Citizen science has been particularly effective in gathering reliable, timely, large-scale data on the presence and distributions of animal species, including mosquito vectors of human and zoonotic pathogens. This involves the participation of citizen scientists in research projects, with success strongly dependent on the capacity to disseminate project information and engage citizen scientists to contribute their time. Mosquito Alert is a citizen science that aids in the system surveillances of vector mosquitoes. It involves citizen scientists providing expert-validated photos of targeted mosquitoes, along with records of bites and breeding sites. Since 2020 the system has been disseminated throughout Europe. This article uses models to analyze the effect of promotion activities carried out by the Mosquito Alert ITALIA team from October 2020 to December 2022 on the number of citizen scientists recruited and engaged in the project, and their performance in mosquito identification. Results show a high level of citizen scientist recruitment (N > 18.000; 37 % of overall European participants). This was achieved mostly through articles generated by ad hoc press releases detailing the app's goals and functioning. Press releases were more effective when carried out at the beginning and end of the mosquito season and when mosquito's public health significance was emphasized. Despite the high number of records received (N > 20.000), only 30 % of registered participants sent records, and the probability of a participant sending a record dropped off quickly over time after first registering. Among participants who contributed, ∼50 % sent 1 record, ∼30 % ≥3 and 4 % >10 records. Participants showed good capacity to identify mosquitoes and improve identification skills with app usage. The results will be valuable for anyone interested in evaluating citizen science, as participation and engagement are seldom quantitatively assessed. Our results are also useful for designing dissemination and education strategies in citizen science projects associated with arthropod vector monitoring.

We investigate the dependence on the search space dimension of statistical properties of random searches with Lévy α-stable and power-law distributions of step lengths. We find that the probabilities to return to the last target found (P_{0}) and to encounter faraway targets (P_{L}), as well as the associated Shannon entropy S, behave as a function of α quite differently in one (1D) and two (2D) dimensions, a somewhat surprising result not reported until now. While in 1D one always has P_{0}≥P_{L}, an interesting crossover takes place in 2D that separates the search regimes with P_{0}>P_{L} for higher α and P_{0}<P_{L} for lower α, depending on the initial distance to the last target found. We also obtain in 2D a maximum in the entropy S for α∈(0,2], not observed in 1D apart from the trivial α→0 ballistic limit. Improving the understanding of the role of dimensionality in random searches is relevant in diverse contexts, as in the problem of encounter rates in biology and ecology.

The Lévy flight foraging hypothesis states that organisms must have evolved adaptations to exploit Lévy walk search strategies. Indeed, it is widely accepted that inverse square Lévy walks optimize the search efficiency in foraging with unrestricted revisits (also known as nondestructive foraging). However, a mathematically rigorous demonstration of this for dimensions D≥2 is still lacking. Here we study the very closely related problem of a Lévy walker inside annuli or spherical shells with absorbing boundaries. In the limit that corresponds to the foraging with unrestricted revisits, we show that inverse square Lévy walks optimize the search. This constitutes the strongest formal result to date supporting the optimality of inverse square Lévy walks search strategies.

Information on the relevant global scales of the search space, even if partial, should conceivably enhance the performance of random searches. Here we show numerically and analytically that the paradigmatic uninformed optimal Lévy searches can be outperformed by informed multiple-scale random searches in one (1D) and two (2D) dimensions, even when the knowledge about the relevant landscape scales is incomplete. We show in the low-density nondestructive regime that the optimal efficiency of biexponential searches that incorporate all key scales of the 1D landscape of size L decays asymptotically as η_{opt}∼1/sqrt[L], overcoming the result η_{opt}∼1/(sqrt[L]lnL) of optimal Lévy searches. We further characterize the level of limited information the searcher can have on these scales. We obtain the phase diagram of bi- and triexponential searches in 1D and 2D. Remarkably, even for a certain degree of lack of information, partially informed searches can still outperform optimal Lévy searches. We discuss our results in connection with the foraging problem.

