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Coffee farms receive ecosystem services that rely on pollinators and pest predators. Landscape-scale processes regulate the flow of these biodiversity-based services. Consequently, the coffee farms' surrounding landscape impacts coffee production. This paper investigates how landscape structure can influence coffee production at different scales. We also evaluated the predictive utility of landscape metrics in a spatial (farm level) and aspatial approach (municipality level). We tested the effect of landscape structure on coffee production for 25 farms and 30 municipalities in southern Brazil. We used seven landscape metrics at landscape and class levels to measure the effect of landscape structure. At the farm level, we calculated metrics in five buffers from 1 to 5 km from the farm centroid to measure their scale of effect. We conducted a model selection using the generalized linear model (GLM) with a Gamma error distribution and inverse link function to evaluate the impact of landscape metrics on coffee production in both spatial and aspatial approaches. The landscape intensity index had a negative effect on coffee production (AICc = 375.59, p < 0.001). The native forest patch density (AICc = 390.14, p = 0.011) and landscape diversity (AICc = 391.18, p = 0.023) had a positive effect on production. All significant factors had effects at the farm level in the 2 km buffer but no effects at the municipality level. Our findings suggest that the landscape composition in the immediate surroundings of coffee farms helps predict production in a spatially explicit approach. However, these metrics cannot detect the impact of the landscape when analyzed in an aspatial approach. These findings highlight the importance of the landscape spatial structure, mainly the natural one, in the stability of coffee production. This study enhanced the knowledge of coffee production dependence on landscape-level processes. This advance can help to improve the sustainability of land use and better planning of agriculture, ensuring food and economic safety. Furthermore, our framework provides a method that can be useful to scrutinize any cropping system with census data that is either spatialized or not., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Niche partitioning is an important mechanism that allows species to coexist. Within mutualistic interaction networks, diel niche partitioning, i.e., partitioning of resources throughout the day, has been neglected. We explored diel niche partitioning of a plant-hummingbird network in the Brazilian Atlantic forest for nine months. To evaluate diel patterns of hummingbird visits and nectar production, we used time-lapse cameras on focal flowers and repeated nectar volume and concentration measures, respectively. Additionally, we measured flower abundance around focal flowers and flower morphological traits. We did not observe diel partitioning for either hummingbirds or plants. Instead, hummingbirds appeared to specialize in different plant species, consistent with trophic niche partitioning, potentially resulting from competition. In contrast, plant species that co-flowered and shared hummingbird visits produced nectar during similar times, consistent with facilitation. Our focus on the fine-scale temporal pattern revealed that plants and hummingbirds appear to have different strategies for promoting co-existence., (© 2023. The Author(s).)

Background: Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing., Results: Here we present a vocabulary of terms and a data model for sharing plant-pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant-pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant-pollinator interactions., Conclusions: The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant-pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant-pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms., (© The Author(s) 2022. Published by Oxford University Press GigaScience.)

Crop pollination is one of Nature's Contributions to People (NCP) that reconciles biodiversity conservation and agricultural production. NCP benefits vary across space, including among distinct political-administrative levels within nations. Moreover, initiatives to restore ecosystems may enhance NCP provision, such as crop pollination delivered by native pollinators. We mapped crop pollination demand (PD), diversity of pollinator-dependent crops, and vegetation deficit (VD) (vis-a-vis Brazilian legal requirements) across all 5570 municipalities in Brazil. Pollinator-dependent crops represented ∼55% of the annual monetary value of agricultural production and ∼15% of the annual crop production. Municipalities with greater crop PD (i.e., higher degree of pollinator dependence of crop production) also had greater VD, associated with large properties and monocultures. In contrast, municipalities with a greater diversity of pollinator-dependent crops and predominantly small properties presented a smaller VD. Our results support that ecological restoration prompted by legal requirements offers great potential to promote crop productivity in larger properties. Moreover, conservation of vegetation remnants could support food security in small properties. We provided the first steps to identify spatial patterns linking biodiversity conservation and pollination service. Using Brazilian legal requirements as an example, we show that land-use management policies may be successfully used to ensure agricultural sustainability and crop production.

When describing plant-animal interaction networks, sampling can be performed using plant- or animal-centred approaches. Despite known effects of sampling on network structure, how samplings affect the estimates of interaction β-diversity across networks is still unresolved. We investigated how the sampling method affects the assessment of β-diversity of interactions, turnover and rewiring. We contrasted plant- and animal-centred sampling methods applied to pollination networks across habitats in a heterogeneous tropical landscape, the Pantanal Wetlands. We also asked whether plant traits influence the difference in interaction specialization according to sampling. Plant-centred networks resulted in higher β-diversity of interactions in space than animal-centred networks. Turnover explained most of the β-diversity in both methods, but rewiring was proportionately more important when using the animal-centred method. While the plant-centred method indicated lower network modularity and specialization, floral traits modulated the effects of the sampling method on species-level network metrics. Combining animal- and plant-centred approaches returned intermediate values for β-diversity of interactions and network metrics. Distinct methods may also be better suited for answering questions at different scales. Our results point out that the method choice, or combination of methods, should always reflect the appropriate scale of the factors determining the interactions being investigated., (© 2021 The Authors New Phytologist © 2021 New Phytologist Foundation.)

Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap and species abundances. How these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographical scale. For 24 quantitative networks sampled throughout the Americas, we found that the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low-temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.