Neighbor Effects Research Articles

Computational Analysis of Wind Neighborhood Effects on Buildings: A Comparison Between Closure Models for Turbulence

Determining the neighboring effects of wind is a complex task, as generic approaches are often unable to accurately capture the interactions between buildings and their surrounding environment. For this reason, standard guidelines may be insufficient for determining these effects, making it necessary to rely on wind tunnel testing or numerical simulations through computational fluid dynamics (CFD). This study presents an analysis of the changes in aerodynamic coefficients of the CAARC (Commonwealth Advisory Aeronautical Research Council) building due to the presence of neighboring structures that interfere with wind flow. The neighborhood consists of eight blocks with proportions of 1:1:3. Turbulence was modeled using the Reynolds-Averaged Navier-Stokes (RANS) approach, employing the k-omega and k-omega SST turbulence closure models. A comparative analysis of the results obtained from these two models is presented. The study was conducted by varying the system’s orientation from 0 to 90 degrees in 15-degree intervals. Results show that the perimeter buildings create a shielding effect on the centrally located CAARC building, leading to a reduction in the drag coefficient. Additionally, for some angles, the presence of neighboring structures caused an increase in the torsional and lift coefficients.

Total Synthesis of the Tridecasaccharide Motif fromAngelica sinensisAPS-1 II Polysaccharide with Anti-leukemia Activity and Structure-Activity Relationship Studies.

A polysaccharide APS-1 II from a medicinal plant Angelica sinensisrepresents an interesting therapeutic agent against leukemia. However, the synthetic accessibility of the highly branched and complex APS-1 II polysaccharide with multiple 1, 2-cis-glycosidic linkages remains a difficult task, impeding the in-depth structure-activity relationship biological studies and the development of carbohydrates-based therapeutics against leukemia. Here, we report the first chemical synthesis of tridecasaccharide repeating unit together with shorter sequences 4-mer, 6-mer and 9-mer from APS-1 II polysaccharide via one-pot orthogonal glycosylation strategy based on glycosyl ortho-(1-phenylvinyl)benzoates, which precluded the potential issues such as aglycone transfer associated with one-pot assembly with thioglycosides. The synthetic pathway also features the following aspects: 1) three contiguous and challenging 1, 2-cis-Fuc bonds were highly stereoselectively constructed via the newly developed stereoselective 1, 2-cis-fucosylation method; 2) several 1, 2-trans-glycosidic linkages were formed via neighboring group participation effect, while 1,2-cis-Glc linkage was stereoselectively assembled via N,N-dimethylformamide reagent modulation; 3) the final [1+1+2+9] one-pot assembly of the target tridecasaccharide via strategic utilizations of glycosyl N-phenyltrifluoroacetimidates, ortho-alkynylbenzoates and ortho-(1-phenylvinyl)benzoates. Biological studies revealed that human leukemia K562 and mouse L1210 cells could be effectively inhibited by tridecasaccharide repeating unit andnonasaccharide.

Grain orientation and grain neighboring effects on deformation twin of Sn behind the brittle fracture of cryogenic electronics

Grain orientation and grain neighboring effects on deformation twin of Sn behind the brittle fracture of cryogenic electronics

Neighboring effects of single-atom cobalt enable high-performance CO2 photoreduction

A facile strategy has been reported for anchoring Co single atoms on BiOCl nanosheets to enable efficient CO2 photoreduction, and the neighboring effect of single-atom cobalt has been clarified by in situ X-ray photoelectron spectroscopy.