It is widely accepted that inverse square Lévy walks are optimal search strategies because they maximize the encounter rate with sparse, randomly distributed, replenishable targets when the search restarts in the vicinity of the previously visited target, which becomes revisitable again with high probability, i.e., non-destructive foraging [Nature 401, 911 (1999)]. The precise conditions for the validity of this Lévy flight foraging hypothesis (LFH) have been widely described in the literature [Phys. Life Rev. 14, 94 (2015)]. Nevertheless, three objecting claims to the LFH have been raised recently for d ≥ 2: (i) the capture rate η has linear dependence on the target density ρ for all values of the Lévy index α; (ii) "the gain η_max/η achieved by varying α is bounded even in the limit ρ→ 0" so that "tuning α can only yield a marginal gain"; (iii) depending on the values of the radius of detection a, the restarting distance l_c and the scale parameter s, the optimum is realized for a range of α [Phys. Rev. Lett. 124, 080601 (2020)]. Here we answer each of these three criticisms in detail and show that claims (i)-(iii) do not actually invalidate the LFH. Our results and analyses restore the original result of the LFH for non-destructive foraging.

Movement is fundamental to the animal ecology, determining how, when, and where an individual interacts with the environment. The animal dynamics is usually inferred from trajectory data described as a combination of moves and turns, which are generally influenced by the vast range of complex stochastic stimuli received by the individual as it moves. Here we consider a statistical physics approach to study the probability distribution of animal move lengths based on stochastic differential Langevin equations and the superstatistics formalism. We address the stochastic influence on the move lengths as a Wiener process. Two main cases are considered: one in which the statistical properties of the noise do not change along the animal’s path and another with heterogeneous noise statistics. The latter is treated in a compounding statistics framework and may be related to heterogeneous landscapes. We study Langevin dynamics processes with different types of nonlinearity in the deterministic component of movement and both linear and nonlinear multiplicative stochastic processes. The move length distributions derived here comprise the possibility of movement multiscales, diffusive and superdiffusive (Lévy-like) dynamics, and include most of the distributions currently considered in the literature of animal movement, as well as some new proposals.

Dispersal is a main determining factor of population structure and variation. In the marine habitat, well-connected populations with large numbers of reproducing individuals are common but even so population structure can exist on a small-scale. Variation in dispersal between populations or over time is often associated to both environmental and genetic variation. Nonetheless, detecting structure and dispersal variation on a fine-scale within marine populations still remains a challenge. Here we propose and use a novel approach of combining a clustering model, early-life history trait information from fish otoliths, spatial coordinates and genetic markers to detect very fine-scale dispersal patterns. We collected 1573 individuals (946 adults and 627 juveniles) of the black-faced blenny across a small-scale (2km) coastline as well as at a larger-scale area (<50kms). A total of 178 single nucleotide polymorphism markers were used to evaluate relatedness patterns within this well-connected population. Local retention and/or dispersal varied across the 2km coastline with higher frequency of SHORT-range disperser adults; representing local recruitment; towards the southwest of the area. An inverse pattern was found for juveniles, showing an increase of SHORT-range dispersers towards the northeast. This reveals a complex but not full genetic mixing and suggests oceanic/coastal circulation as the main driver of this fine-scale chaotic genetic patchiness within this otherwise homogeneous population. When focusing on the patterns within one recruitment season, we found large differences in temperatures (from approx. 17oC to 25oC) as well as pelagic larval duration (PLD) for juveniles from the beginning of the season and the end of the season. We were able to detect fine-scale differences in HIGH-range juvenile dispersers, representing distant migrants, depending on whether they were born at the beginning of the season, hence, with a longer PLD, or at the end of the reproductive season. The ability to detect such fine-scale dispersal patchiness will aid in our understanding of the underlying mechanisms of population structuring and chaotic patchiness in a wide range of species even with high potential dispersal abilities.

Dispersal is one of the main determining factors of population structure. In the marine habitat, well-connected populations with large numbers of reproducing individuals are common but even so population structure can exist on a small-scale. Variation in dispersal patterns between populations or over time is often associated to geographic distance or changing oceanographic barriers. Consequently, detecting structure and variation in dispersal on a fine-scale within marine populations still remains a challenge. Here we propose and use a novel approach of combining a clustering model, early-life history trait information from fish otoliths, spatial coordinates and genetic markers to detect very fine-scale dispersal patterns. We collected 1573 individuals (946 adults and 627 juveniles) of the black-faced blenny across a small-scale (2 km) coastline as well as at a larger-scale area (<50 kms). A total of 178 single nucleotide polymorphism markers were used to evaluate relatedness patterns within this well-connected population. In our clustering models we categorized SHORT-range dispersers to be potential local recruits based on their high relatedness within and low relatedness towards other spatial clusters. Local retention and/or dispersal of this potential local recruitment varied across the 2 km coastline with higher frequency of SHORT-range dispersers towards the southwest of the area for adults. An inverse pattern was found for juveniles, showing an increase of SHORT-range dispersers towards the northeast. As we rule out selective movement and mortality from one year to the next, this pattern reveals a complex but not full genetic mixing, and variability in coastal circulation is most likely the main driver of this fine-scale chaotic genetic patchiness within this otherwise homogeneous population. When focusing on the patterns within one recruitment season, we found large differences in temperatures (from approx. 17 °C to 25 °C) as well as pelagic larval duration (PLD) for juveniles from the beginning of the season and the end of the season. We were able to detect fine-scale differences in LONG-range juvenile dispersers, representing distant migrants, depending on whether they were born at the beginning of the season with a longer PLD, or at the end of the reproductive season. The ability to detect such fine-scale dispersal patchiness will aid in our understanding of the underlying mechanisms of population structuring and chaotic patchiness in a wide range of species even with high potential dispersal abilities.

