stand features such as individual density, spatial cover or demographic and genetic structure vary in these range shift processes (Excoffier et al., 2009; Petit, 2011; Shigesada & Kawasaki, 2002). Population expansion often involves a complex network of interactions with animals that either facilitate expansion (e.g. seed dispersers, pollinators) or constrain it (e.g. herbivores, seed predators). The outcome and balance between positive (mutualistic) and negative (antagonistic) interactions with other effects (e.g. interspecific competition) may pervasively determine the dynamics of plant movements (Svenning et al., 2014). It is important to explicitly represent interspecific interactions in forecasts of dynamic range expansion when most interacting species show correlated spatio-temporal trends in their effects and the number of interacting species is low (Svenning et al., 2014). The presence of active expansion fronts necessarily associates with such spatial and geographical variation in interaction conditions (Travis, 1996). One of the possible hypotheses linking natural expansion processes and plant–animal interactions is the enemy release hypothesis (Keane & Crawley, 2002). This release from enemies facilitates the expansion through a reduction or elimination of antagonistic agents, repeatedly documented during expansions of alien species (Meijer et al., 2016). Antagonistic plant–animal interactions related to reproductive fitness play a key role during processes restructuring plant populations. For example, by increasing interactions intensity or releasing their pressure, these could constrain or allow early regeneration processes (Keane & Crawley, 2002; Svenning et al., 2014) or determine species richness (Janzen, 1970). These are likely processes during colonization from source stands, yet we still have a limited understanding regarding how biotic interactions and ecological factors result in observed range dynamics.

Antagonistic interactions with animals and their effect on plants can deeply affect plant reproductive output (Sallabanks & Courtney, 1992; Strauss & Irwin, 2004). These interactions could determine seed source limitation: plants are simply unable to produce enough propagules to ‘fill’ available target microsites for recruitment (Münzbergová & Herben, 2005; Schupp, 2002). Antagonistic and mutualistic interactions in nature are embedded, building complex networks with species from very different taxa (Fontaine et al., 2011; Morris et al., 2014) and result in combined effects on plant fitness (Harper, 1977). Predispersal seed predation occurs in advance to other potentially limiting effects that act on seed dispersal, such as recruitment or regeneration limitation (Nathan & Muller-Landau, 2000; Schupp, 2002). In fleshy fruited species, predispersal predation interactions may involve direct seed destruction (Fuentes & Schupp, 1998; González-Varo, 2010), fruit infestation by insect pests and other pathogens (García, 1998) and fruit/seed damage by pulp peckers and seed predators (Simmons et al., 2018; Snow & Snow, 1988). Subsequently, predation on dispersed seeds is performed by major seed predators and non-legitimate seed dispersers including insects, mammals and birds (Hulme & Benckman, 2002; Janzen, 1971). The magnitudes of predispersal seed predation are usually relatively low (Janzen, 1971; Kolb et al., 2007; Xu et al., 2015), although sometimes can compromise a large part of the available propagules (Crawley, 2000; Guido & Roques, 1996). How assemblages of predispersal seed–pulp predators are reshaped along plant regeneration gradients remains underexplored (Sallabanks & Courtney, 1992).

Tools from ecological networks theory have recently proven most effective in assessing the complex patterns of plant–animal interactions (Bascompte & Jordano, 2014). However, network models are typically built on species-averaged estimators, ignoring variability among individuals in their interaction patterns (Dupont et al., 2014; Melián et al., 2014). By averaging, the importance of individual biotic and abiotic context in the establishment of interactions is neglected (Rodríguez-Rodríguez et al., 2017; Thompson, 1988; Valverde et al., 2016). This approach has pervasive consequences for the inferences and results interpretation. For example, aggregated data from many individuals subject to spatio-temporal variation are used to produce species-level averages, which marginalize away the relevant (process-level) scale (Clark et al., 2011). It is important to note that the partners in interactions in nature are individuals, not the species to which they belong. This fine scale is the most appropriate when assessing factors structuring interaction networks between plants and animals (Dupont et al., 2011). An individual-based approach is a powerful tool to understand the role of predispersal antagonistic interactions during plant range expansion, and factors that structure them. Any interaction shaped by individual phenotypes (with heritable potential) that could modify individual plant fitness can be an important selective force for trait evolution (Strauss et al., 2005; Strauss & Irwin, 2004). At the intra-population level, both intrinsic and extrinsic individual plant attributes play a role in interactions with predispersal antagonists (Schupp et al., 2019). The main intrinsic traits are those related to individual fecundity, plant physical features and seed–fruit traits. Meanwhile, extrinsic plant attributes such as location, isolation and neighbourhood also play a role in the assembly of antagonists (Schupp et al., 2019).