Contaminated water spillovers or peer effects? Determinants of disease outbreaks in shrimp farming in Vietnam

AbstractDisease outbreaks are one of the major issues in the aquaculture sector and can lead to significant economic losses. Although the source of the disease is difficult to trace, understanding how it occurs is important to mitigate the problem. A crucial factor that has not received sufficient attention is the presence of spillovers among fish farmers connected by waterways. This study examines the presence of spillovers among shrimp farmers in Southern Vietnam based on primary data. In particular, it quantifies the effects of contaminated water spillovers from one farm to another and the peer effects of farming practices among neighbors. We solve the reflection problem by employing a method developed in social network analyses. The findings indicate that a farmer's practices are affected by their neighbors’ farming practices. Further, the disease outbreak in a farmer's pond is affected by those in their neighbors’ ponds, even after controlling for contextual peer effects and correlated effects. The negative effects of neighbors’ ponds on the probability of disease outbreaks in a farmer's pond may offset the positive effects of the farmer's good farming practices, suggesting the importance of considering neighboring farmers as a group when addressing the issue of disease control.

Neighbor effects on population growth rate differ among populations due to variation in demographic rate sensitivities in Sedum lanceolatum

Population growth rates will respond to an environmental driver only if the driver impacts demographic rate(s) and the population is sensitive to impacted demographic rate(s). If populations vary in the sensitivity of population growth rate to demographic rates, the effect of an environmental driver on population growth rate could vary across populations, even if the effect of the driver on demographic rates does not vary across populations. Here, we use five years of demographic data of a common alpine plant, including data from a neighbor removal experiment and a climate warming experiment, to quantify the relative contribution of neighbor effects on demographic rates versus sensitivity of population growth rate to demographic rates to across‐population variation in neighbor effects on population growth rate. We find neighbor effects on population growth rate vary significantly across populations, and this effect is driven primarily by variation in sensitivity of population growth rate to demographic rates across populations. Further, results from our climate warming experiment suggests variation in sensitivity across populations is partly driven by temperature differences. Our results highlight the importance of considering changes in the sensitivity of population growth rate to demographic rates across space, and show how changes in sensitivity can contribute to spatial variation in the effects of a driver on population growth rate.

Boosting low-temperature CO2 methanation activity through Tailored electronic structures and step-edge defects in Niε−-Ov-Ceδ+ inverse interfaces

Inverse interfacial oxygen vacancies (OVs) are expected to efficiently activate CO2, thereby enhancing low-temperature CO2 methanation activity. However, the mechanisms of electronic structure modulation and the interface-activity relationships remain ambiguous. This study constructs three CeO2/Ni inverse catalysts, with CeO2/Ni-4 showing abundant Niε−-Ov-Ceδ+ (ε > 0, δ < 3) interfaces featuring step-edge defects. These structures lower the oxygen vacancy formation energy (0.68 eV) and promote electron transfer from Ni-O to Ce (0.05 e−), facilitating Ceδ+ (δ < 3) formation. This process results in plentiful interfacial OVs and moderately basic sites, while Ceδ+ can donate electrons to the OVs, collectively enhancing CO2 activation. Additionally, the Niε−-Ov-Ceδ+ interface structure creates a wealth of high-electron-density active Niε− sites (−0.3 e−), which facilitates the adsorption and activation of H2. The neighboring effect of Ni-Ov also promotes rapid hydrogen spillover from Ni to Ov. As a result, the CeO2/Ni-4 catalyst achieves a low activation energy of 55.4 kJ·mol−1, and reaches 67.5 % CO2 conversion with 100 % CH4 selectivity at a temperature as low as 225℃. In-situ DRIFTS results reveal that the reaction follows the formate pathway, highlighting that the abundant Niε−-Ov-Ceδ+ inverse interfaces can swiftly generate m-CO3*. Subsequently, m-HCOO* reacted with decomposed H* from adjacent Ni sites to produce CH4.

Has Green Insurance Ensured the Realization of China 's Dual Carbon Goals?

