Biology subjects

Santos, M. J.

Publications and source records attributed to Santos, M. J..

7 recordsLinked to original sources

bioRxiv2026

Assessing the impact of data uncertainty on remote sensing estimation of plant functional diversity

Remote sensing mapping of plant functional diversity (PFD) is increasingly used at the science-policy interface. Yet assessments of uncertainty and quality standards for these products are seldom provided, as the impact of measurement uncertainty on PFD estimates, i.e., the variability across pixels, is still poorly understood. We use trait maps and hyperspectral imagery simulations from the Biodiversity Observing System Simulation Experiment (BOSSE) to assess the impact of different types of uncertainty on the estimation PFD. Results show that uncertainties stemming from random errors affect the estimation of PFD (up to three times) more than those arising from systematic errors, with spectral and spatial error correlation reducing their impact. Standardization computing PFD metrics reduces systematic errors, making in-situ-measured plant traits and remote sensing reflectance factors more robust estimators of PFD than other remote sensing proxies derived from reflectance (e.g., spectral indices or optical traits). The impact of uncertainty propagation from reflectance factors to these often-preferred secondary proxies increases with their complexity. Nonetheless, trait uncertainty can spuriously diminish differences between PFD derived from the ground (plant traits) and satellite imagery, as it can reduce uncertainty-induced or inherent biases between the PFD metrics computed from each trait (plant or spectral). This study provides new understanding of how uncertainty propagates into PFD estimates; this knowledge is relevant for optimizing the selection and defining quality requirements for PFD estimation. It also suggests that random and systematic uncertainties should be quantified separately at the reflectance factor level to guide their use and interpretation in PFD analysis.

ecology↗

bioRxiv2024

Causal discovery in biodiversity-mediated social-ecological systems

Global biodiversity loss and climate change exacerbate feedbacks within social-ecological systems, i.e., between ecosystems, their services and well-being of human societies. Our ability to mediate these feedbacks is hampered by incomplete understanding of the underlying causal links, which could benefit from interdisciplinary approaches to discover theoretical or empirical links from heterogeneous data characteristic of social-ecological studies. We propose a novel framework connecting literature-based causal knowledge with data-driven inference of causality. We test this framework for the highly biodiverse island of Borneo by conducting a systematic literature review of 7473 studies over 170 years, and a causal inference analysis for three conceptual causal diagrams connecting global change, socio-economics, ecosystem services, and biodiversity-ecosystem function using a set of 227 spatially explicit variables. We find that, while natural or social processes have been mostly studied independently, a set of studies already documents causal links across social-ecological domains for processes related to deforestation, food or energy. Causal discovery unveiled consistent negative causal links between global change, social-economic landscape, and biodiversity-ecosystem function, and positive causal links between global change and socio-economics, and these links were robust to indicator selection and addition. We detected few and weak links between social-economic landscape, global change, and ecosystem services. When comparing the data-driven inferred causal links to those documented by the literature, we find that links between biodiversity and ecosystem function with global change, and links between social-economic landscape and ecosystem services were also consistent, and causal analysis uncovered new (potential) causal links not yet described in the literature. Significance StatementAddressing climate change and biodiversity loss in the Anthropocene requires us to recognize that human societies and ecological systems are inherently interconnected in complex adaptive systems. Causal understanding in social-ecological systems enables understanding system dynamics and response to pressures and shocks. While promising, few studies have studied these systems using a combination of big literature which provides the state-of-the-knowledge and big data that provides the underlying information for causal discovery. With this framework, we can specify and rigorously test, causal links in biodiversity-mediated social-ecological processes under global change and examine potential interventions that lead to much needed sustainable outcomes.

ecology↗

bioRxiv2023

Body size-dependent effects on the distribution patterns of phoretic mites of the multi-symbiont Rhynchophorus ferrugineus (Olivier, 1790) host

Phoretic mites have been found attached to different body parts of the red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier, 1790), to disperse. However, the question of how the patterns of attachment sites are formed remains intriguing. Here, we conducted the first study of RPW-associated phoretic mites in Portugal, particularly in the districts of Viana do Castelo, Braga, Porto and Aveiro in Northern Portugal (macrohabitat), and investigated the patterns of mite distribution on six body parts of RPW (microhabitat). At the macrohabitat level, we detected seven phoretic mite taxa actively using the RPW host in each of the four studied districts, all documented for the first time in association with this invasive exotic species in Portugal. However, their relative abundance (species evenness) varied between districts, as did species diversity. All examined weevils carried mites, and the prevalence of the different taxa did not differ between districts or sex of weevils. Measured by mean abundance and degree of aggregation, Centrouropoda sp. proved to be the common dominant taxon, while Acarus sp. And C. rhynchoporus were considered common subordinate taxa and Uroovobella sp., Mesostigmata, N. extremica and Dendrolaelaps sp. sparse taxa. At the microhabitat level, all taxa were present in all body parts of the RPW; the highest abundance was in a region encompassing the inner surface of the elytra and the membranous hind wings (subelytral space). Analysis of niche overlap revealed that the distribution patterns of phoretic mite taxa on the RPW were not randomly structured. In the subelytral space, interspecific coexistence of mites increased as a function of body size difference with the dominant Centrouropoda sp. We conclude that the distribution patterns of RPW-associated phoretic mites show body size-dependent effects that resulted in the dominant taxon displacing similar size taxa and accepting taxa with which it has the greatest size difference as co-habitants.