Novel analytical tools like Exponential Random Graph Models (ERGMs) allow us to unravel the determining factors of the complex structure of interaction networks (Morris et al., 2008; Saul & Filkov, 2007) and are extremely effective in addressing individual-scale variation. Analogously to a generalized linear model, ERGMs are based on a response variable which is the structure of the network itself (link distribution among nodes), and predictor variables with information associated with each specific network node (i.e. plant attributes). Thus, it is possible to compare the structure of an observed network with that generated by models that include or exclude specific node information. These models have been recently introduced in ecological research (Arroyo-Correa et al., 2021; Miguel et al., 2018), providing ways to infer causes determining the distribution of the interactions among network nodes (Kolaczyk & Csárdi, 2014). The relative roles of intrinsic and extrinsic traits in interaction network structures have been evaluated for mutualistic networks (Arroyo-Correa et al., 2021; Miguel et al., 2018; also see Gómez et al., 2011; Valverde et al., 2016), although how these factors drive antagonistic network topologies at the individual level remains unexplored.

In this study, we focused on the predispersal antagonistic assemblage of seed–pulp predators of Juniperus phoenicea subsp. turbinata. Juniperus phoenicea is considered as a foundation species (Whitham et al., 2006) and has undergone a rapid expansion since the protection of Doñana National Park five decades ago (García et al., 2014). This plant range expansion setting, involving a diverse assemblage of predispersal antagonists, is ideal for examining how interaction networks are restructured at the individual level across colonization stages, and the factors that determine these shifts in network structure. We expect a reconfiguration of interaction networks along the colonization gradient that would explain the rapid expansion of this population (e.g. through a release of antagonistic interactions in recently established stands). Furthermore, we hypothesize that the individual-based network topologies are being driven by individual traits and neighbourhood context. Specifically, the main goals in this study were: (i) Describe the individual-based network of J. phoenicea and its assemblage of predispersal seed–pulp predators. (ii) Examine how these interactions are reshaped along a natural gradient of colonization through basic network descriptors and the species and the spread of interactions across individual plants. (iii) Assess the role of plant traits and neighbourhood context as drivers of network topology. (iv) Evaluate the consistency of network topology drivers during plant range expansion.

中文翻译：

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植物范围扩展期间基于个体的对抗性交互网络的驱动因素

1 简介

快节奏的全球变化目前正在影响一些引发植物范围变化的关键生态因素。最近，有力支持的证据包括气候变化引起的相互作用物种之间的空间错配（Schweiger 等人，  2008 年）、废弃农业用地的自然重新殖民化（Escribano-Avila 等人，  2014 年）或自然扩张（García 等人，  2014 年）) 已显示植物在短时间内自然再生、分散和殖民新栖息地的能力。在大多数情况下，已经记录了各种植物-动物相互作用的明确参与，这些相互作用塑造了植物的运动。例如，动物介导的种子传播等互惠相互作用对于触发植物快速响应以有效应对全球变化驱动因素是必要的（González-Varo 等人，  2021 年）。然而，拮抗相互作用在限制或促进响应这些因素的植物范围变化方面可能发挥的作用在很大程度上是未知的。

自然范围扩张情景中的植物种群的特点是成熟种群作为繁殖体的来源，这些种群朝向最近建立的区域，称为殖民前沿（Shigesada & Kawasaki，  2002）。个体密度、空间覆盖或人口和遗传结构等植物林分特征在这些范围转移过程中会发生变化（Excoffier 等人，  2009 年；Petit，  2011 年；Shigesada 和川崎，  2002 年）。种群扩张通常涉及与动物相互作用的复杂网络，这些网络要么促进扩张（例如种子传播者、传粉媒介），要么限制扩张（例如食草动物、种子捕食者）。正（互利）和负（对抗）相互作用与其他效应（例如种间竞争）之间的结果和平衡可能普遍决定植物运动的动态（Svenning 等，  2014）。当大多数相互作用的物种在其影响中显示出相关的时空趋势并且相互作用物种的数量很低时，在动态范围扩展的预测中明确表示种间相互作用是很重要的（Svenning et al.,  2014）。积极扩张前沿的存在必然与互动条件中的这种空间和地理变化相关联（特拉维斯，  1996 年）。将自然扩张过程和植物-动物相互作用联系起来的可能假设之一是敌人释放假设（Keane & Crawley，  2002）。这种从敌人身上的释放通过减少或消除拮抗剂来促进扩张，在外来物种扩张过程中反复记录（Meijer et al.,  2016）。与生殖适应性相关的拮抗动植物相互作用在植物种群重组过程中起着关键作用。例如，通过增加相互作用强度或释放它们的压力，这些可以限制或允许早期再生过程 (Keane & Crawley,  2002 ; Svenning et al.,  2014 ) 或确定物种丰富度 (Janzen,  1970 )。这些可能是从源站定殖期间的过程，但我们对生物相互作用和生态因素如何导致观察到的范围动态的理解仍然有限。