As an essential risk guarantee and economic compensation mechanism to construct green and low-carbon circular economic development system, the role of green insurance in the field of energy conservation and emission reduction remains a realm yet to be explored substantially. Based on the panel data of 30 provinces in China from 2005 to 2019, the influence and theoretical mechanism of green insurance on carbon emissions were analyzed by the construction of intermediary effect model and moderating effect model. Additionally, the spatial spillover effect was explored by the spatial Durbin model. The results show that: (1) Green insurance has a significant inhibitory effect on carbon emissions, which retains salience across the spectrum of endogenous tests and stability tests. (2) Both the “local effect” and “neighboring effect” of green insurance on carbon emissions are inhibitory, displaying “simultaneous resonance” characteristics based on the spatial perspective. In view of the above conclusions, this thesis provides policy suggestions for promoting the construction of a diversified and collaborative green insurance system and enriching carbon emission reduction paths.

Studying the Impact of LULC Correspondence Between Landsat 8 and Spot 7 Data on Land Surface Temperature Estimation

Information about land surface temperature (LST) plays a crucial role in environmental studies, as it provides essential data for understanding climate patterns, assessing ecosystem health, and predicting environmental changes. Understanding the relationship between land cover types and LST is crucial across all disciplines that deal with LST data. It helps researchers identify trends in global warming, heatwaves, and cooling effects, which can influence biodiversity, agriculture, and water resources. The accuracy of LST calculations heavily depends on the quality of the data used. However, most satellite thermal data used for LST estimations are in coarse spatial resolution. This study aims to explore the complex interaction between land cover types, considering factors such as proportion and neighboring effects, and LST recalculation by integrating the estimated LST from Landsat thermal band and Spot imagery classification. A machine learning model was employed to quantify the contribution of each Spot pixel to the LST estimated from TIRS data, classifying it as either heating or cooling. The Al Morjan and Al Hamra districts in Jeddah, Saudi Arabia, were used as case studies. The results showed that Spot images achieved a classification accuracy of over 95%, whereas Landsat images did not exceed 77%. The average heating and cooling factors from neighboring pixels were 1.06 and 0.96, respectively. The study demonstrates the improved spatial distribution of LST, with overall temperature increases across all land cover classes. The findings of this study could aid in identifying environmental imbalances and developing effective solutions.

The Specific Impacts of Allelopathy and Resource Competition from Artemisia frigida on the Growth of Three Plant Species in Northern China.

Plant interference is a key factor influencing plant coexistence and species composition. The two primary forms of plant interference-allelopathy and resource competition-are often difficult to separate. This study conducted an outdoor pot experiment to quantify the distinct contributions of resource competition and allelopathy of Artemisia frigida on seedling growth of three species: Leymus chinensis, Cleistogenes squarrosa, and Potentilla acaulis. The index of relative neighbor effect (RNE) was used to quantify the overall effect of plant interference, while the inhibition rates (IRs) of resource competition and allelopathy were utilized to determine the specific contributions of allelopathy and resource competition from A. frigida on the growth of target plant species. The interference effect of A. frigida was found to be species-specific. The allelopathic effect of A. frigida played a major role in inhibiting the belowground biomass of L. chinensis (23.97%) and C. squarrosa (58.27%), while allelopathy and resource competition from A. frigida promoted the belowground biomass (45.12%) and aboveground biomass (46.63%) of P. acaulis, respectively. The combined effect of allelopathy and resource competition from A. frigida significantly affected the aboveground biomass of C. squarrosa and P. acaulis, as well as the belowground biomass of L. chinensis and C. squarrosa. These findings contribute to a better understanding of the patterns and mechanisms of plant species composition and its relationship with grazing intensity in this grassland ecosystem.