ecology↗

bioRxiv2021

Towards risk-based surveillance of African Swine Fever in Switzerland

African Swine Fever (ASF) has emerged as a disease of great concern to swine producers and government disease control agencies because of its severe consequences to animal health and the pig industry. Early detection of an ASF introduction is considered essential for reducing the harm caused by the disease. Risk-based surveillance approaches have been used as enhancements to early disease epidemic detection systems in livestock populations. Such approaches may consider the role wildlife plays in hosting and transmitting a disease. In this study, a novel method is presented to estimate and map the risk of introducing ASF into the domestic pig population through wild boar intermediate hosts. It makes use of data about hunted wild boar, rest areas along motorways connecting ASF affected countries to Switzerland, outdoor piggeries, and forest cover. These data were used to compute relative wild boar abundance as well as to estimate the risk of both disease introduction into the wild boar population and disease transmission to domestic pigs. The way relative wild boar abundance was calculated adds to the current state of the art by considering the effect of beech mast on hunting success and the probability of wild boar occurrence when distributing relative abundance values among individual grid cells. The risk of ASF introduction into the domestic pig population by wild boar was highest near the borders of France, Germany, and Italy. On the north side of the Alps, areas of high risk were located on the unshielded side of the main motorway crossing the Central Plateau, which acts as a barrier for wild boar. The results of this study can be used to focus surveillance efforts for early disease detection on high risk areas. The developed method may also inform policies to control other diseases that are transmitted by direct contact from wild boar to domestic pigs.

ecology↗

bioRxiv2021

rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

O_LIEcosystem heterogeneity has been widely recognized as a key ecological feature, influencing several ecological functions, since it is strictly related to several ecological functions like diversity patterns and change, metapopulation dynamics, population connectivity, or gene flow. C_LIO_LIIn this paper, we present a new R package - rasterdiv - to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. C_LIO_LIThe rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open source algorithms. C_LI

ecology↗

bioRxiv2019

Identification of a Novel Retrieval-Dependent Memory Process in the Crab Neohelice granulata

Fully consolidated associative memories may be altered by alternative retrieval dependent memory processes. While a brief exposure to the conditioned stimulus (CS) can trigger reconsolidation of the original memory, a prolonged CS exposure will trigger memory extinction. The conditioned response is maintained after reconsolidation, but is inhibited after extinction, presumably by the formation of a new inhibitory memory trace. In rats and humans, it has been shown that CS exposure of intermediate duration leave the memory in an insensitive or limbo state. Limbo is characterised by the absence of reconsolidation or extinction. Here we investigated the evolutionary conserved nature of limbo using a contextual Pavlovian conditioning (CPC) memory paradigm in the crab Neohelice granulata. In animals with fully consolidated CPC memory, systemic administration of the protein synthesis inhibitor cycloheximide after 1 CS presentation disrupted the memory, presumably by interfering with memory reconsolidation. The same intervention given after 320 CSs prevented CPC memory extinction. Cycloheximide had no behavioural effect when administered after 80 CS presentations, a protocol that failed to extinguish CPC memory. Also, we observed that a stronger CPC memory engaged reconsolidation after 80 CS instead of limbo, indicating that memory strength affects the parametrical conditions to engage either reconsolidation or limbo. Altogether, these results indicate that limbo is an evolutionary conserved memory process segregating reconsolidation from extinction in the number of CSs space. Limbo appears as an intrinsic component of retrieval dependent memory processing, with a key function in the transition from memory maintenance to inhibition. Author statement (CRediT Roles)Santiago A. Merlo: Conceptualization, Data curation, Formal Analysis, Investigation, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. Jimena Santos: Investigation, Writing - review & editing. Maria Eugenia Pedreira: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing. Emiliano Merlo: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing.

neuroscience↗

bioRxiv2019

Testing the ability of species distribution models to infer variable importance

Models of species distributions and niches are frequently used to infer the importance of range- and niche-defining variables. However, the degree to which these models can reliably identify important variables and quantify their influence remains unknown. Here we use a series of simulations to explore how well models can 1) discriminate between variables with different influence and 2) calibrate the magnitude of influence relative to an "omniscient" model. To quantify variable importance, we trained generalized additive models (GAMs), Maxent, and boosted regression trees (BRTs) on simulated data and tested their sensitivity to permutations in each predictor. Importance was inferred by calculating the correlation between permuted and unpermuted predictions, and by comparing predictive accuracy of permuted and unpermuted predictions using AUC and the Continuous Boyce Index. In scenarios with one influential and one uninfluential variable, models were unable to discriminate reliably between variables in conditions that are normally challenging for generating accurate predictions: training occurrences <8-64; prevalence >0.5; small spatial extent; environmental data with coarse resolution when spatial autocorrelation is low; and correlation between environmental variables where |r| >0.7. When two variables influenced the distribution equally, importance was underestimated when species had narrow or intermediate niche breadth. Interactions between variables in how they shaped the niche did not affect inferences about their importance. When variables acted unequally, the effect of the stronger variable was overestimated. GAMs and Maxent discriminated between variables more reliably than BRTs, but no algorithm was consistently well-calibrated vis-a-vis the omniscient model. Algorithm-specific measures of importance like Maxents change-in-gain metric were less robust than the permutation test. Overall, high predictive accuracy did not connote robust inferential capacity. As a result, requirements for reliably measuring variable importance are likely more stringent than for creating models with high predictive accuracy.

ecology↗