与动物的拮抗作用及其对植物的影响会严重影响植物的生殖产量（Sallabanks & Courtney,  1992 ; Strauss & Irwin,  2004）。这些相互作用可以决定种子来源的限制：植物根本无法产生足够的繁殖体来“填充”可用的目标微型站点进行招募（Münzbergová & Herben,  2005 ; Schupp,  2002）。自然界中的拮抗和共生相互作用是嵌入的，与来自非常不同的分类群的物种建立复杂的网络（Fontaine 等人，  2011 年；莫里斯等人，  2014 年），并导致对植物适应性的综合影响（哈珀，  1977 年））。散布前的种子捕食发生在其他对种子散布起作用的潜在限制作用之前，例如补充或再生限制（Nathan & Muller-Landau，  2000；Schupp，  2002）。在肉质果实物种中，分散前的捕食相互作用可能涉及直接种子破坏（Fuentes & Schupp,  1998 ; González-Varo,  2010）、昆虫害虫和其他病原体侵扰果实（García,  1998）以及果肉啄木鸟和种子对果实/种子的损害捕食者（Simmons 等人，  2018 年；Snow & Snow，  1988 年）。随后，主要的种子捕食者和非法的种子传播者（包括昆虫、哺乳动物和鸟类）对散播的种子进行捕食（Hulme & Benckman，  2002 年；Janzen，  1971 年）。预分散种子捕食的幅度通常相对较低（Janzen，  1971；Kolb 等，  2007；Xu 等，  2015），尽管有时会损害大部分可用的繁殖体（Crawley，  2000；Guido & Roques，  1996 年）。如何沿着植物再生梯度重塑预分散种子浆捕食者的组合仍未得到充分探索（Sallabanks 和 Courtney，  1992 年）。

生态网络理论的工具最近被证明在评估动植物相互作用的复杂模式方面最为有效（Bascompte & Jordano，  2014 年）。然而，网络模型通常建立在物种平均估计量之上，忽略了个体之间交互模式的可变性（Dupont 等人，  2014 年；Melián 等人，  2014 年）。通过平均，个体生物和非生物环境在建立相互作用中的重要性被忽略（Rodríguez-Rodríguez 等人，  2017 年；汤普森，  1988 年；Valverde 等人，  2016 年））。这种方法对推论和结果解释具有普遍的影响。例如，来自许多受时空变化影响的个体的汇总数据被用于产生物种水平的平均值，从而将相关（过程水平）尺度边缘化（Clark et al.,  2011）。重要的是要注意，自然界相互作用的伙伴是个体，而不是它们所属的物种。在评估构建动植物相互作用网络的因素时，这种精细的尺度是最合适的（Dupont et al.,  2011）。基于个体的方法是了解在植物范围扩展过程中预分散拮抗相互作用的作用以及构成它们的因素的有力工具。任何由个体表型（具有遗传潜力）形成的可以改变个体植物适​​应性的相互作用都可以成为性状进化的重要选择力量（Strauss et al.,  2005 ; Strauss & Irwin,  2004）。在种群内水平上，内在和外在的个体植物属性在与预分散拮抗剂的相互作用中发挥作用（Schupp 等人，  2019）。主要的内在性状是与个体繁殖力、植物物理特征和种子-果实性状有关的那些。同时，位置、隔离和邻域等外在植物属性也在拮抗剂的组装中发挥作用（Schupp et al.,  2019）。

指数随机图模型 (ERGM) 等新型分析工具使我们能够解开交互网络复杂结构的决定因素（Morris 等人，  2008 年；Saul & Filkov，  2007 年），并且在解决个体尺度变化方面非常有效。类似于广义线性模型，ERGM 基于响应变量，该响应变量是网络本身的结构（节点之间的链路分布），以及具有与每个特定网络节点相关联的信息（即植物属性）的预测变量。因此，可以将观察到的网络的结构与包含或排除特定节点信息的模型生成的结构进行比较。这些模型最近被引入生态研究（Arroyo-Correa et al., 2021 ; Miguel 等人，  2018 年），提供了推断原因的方法，以确定网络节点之间的交互分布（Kolaczyk & Csárdi，  2014 年）。交互网络结构中内在和外在特征的相对作用已针对互惠网络进行了评估（Arroyo-Correa 等人，  2021 年；Miguel 等人，  2018 年；另见 Gómez 等人，  2011 年；Valverde 等人，  2016 年） )，尽管这些因素如何在个人层面驱动对抗性网络拓扑结构仍未探索。

在这项研究中，我们专注于Juniperus phoenicea subsp. 的种子 - 纸浆捕食者的预分散拮抗组合。鼻甲_ Juniperus phoenicea被认为是基础物种（Whitham 等人，  2006 年），自 50 年前多纳纳国家公园受到保护（García 等人，  2014年）以来经历了快速扩张）。这种植物范围扩展设置涉及多种预分散拮抗剂组合，非常适合检查相互作用网络在个体水平上如何在殖民化阶段进行重组，以及确定网络结构这些变化的因素。我们期望沿着殖民梯度重新配置相互作用网络，这将解释这个种群的快速扩张（例如，通过在最近建立的立场中释放对抗性相互作用）。此外，我们假设基于个体的网络拓扑是由个体特征和邻域环境驱动的。具体来说，本研究的主要目标是：(i) 描述J. phoenicea的基于个体的网络以及它的预分散种子 - 纸浆捕食者的组合。(ii) 检查这些相互作用如何通过基本网络描述符和物种以及相互作用在单个植物之间的传播沿着自然的定殖梯度进行重塑。(iii) 评估植物性状和邻里环境作为网络拓扑驱动因素的作用。(iv) 在工厂范围扩展期间评估网络拓扑驱动程序的一致性。