Design of Bimetallic Boronene Structures Leveraging Neighboring Effects for Efficient Electrocatalytic CO2 Reduction Reaction

AbstractElectrocatalytic CO2 reduction (CO2RR) offers a promising avenue to address rising atmospheric CO2 levels by producing high‐value chemicals. However, the development of efficient, long‐lasting catalysts remains challenging. In this study, particle swarm optimization is employed to design a novel bimetallic boronene structure, thereby enhancing CO2RR activity through precise tuning of the metal‐substrate microenvironment. Through high‐throughput screening, seven CuMB4 (M = V, Zn, Nb, Ag, Cd, Ta, Au) monolayers are identified as promising CO2RR catalysts based on stability, conductivity, catalytic activity, and selectivity. These materials, characterized by hyper‐coordination and neighboring bimetallic effects, are proposed for synthesis via self‐assembled surface growth. Notably, CuZnB4 exhibited exceptional theoretical catalytic activity, characterized by remarkably low limiting potentials (UL) of −0.16 V for CH4 and −0.27 V for C2H4, as well as low kinetic barriers of 0.65 and 0.53 eV, respectively. The enhanced activity results from neighboring effects optimizing densely populated boron active sites and the ability to suppress hydrogen evolution reactions. Additionally, this study explored intrinsic properties influencing catalytic activity using volcano plots, descriptor analysis, and electron density evaluation. Unlike traditional catalysts prone to oxidation, CuMB4 varieties possess self‐activating properties, facilitating the conversion of *O/*OH to H2O and enhancing CO2 conversion. This research introduces robust CO2RR catalysts and provides insights into manipulating neighboring effects, thus guiding future catalyst design.

Differences in species composition between calcareous and siliceous herbaceous communities are primarily explained by competition in favourable climates

Difference in vegetation composition between communities from calcareous and siliceous soils might be due to high competition on siliceous soils for species from calcareous origin, and high rock‐induced drought stress on calcareous soils for species from siliceous origin. We tested the hypothesis that, with increasing climate stress, competition should decrease on siliceous rock for species of calcareous origin and drought stress increase on calcareous rock for species of siliceous origin because of decreasing community biomass with increasing cold or drought stress. This question is of high interest for predicting changes in species distribution with climate change since bedrock type and climate change are both complex factors that are likely to interact with climate. We set up a transplant removal experiment in contrasting climate conditions of the south of France, warm and wet temperate, warm and dry Mediterranean, and cold temperate in the Alps and the Pyrenees. In each climate condition, three targets (two species and one population from a third species) from each origin were transplanted with and without neighbours on the two rock types and during two years with different levels of drought stress. Variation in the effects of neighbours and rock‐induced drought stress on transplant survival with and without neighbours were analysed with linear modelling at each site, separately, and with ANCOVA in the whole design. Competition was the highest on siliceous rock in the more favourable climate conditions but for species of siliceous origin. The lower competition found for species of calcareous origin was likely due to the occurrence of allelopathic effects that decreased the negative effect of neighbours as measured with the removal method. The rock‐induced drought stress was the highest on calcareous rock, in particular for species of siliceous origin. Thus, the decrease in competition intensity on siliceous rocks with increasing climate stress was more important for species from siliceous than calcareous origin. Additionally, the importance of the rock‐induced drought stress was relatively low in the most stressful climate conditions as compared to the overwhelming importance of climate drought stress over the two years of our experiment, which likely induced a collapse of the positive effect of growing on a siliceous rock.

Exactly solvable dual bus-route model.

In 1998, O'Loan etal. introduced a simplified bus-route model to illustrate bus dynamics. However, fluctuations in passenger numbers make it challenging to achieve an exact solution for the model's stationary state, as these fluctuations can impact bus behavior. In this study, we present an exactly solvable model for a dual bus-route system that builds upon O'Loan etal.'s model. This dual model allows us to comprehensively analyze bus-route dynamics. Our model introduces additional parameters not previously considered by O'Loan etal. to account for neighboring effects and align with an observation in the original model, which can influence the average stationary current and velocity of buses. When the neighboring effect is weak, our model behaves similarly to O'Loan etal.'s bus-route model. However, with a strong neighboring effect, our model exhibits intriguing characteristics. Additionally, in some limiting cases, our model recovers well-known models such as the simple exclusion process, its generalization, the cooperative exclusion process, and the RNA polymerase model during the elongation stage.

