Biology subjects

Saavedra, S.

Publications and source records attributed to Saavedra, S..

31 records · Page 2Linked to original sources

bioRxiv2022

Rapid monitoring for ecological persistence

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of ecological communities is largely supported by its structured architecture of species interactions, known as an ecological network. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, we can only monitor small subsets of these networks due to logistical sampling constraints. There is therefore an urgent need to establish links between the small snapshots of data conservationists are able to collect, and the big picture conclusions about ecosystem health demanded by policy makers, scientists and societies. Here we show that the persistence of small subnetworks in isolation -- that is, their persistence when considered separately from the larger network of which they are a part -- is a reliable probabilistic indicator of the persistence of the network as a whole. Our results are general across both antagonistic and mutualistic interaction networks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies. This could significantly improve our ability to monitor progress towards achieving policy targets, such as those enshrined in the UN Convention on Biological Diversity.

ecology↗

bioRxiv2022

Marine protected areas regulate the structure of fish communities threatened by global warming and human impact

The sustainability of marine communities is critical for supporting many biophysical processes that provide ecosystem services that promote human well-being. It is expected that anthropogenic disturbances such as climate change and human activities will tend to create less energetically-efficient ecosystems that support less biomass per unit energy flow. It is debated, however, whether this expected development should translate into bottom-heavy (with small basal species being the most abundant) or top-heavy communities (where more biomass is supported at higher trophic levels with species having larger body sizes). Here, we combine ecological theory and empirical data to demonstrate that full marine protection promotes shifts towards top-heavy energetically-efficient structures in marine communities. First, we use metabolic scaling theory to show that protected communities are expected to display stronger top-heavy structures than disturbed communities. Similarly, we show theoretically that communities with high energy transfer efficiency display stronger top-heavy structures than communities with low transfer efficiency. Next, we use empirical structures observed within fully protected marine areas compared to disturbed areas that vary in stress from thermal events and adjacent human activity. Using a nonparametric causal-inference analysis, we find a strong, positive, causal effect between full marine protection and stronger top-heavy structures. Our work corroborates ecological theory on community development and provides a quantitative framework to study the potential restorative effects of different candidate strategies on protected areas. PO_SCPLOWREPRINTC_SCPLOWThe manuscript [1] is deposited on bioRxiv (https://doi.org/10.1101/2022.06.02.494503).

ecology↗

bioRxiv2021

Feasibility conditions of ecological models: Unfolding links between model parameters

Over more than 100 years, ecological research has been striving to derive internal and external conditions compatible with the coexistence of a given group of interacting species. To address this challenge, numerous studies have focused on developing ecological models and deriving the necessary conditions for species coexistence under equilibrium dynamics, namely feasibility. However, due to mathematical limitations, it has been impossible to derive analytic expressions if the isocline equations have five or more roots, which can be easily reached even in 2-species models. Here, we propose a general formalism to obtain the set of analytical conditions of feasibility for any polynomial population dynamics model of any dimension without the need to solve for the equilibrium locations. We additionally illustrate the application of our methodology by showing how it is possible to derive mathematical relationships between model parameters, while maintaining feasibility in modified Lotka-Volterra models with functional responses and higher-order interactions (model systems with at least five equilibrium points)--a task that is impossible to do with simulations. This work unlocks the opportunity to increase our systematic understanding of species coexistence.

ecology↗

bioRxiv2021

Plant-insect chemical communication in ecological communities: an information theory perspective

Cross-species communication, where signals are sent by one species and perceived by others, is one of the most intriguing types of communication that functionally links different species to form complex ecological networks. Yet, global changes and human activities can affect communication by increasing the fluctuations of species composition and phenology, altering signal profiles and intensity, and introducing noises. So far, most studies on cross-species communication have focused on a few specific species isolated from ecological communities. Scaling up investigations of cross-species communication to the community level is currently hampered by a lack of conceptual and practical methodologies. Here, we propose an interdisciplinary framework based on information theory to investigate mechanisms shaping cross-species communication at the community level. We use plants and insects, the cornerstones of most ecosystems, as a showcase; and focus on chemical communication as the key communication channel. We first introduce some basic concepts of information theory, then we illustrate information patterns in plant-insect chemical communication, followed by a further exploration of how to integrate information theory into ecological and evolutionary processes to form testable mechanistic hypotheses. We conclude by highlighting the importance of community-level information as a vehicle to better understand the maintenance of ecological systems, especially when facing rapid global changes.

