Biology subjects

Mello, M. A. R.

Publications and source records attributed to Mello, M. A. R..

7 recordsLinked to original sources

bioRxiv2026

From concentration to export: resource contrasts and bee traits shape pollinator spillover to crops

Floral plantings can either concentrate bees or export them to adjacent crops, yet the ecological conditions influencing these outcomes remain unclear. Here, we develop a mathematical model as proof of concept for our previous integrative hypothesis: concentrator and exporter outcomes can arise as alternative, context-dependent outcomes of the same underlying resource-selection process. Using bees as a model and focusing specifically on spillover from floral plantings to crops, we identified resource-specific thresholds separating concentration- and export-favoring conditions. Our model translates differences in relative patch attractiveness into context-dependent concentration and export outcomes and generates resource-specific, testable predictions about the conditions favoring pollinator movement into crops. In our simulations, the concentrator-exporter transition occurred at a lower flowering-intensity contrast than at pollen or nectar contrasts, which suggests that flowering intensity may provide an initial cue for bee movement, whereas nectar and pollen rewards refine or sustain bee responses once crops are perceived as attractive. Spillover thresholds differed among resource contrasts, whereas response steepness varied across bee-trait and community scenarios. Under the model's trait-sensitivity formulation, predicted spillover probability responded more strongly to flowering contrast for specialists than for generalists; colony size amplified this response, whereas bee richness dampened it. Together, these patterns show how flowering and resource contrasts interact with bee traits and community context to shape predicted spillover. Our results confirm that the concentrator and exporter hypotheses can be understood as context-dependent outcomes of the same ecological process rather than as mutually exclusive alternatives. Experimental tests of the predicted thresholds conducted in the field could reveal when and where floral plantings are most likely to promote bee spillover to crops, potentially supporting crop pollination.

ecology↗

bioRxiv2025

An ecological synthesis about the effects of floral plantings on crop pollination by bees

One of the UNs 17 Sustainable Development Goals is a world free from hunger, with sustainable food production and resilient agricultural practices (SDG 2). However, as we approach the 2030 deadline, global food security, a multidimensional challenge, remains unsolved. With a growing human population, food demand will likely increase, leading to more intensive agricultural practices that put bees and their pollination services at risk. Conserving bees is, thus, crucial to ensuring our food security. A promising solution is cultivating floral plantings alongside crops, which can enhance ecosystem services such as pollination. However, floral plantings may also compete with crops for bees. To optimize their benefits, we need to understand when floral plantings facilitate bee spillover to crops, supporting both bee conservation and agricultural productivity. To address this, we synthesized existing knowledge using a research weaving approach, which combines bibliometric and systematic mapping. Our synthesis suggests that the effects of floral plantings result from a complex interplay of factors, including crop type, bee species, floral planting composition, and environmental conditions. To clarify this interplay, we propose an integrative hypothesis to guide future studies. Finally, our results highlight the need for stronger collaboration among researchers to better understand the role of floral plantings in ecological intensification.

ecology↗

bioRxiv2025

Connections in the Dark: Social-Ecological Networks as a Promising Tool for Bat Conservation and One Health

Bats provide vital ecosystem services, including pest suppression and crop pollination. However, the increasing proximity of bats and humans is a growing conservation and public health concern with negative consequences for both sides. Mitigating these consequences requires integrative approaches like network science and the emerging field of social-ecological networks (SENs), which offer powerful tools to map and analyse complex social and ecological dynamics. Here, we synthesize how network approaches have been applied to bat research and conservation. Specifically, we: (i) assess the use of both ecological and social network analyses to study bats; (ii) identify network tools well-suited for SEN-based bat research; (iii) present a case study illustrating how SEN applications in bat research can inform conservation and One Health efforts; and, lastly, (iv) discuss key challenges and opportunities in using SENs to investigate the human-bat interface. Our review unveils a rise in network-based bat research from 2006 to 2020, followed by a post-pandemic decline. Nevertheless, across the 127 studies mapped by our review, only one applied an SEN lens. Finally, we suggest how applying some underexplored SEN tools to bat research could lead to novel perspectives, aiming to promote integrated strategies for the coexistence of bats and humans.

ecology↗

bioRxiv2021

A novel perspective on the meaning of nestedness with conceptual and methodological solutions