‘They adopt, I also adopt’: The neighborhood effects and irrigator farmers’ conversion to adopt water-saving irrigation technology

Promoting water-saving irrigation technology (WSIT) has long been recognized as an effective measure to reduce irrigation water use and alleviate regional water poverty. Neighbours are the groups with the most interaction, the most intensive contact and the most frequent communication in agricultural production. In this paper, based on a field survey of irrigator farmers of China, experiments were conducted to evaluate the contribution of neighbour effect to farmers’ WSIT behaviour and its moderating mechanism between neighbour effect and technology adoption. The results show 26.7 % farmers adopt water-saving technology and these farmers often have strong neighborly relationships. In particular, neighbor effect significantly promote WSIT adoption by 42.1 % and farmers with strong neighborly effects apply significant higher technology compared to farmers with weak neighbourly effects. Furthermore, mechanism results indicated that neighbour effects indirectly influence farmers' adoption of water-saving irrigation technology through three pathways: reducing information search costs, mitigating agricultural production risks and benefiting from the demonstration effect. Moreover, the heterogeneous results report that higher-income, lower digital and lower training frequency farmers will benefit more from the NE in terms of WSIT. Overall, this research provides a micro foundation and policy implications for the promotion of WSIT, and sheds light upon how the government can formulate relevant policies to promote the sustainable development of agricultural water resources.

Strip cropping increases yield and revenue: multi-year analysis of an organic system in the Netherlands

Intercropping is proposed as a promising strategy to meet future food demand while reducing agriculture’s environmental impact by re-diversifying agricultural fields. Strip cropping, a form of intercropping, has a potential to simultaneously deliver multiple ecosystem services including productivity, while facilitating management as strip width can be adjusted to the working width of available machines. While the yield performance of strip cropping systems is influenced by the interaction between neighboring crops, to date, empirical studies on the performance of various crop combinations in strip cropping systems are limited. Here we used three-year data (2020–2022) from a 64-ha organic strip cropping system in the Netherlands to (1) evaluate the effects of crop neighbors and strip cropping on yield and (2) explore if optimizing the allocation of crop neighbors in alternative strip cropping configurations can improve yield and revenue performances. We analyzed the edge effect and strip cropping effect on yield of six crops grown in strips, each neighboring a total of five crops. The yield data was then used to evaluate the performance of the current and alternative strip configurations in terms of LER and relative revenue. Results showed that except for the positive effect observed on potato when neighboring celeriac or broccoli, edge effects lacked statistical significance. Strip cropping effect varied per crop: positive for faba bean and parsnip, neutral for celeriac and potato, and negative for oat and onion. Analysis across crops showed an overall significant positive strip cropping effect on yield. These findings highlighted the value of analysis at the cropping system level in developing designs aimed at unlocking the potential of strip cropping. The positive but variable strip cropping effects observed in the current experimental design and the two alternative configurations suggests prioritizing an overall increased crop diversity over optimizing their spatial arrangement. While we demonstrated increased productivity with strip cropping, further research is needed to expand the database on optimal crop combinations, extending the evaluation beyond yield and revenue performances to facilitate broader adoption of strip cropping in the Netherlands and Western Europe.

Strip‐cropping legacy enhances potato plant defence responses to aphids via soil‐mediated mechanisms