ecology↗

bioRxiv2021

Towards a system-level causative knowledge of pollinator communities

Pollination plays a central role both in the maintenance of biodiversity and in crop production. However, habitat loss, pesticides, invasive species, and larger environmental fluctuations are contributing to a dramatic decline of numerous pollinators world-wide. This has increased the need for interventions to protect the composition, functioning, and dynamics of pollinator communities. Yet, how to make these interventions successful at the system level remains extremely challenging due to the complex nature of species interactions and the various unknown or unmeasured confounding ecological factors. Here, we propose that this knowledge can be derived by following a probabilistic causal analysis of pollinator communities. This analysis implies the inference of interventional expectations from the integration of observational and synthetic data. We propose that such synthetic data can be generated using theoretical models that can enable the tractability and scalability of unseen confounding ecological factors affecting the behavior of pollinator communities. We discuss a road map for how this probabilistic causal analysis can be accomplished to increase our system-level causative knowledge of natural communities.

ecology↗

bioRxiv2021

Untangling the complexity of priority effects in multi-species communities

The history of species immigration can dictate how species interact in local communities, thereby causing historical contingency in community assembly. Since immigration history is rarely known, these historical influences, or priority effects, pose a major challenge in predicting community assembly. Here, we provide a graph-based, non-parametric, theoretical framework for understanding the predictability of community assembly as affected by priority effects. To develop this frame-work, we first show that the diversity of possible priority effects increases super-exponentially with the number of species. We then point out that, despite this diversity, the consequences of priority effects for multispecies communities can be classified into four basic types, each of which reduces community predictability: alternative stable states, alternative transient paths, compositional cycles, and the lack of escapes from compositional cycles to stable states. Using a neural network, we show that this classification of priority effects enables accurate explanation of community predictability, particularly when each species immigrates repeatedly. We also demonstrate the empirical utility of our theoretical framework by applying it to two experimentally derived assembly graphs of algal and ciliate communities. Based on these analyses, we discuss how the framework proposed here can help guide experimental investigation of the predictability of history-dependent community assembly.

ecology↗

bioRxiv2020

Coexistence holes characterize the assembly and disassembly of multispecies systems

A central goal of life science has been to understand the limits of species coexistence. However, we know surprisingly little about the structure of species coexistence below such limits, and how it affects the assembly and disassembly of ecological systems. Here we introduce a novel hypergraph-based formalism that fully captures the structure of coexistence in multispecies systems. Our formalism uncovers that, below its limits, coexistence in ecological systems has ubiquitous discontinuities that we call "coexistence holes." These coexistence holes do not occur arbitrarily but tend to obey patterns that make them predictable. We provide direct evidence showing that the biotic and abiotic constraints of empirical systems produce an over-representation of coexistence holes. By highlighting discontinuities in the form of coexistence holes, our work provides a new platform to uncover the order and structure of the assembly and disassembly of ecological systems.

ecology↗

bioRxiv2020

Understanding the emergence of contingent and deterministic exclusion in multispecies communities

Competitive exclusion can be classified as deterministic or as historically contingent. While competitive exclusion is common in nature, it has remained unclear when multispecies communities should be dominated by deterministic or contingent exclusion. Here, we provide a general theoretical approach to explain both the emergence and sources of competitive exclusion in multispecies communities. We illustrate our approach on an empirical competition system between annual and perennial plant species. First, we find that the life-history of perennial species increases the probability of observing contingent exclusion by increasing their effective intrinsic growth rates. Second, we find that the probability of observing contingent exclusion increases with weaker intraspecific competition, and not with the level of hierarchical competition. Third, we find a shift from contingent exclusion to dominance with increasing numbers of competing species. Our work provides a heuristic framework to increase our understanding about the predictability of species persistence within multispecies communities.

ecology↗

bioRxiv2020

Bridging parametric and nonparametric measures of species interactions

A central theme in ecological research is to understand how species interactions contribute to community dynamics. Species interactions are the basis of parametric (model-driven) and nonpara-metric (model-free) approaches in theoretical and empirical work. However, despite their different interpretations across these approaches, these measures have occasionally been used interchangeably, limiting our opportunity to use their differences to gain new insights about ecological systems. Here, we revisit two of the most used measures across these approaches: species interactions measured as constant direct effects (typically used in parametric approaches) and local aggregated effects (typically used in nonparametric approaches). We show two fundamental properties of species interactions that cannot be revealed without bridging these definitions. First, we show that the local aggregated intraspecific effect summarizes all potential pathways through which one species impacts itself, which are likely to be negative even without any constant direct self-regulation mechanism. This property has implications for the long-held debate on how communities can be stabilized when little evidence of self-regulation has been found among higher-trophic species. Second, we show that a local aggregated interspecific effect between two species is correlated with the constant direct interspecific effect if and only if the population dynamics do not have any higher-order direct effects. This other property provides a rigorous methodology to detect direct higher-order effects in the field and experimental data. Overall, our findings illustrate a practical route to gain further insights about non-equilibrium ecological dynamics and species interactions.