O_LINestedness is a common pattern in metacommunities and interaction networks, whose causes are still subject to investigation. Nestedness inference is challenging because, beyond calculating an index, we need to compare observed and expected values using null models. There are many different null models and the choice between them strongly affects test outcomes. Furthermore, there is no theoretical basis to guide this choice. C_LIO_LIHere, we propose a different look at the meaning of nestedness that improves our understanding of its causes and directly links null models to hypotheses. The nestedness of a matrix is the combination of marginal sum inequality and high overlap. The higher the overlap, the more predictable the cell values by marginal sums. Therefore, the only way a process can increase nestedness is by promoting marginal sum inequalities, without concomitantly introducing preferences. We propose a combination of null models to test for different topological hypotheses. In these null models, interactions are randomized following a probability matrix. The probability matrix of the equiprobable model excludes marginal sum inequalities and consequently all nestedness-generating mechanisms, providing a distribution of expected values for nestedness significance tests. The probability matrix of the proportional model, by conserving marginal sums and maximizing overlap, conserves nestedness-generating mechanisms and excludes nestedness-disrupting mechanisms, thereby yielding the expected nestedness values for fully nested matrices. C_LIO_LIWe advance a new protocol to test for nestedness in binary and weighted matrices, in which those two null models represent different topological hypotheses. Our protocol helps to tell apart cases in which nestedness is different from expected by chance and cases in which nestedness represents the best topological archetype. We also evaluate the efficiency of applying this protocol using some common nestedness indices. Analyses based on weighted data proved to be highly efficient and informative, while binary analyses induced severe distortions. Finally, we empirically illustrate our approach using a plant-pollinator network. C_LIO_LIThrough a shift of perspective, our approach reconciliates contradictions in null model analysis and provides a guideline for nestedness interpretation. C_LI

ecology↗

bioRxiv2018

Insights on the assembly rules of a continent-wide multilayer network

Introductory paragraphHow are ecological systems assembled? Here, we aim to contribute to answering this question by harnessing the framework of a novel integrative hypothesis. We shed light on the assembly rules of a multilayer network formed by frugivory and nectarivory interactions between bats and plants in the Neotropics. Our results suggest that, at a large scale, phylogenetic trade-offs separate species into different layers and modules. At an intermediate scale, the modules are also shaped by geographic trade-offs. And at a small scale, the network shifts to a nested structure within its modules, probably as a consequence of resource breadth processes. Finally, once the topology of the network is shaped, morphological traits related to consuming fruits or nectar determine which species are central or peripheral. Our results help understand how different processes contribute to the assemblage of ecological systems at different scales, resulting in a compound topology.

ecology↗

bioRxiv2018

A new model explaining the origin of different topologies in interaction networks

The architecture of interaction networks has been extensively studied in the past decades, and different topologies have been observed in natural systems. Despite several phenomenological explanations proposed, we still understand little of the mechanisms that generate those topologies. Here we present a mechanistic model based on the integrative hypothesis of specialization, which aims at explaining the emergence of topology and specialization in consumer-resource networks. By following three first-principles and adjusting five parameters, our model was able to generate synthetic weighted networks that show the main patterns of topology and specialization observed in nature. Our results prove that topology emergence is possible without network-level selection. In our simulations, the intensity of trade-offs in the performance of each consumer species on different resource species is the main factor driving network topology. We predict that interaction networks with low species diversity and low dissimilarity between resources should have a nested topology, although more diverse networks with large dissimilarity should have a compound topology. Additionally, our results highlight scale as a key factor. Our model generates predictions consistent with ecological and evolutionary theories and real-world observations. Therefore, it supports the IHS as a useful conceptual framework to study the architecture of interaction networks.

ecology↗

bioRxiv2017

The compound topology of a continent-wide host-parasite network explained by an integrative hypothesis of specialization.

Is there a prevalent pattern among interaction networks: nestedness or modularity? Must consumers always trade-off generalism for average performance in resource exploitation? These two questions have been addressed in various systems, with contradictory results. A recent integrative hypothesis combines both questions within a common theoretical framework, proposing that ecological specialization is structured by different prevailing processes in smaller and larger network units. This should produce both a compound interaction network, formed by internally nested modules, and a scale-dependence on the relationship between consumer performance and generalism. Here, we confirm both predictions in a large dataset on host-parasite interactions. We show that modules indeed constrain nestedness at the whole network level, and that the relationship between parasite generalism and performance on their hosts changed from negative at large to positive at small scales. Our results shed light on both debates, and provide some clues to their integration and solution.

ecology↗