Abstract Intensive agriculture often comes at the expense of soil health. A shift towards practices that foster soil health will support yield and defences against pests and diseases. Growing crops in monoculture is the standard in modern agriculture, though strip‐cropping, in which different crops are planted in strips, is a promising strategy in the transition towards sustainable agriculture. Increasing crop diversity is hypothesized to positively influence arbuscular mycorrhizal fungi (AMF), thereby enhancing soil health, but the mechanisms by which AMF‐plant symbioses contribute to higher yields and reduced pest populations in strip‐cropping systems remain unclear. We used a green‐house experiment with potato plants to explore the soil legacy effects of mono‐cropping versus strip‐cropping systems, AMF inoculation and aphid infestation on AMF root colonization, the induction of plant defences (untargeted LCMS‐based metabolomics), aphid population size and potato yield. We found that potato plants grown in strip‐cropping soil had higher AMF colonization than plants grown in mono‐cropping soil. Potato plants grown in strip‐cropping soil also had higher shoot nitrogen content, increased solamargine levels, and reduced aphid populations. AMF root colonization was only enhanced by the addition of commercial AMF in mono‐cropping soils. Potato plant metabolites were affected by strip‐cropping soil, including jasmonic acid (JA) derivatives. Structural equation models revealed that strip‐cropping soil directly reduced aphid populations and also had a negative direct effect on the JA precursor OPC‐8, and hydroxyJA‐glucosides, indicating complex effects of strip‐cropping soils on JA‐inducible plant defences. Indirect benefits of strip‐cropping soil and AMF inoculation on tuber yield were mediated by their direct positive effects on plant nitrogen content. Our results emphasize the potential of strip‐cropping to enhance AMF root colonization in the field. We show that soil legacy effects of strip‐cropping alter the plant metabolome in ways that suppress of aphid populations. Strip‐cropping legacy effects are the result of crop diversity, crop neighbour and edge effects resulting from crop management practices. While the mechanisms by which soil from strip‐cropping supresses pest populations still need to be identified, our study underscores the potential for strip‐cropping to enhance pest control and yield via soil mediated processes. Read the free Plain Language Summary for this article on the Journal blog.

Reducing herbivory in mixed planting by genomic prediction of neighbor effects in the field

Genetically diverse populations can increase plant resistance to natural enemies. Yet, beneficial genotype pairs remain elusive due to the occurrence of positive or negative effects of mixed planting on plant resistance, respectively called associational resistance or susceptibility. Here, we identify key genotype pairs responsible for associational resistance to herbivory using the genome-wide polymorphism data of the plant species Arabidopsis thaliana. To quantify neighbor interactions among 199 genotypes grown in a randomized block design, we employ a genome-wide association method named “Neighbor GWAS” and genomic prediction inspired by the Ising model of magnetics. These analyses predict that 823 of the 19,701 candidate pairs can reduce herbivory in mixed planting. We planted three pairs with the predicted effects in mixtures and monocultures, and detected 18–30% reductions in herbivore damage in the mixed planting treatment. Our study shows the power of genomic prediction to assemble genotype mixtures with positive biodiversity effects.

Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily.

Due to the homophily assumption in graph convolution networks (GCNs), a common consensus in the graph node classification task is that graph neural networks (GNNs) perform well on homophilic graphs but may fail on heterophilic graphs with many interclass edges. However, the previous interclass edges' perspective and related homo-ratio metrics cannot well explain the GNNs' performance under some heterophilic datasets, which implies that not all the interclass edges are harmful to GNNs. In this work, we propose a new metric based on the von Neumann entropy to reexamine the heterophily problem of GNNs and investigate the feature aggregation of interclass edges from an entire neighbor identifiable perspective. Moreover, we propose a simple yet effective Conv-Agnostic GNN framework (CAGNNs) to enhance the performance of most GNNs on the heterophily datasets by learning the neighbor effect for each node. Specifically, we first decouple the feature of each node into the discriminative feature for downstream tasks and the aggregation feature for graph convolution (GC). Then, we propose a shared mixer module to adaptively evaluate the neighbor effect of each node to incorporate the neighbor information. The proposed framework can be regarded as a plug-in component and is compatible with most GNNs. The experimental results over nine well-known benchmark datasets indicate that our framework can significantly improve performance, especially for the heterophily graphs. The average performance gain is 9.81%, 25.81%, and 20.61% compared with graph isomorphism network (GIN), graph attention network (GAT), and GCN, respectively. Extensive ablation studies and robustness analysis further verify the effectiveness, robustness, and interpretability of our framework. Code is available at https://github.com/JC-202/CAGNN.