ecology↗

bioRxiv2020

The impact of colonization history on the composition of ecological systems

Observational studies of ecological systems have shown that different species compositions can arise from distinct species arrival orders during community assembly--also known as colonization history. However, it is still unclear under which conditions colonization history will dominate community composition. Yet, this is important in order to understand and anticipate the impact of species arrivals on the biodiversity that we observe in both nature and experiments. To address this fundamental question, here we develop a testable theory linking colonization history and community composition. First, we prove two general theorems to determine whether the composition of a community will depend on its colonization history. For communities governed by Lotka-Volterra dynamics, we further simplify the two theorems into a corollary that is easy for numerical test. Second, we show, via extensive numerical simulations, that the probability that community composition is dominated by colonization history increases monotonically with community size and species connectivity. Third, we show that this probability significantly increases with the variation of intrinsic growth rates across species. These results reveal that community composition is a probabilistic process mediated by ecological dynamics via the interspecific variation and the size of regional pools.

ecology↗

bioRxiv2019

Truncated WT1 protein isoform expression is increased in MCF-7 cells in a long-term estrogen depletion.

BackgroundThe WT1 gene codes for a transcription factor that presents several protein isoforms with diverse biological properties, capable of positively and negatively regulating genes involved in proliferation, differentiation, and apoptosis. WT1 protein is overexpressed in more than 90% of breast cancer, however, its role during tumor progression is still unknown.\n\nMethodologyIn this work were analyzed the expression of WT1 isoforms (36-38 kDa and 52-54 kDa, and 17 AA (+/-) and KTS (+/-)) in breast cancer cells. On the other hand, with the purpose of mimicking the process of switch from a hormone-dependent to a hormone-independent neoplasm, an assay was performed using the MCF-7 cells cultured in long-term estrogen depletion (MCF-7 LTED cells) to determine the WT1 protein isoforms expression by western blot and RT-PCR, and Her2/neu and Estrogen receptor (ER) expression by quantitative RT-PCR assay. Growth kinetics and sensitivity to tamoxifen were performed in the MCF-7 LTED cells by trypan blue exclusion.\n\nResultsThe western blot shows the presence of the 52-54 kDa WT1 isoform in the ER (+) breast cancer cells, but not in the ER (-) cells. The 36-38 kDa WT1 isoform was detected in all the breast cancer cell lines analyzed. Using specific primers was found that 17 AA (+) / KTS (-) WT1 isoform was the most frequent in four breast cancer cell lines. During the sampling of the MCF-7 cells in estrogen depletion, an increase in the short-term of 52-54 kDa WT1 isoform was observed and this was kept until week 13, thereafter, its expression was absent; alternately, the 36-38 kDa WT1 isoform was observed from week 1 and it remained constant until week 27. MCF-7 LTED cells growth kinetic decreased 1.4 folds and were not sensitive to tamoxifen antiproliferative effect (p [≤] 0.05). Finally, were observed an increase of expression of ER and Her2/neu in the MCF-7 LTED cells.\n\nConclusionsThe 36-38 kDa WT1 isoform expression occurs during the modifications of the hormonal environment, suggesting that it may be playing an important role in its adaptation and tumor progression.

cell biology↗

bioRxiv2019

Is the addition of higher-order interactions in ecological models increasing the understanding of ecological dynamics?

Recent work has shown that higher-order interactions can increase the stability, promote the diversity, and better explain the dynamics of ecological communities. Yet, it remains unclear whether the perceived benefits of adding higher-order terms into population dynamics models come from fundamental principles or a simple mathematical advantage given by the nature of multivariate polynomials. Here, we develop a general method to quantify the mathematical advantage of adding higher-order interactions in ecological models based on the number of free-equilibrium points that can be engineered in a system (i.e., equilibria that can be feasible or unfeasible by tunning model parameters). We apply this method to calculate the number of free-equilibrium points in Lotka-Volterra dynamics. While it is known that Lotka-Volterra models without higher-order interactions only have one free-equilibrium point regardless of the number of parameters, we find that by adding higher-order terms this number increases exponentially with the dimension of the system. Our results suggest that while adding higher-order interactions in ecological models may be good for prediction purposes, they cannot provide additional explanatory power of ecological dynamics if model parameters are not ecologically restricted.

ecology↗

bioRxiv2017

Rethinking the importance of ecological networks through the glass of environmental variations

A major quest in network and community ecology has been centered on understanding the importance of structural patterns in species interaction networks--the synthesis of who interacts with whom in a given location and time. In the past decades, much effort has been devoted to infer the importance of a particular structure by its capacity to tolerate an external perturbation on its structure or dynamics. Here we demonstrate that such a perspective leads to inconsistent conclusions. That is, the importance of a network structure changes as a function of the external perturbations acting on a community at any given point in time. Thus, we discuss a research agenda to investigate the relative importance of the structure of ecological networks under an environment-dependent framework. We hypothesize that only by studying systematically the link between network structure and community dynamics under an environment-dependent framework, we can uncover the limits at which communities can tolerate environmental changes.\n\n\"Variation stands out as the only meaningful reality\"\n\nStephen J. Gould.

ecology↗