Odour information enables patch choice by mammalian herbivores from afar, leading to predictable plant associational effects

Abstract Neighbouring plants can alter the susceptibility of high‐quality focal plants to herbivores by affecting herbivore patch choice. Herbivores can use plant odour to make patch‐scale foraging decisions from afar, but the actual information they rely on within complex plant odours is rarely defined. Revealing the information enabling patch choice by herbivores will provide the mechanistic link underpinning associational effects of plant neighbours arising from these foraging decisions. Here, our first aim was to test whether odour cues alone enable a mammalian herbivore to make patch choice decisions leading to predictable associational effects of neighbours on high‐quality focal plants. Our second aim was then to test whether artificial odour, designed to mimic the informative odour component within the whole odour profile of low‐quality neighbours, is as effective as real plants in influencing patch choice and associational refuge. We tested patch choice by African elephants, Loxodonta africana using a giant Y‐maze and real or artificial plant odours as the only cues for the neighbours of a high‐quality focal plant. We quantified the probability of various odour treatments being chosen in comparison with the odour of a focal plant alone. Compared with focal plants alone, we found that elephants were more likely to choose patches with the focal plant plus high‐quality neighbours of the same or different species, but less likely to choose patches with the focal plant plus low‐quality neighbours. We also demonstrated that an artificial subset of odours, designed to be informative, were as effective as real low‐quality neighbours in influencing patch choice and hence associational refuge to the focal plant. Our results demonstrate a key role of plant odour—and specifically informative components within complex odour profiles—in patch choice decisions by a mammalian herbivore, leading to plant associational effects on high‐quality focal plants. Understanding what olfactory information herbivores use when deciding which patches to visit or avoid, and how it affects focal plant susceptibility is important ecologically. Non‐random patch choice will not only affect individual fitness of herbivores, but also shape plant community dynamics through impacting plant survival and recruitment. Furthermore, artificially re‐creating odour information could offer a new tool to influence herbivore foraging decisions, with implications for wildlife management and conservation, including plant protection. Read the free Plain Language Summary for this article on the Journal blog.

Plant neighbors differentially alter a focal species' biotic interactions through changes to resource allocation.

Plant resource allocation strategies are thought to be largely a consequence of changing abiotic conditions and evolutionary history. However, biotic interactions also influence how a plant allocates resources. As a result, plants mediate indirect interactions between organisms above- and belowground through resource allocation. Neighboring plants can influence plant fitness directly through competition for resources, and indirectly by altering associated community interactions (associational effects), such as pollination, herbivory, and a suite of belowground interactions. Given the importance of community interactions for plant success, and the known ability for plant neighbors to change these interactions, the goal of this "pandemic project" was to understand how heterospecific plant neighbors alter plant resource allocation, whether this occurred through above- or belowground mechanisms, and whether this in turn alters biotic interactions and the relationship between a focal plant and its herbivore and soil community interactions. To do so, we established a common garden experiment, manipulating plant neighbor identity and the extent of interaction among neighbors (aboveground only, vs. above- and belowground interactions, using customized pot types), and measured changes to a focal plant and its biotic interactions over two growing seasons. We found evidence of both neighbor effects and pot type, showing that neighbor interactions affect a focal plant through both above- and belowground processes, and how the focal plant is affected depends on neighbor identity. Though neighbors did not directly alter herbivory or most soil microbial interactions, they did alter the relationship between belowground microbial communities and a plant response trait (specific leaf area). Plant resource allocation responses were reduced with time, showing the importance of extending experiments beyond a single growing season, and are an important consideration when making predictions about plant responses to changing conditions. This study contributes to a growing body of work showing how community contexts affect the above- and belowground interactions of a plant through plant resource allocation strategies.