An important problem in the study of anomalous diffusion and transport concerns the proper analysis of trajectory data. The analysis and inference of Lévy walk patterns from empirical or simulated trajectories of particles in two and three-dimensional spaces (2D and 3D) is much more difficult than in 1D because path curvature is nonexistent in 1D but quite common in higher dimensions. Recently, a new method for detecting Lévy walks, which considers 1D projections of 2D or 3D trajectory data, has been proposed by Humphries et al. The key new idea is to exploit the fact that the 1D projection of a high-dimensional Lévy walk is itself a Lévy walk. Here, we ask whether or not this projection method is powerful enough to cleanly distinguish 2D Lévy walk with added curvature from a simple Markovian correlated random walk. We study the especially challenging case in which both 2D walks have exactly identical probability density functions (pdf) of step sizes as well as of turning angles between successive steps. Our approach extends the original projection method by introducing a rescaling of the projected data. Upon projection and coarse-graining, the renormalized pdf for the travel distances between successive turnings is seen to possess a fat tail when there is an underlying Lévy process. We exploit this effect to infer a Lévy walk process in the original high-dimensional curved trajectory. In contrast, no fat tail appears when a (Markovian) correlated random walk is analyzed in this way. We show that this procedure works extremely well in clearly identifying a Lévy walk even when there is noise from curvature. The present protocol may be useful in realistic contexts involving ongoing debates on the presence (or not) of Lévy walks related to animal movement on land (2D) and in air and oceans (3D).

Theoretical and empirical investigations of search strategies typically have failed to distinguish the distinct roles played by density versus patchiness of resources. It is well known that motility and diffusivity of organisms often increase in environments with low density of resources, but thus far there has been little progress in understanding the specific role of landscape heterogeneity and disorder on random, non-oriented motility. Here we address the general question of how the landscape heterogeneity affects the efficiency of encounter interactions under global constant density of scarce resources. We unveil the key mechanism coupling the landscape structure with optimal search diffusivity. In particular, our main result leads to an empirically testable prediction: enhanced diffusivity (including superdiffusive searches), with shift in the diffusion exponent, favors the success of target encounters in heterogeneous landscapes.

INTRODUCTION. Esthesioneuroblastoma (ENB) is a very uncommon malignant tumor with a neuroectodermal origin that usually involves the anterior cranial fossa and nasal cavity. OBJECTIVES. To review our experience in the management of ENB and assess the validity of the histopathological diagnosis, modality of treatment and prognostic factors of the disease comparing our findings with the literature. METHODS. A retrospective study of 11 cases with the diagnosis of esthesioneuroblastoma treated in our hospital between 2000 and 2008. Statistical analysis was performed in search for prognostic factors. The bibliography about ENB published between 1990 and 2009 was reviewed RESULTS. There were 3 women and 8 men, with a mean age of 42 years old (range 20-71y). Their symptoms upon admission were nasal obstruction (81%), epistaxis (27%), visual loss (18%), headache and others. According to the Kadish Stage, 2 were stage B and 9 were stage C. Dulguerov and Calcaterra Classification was also used: 2 were T2, 3 were T3 and 6 were T4. The hystopathological result according to the Hyams classification was: 2 cases in stage I, 4 in stage II, 3 in stage III and 2 in stage IV. The two cases classified in stage IV changed the diagnosis to undifferenciate tumor in the second biopsy. A subcranial approach was performed in 8 cases combined with endonasal endoscopy to confirm the total removal, followed by radiotherapy in all and chemotherapy in one case, resulting on 62% (5 patients) being alive without disease, 12,5% (1 p) alive with disease, and 25% (2 p) dead of disease. Another patient was operated by a single endonasal endoscopic approach and a subtotal removal was achieved. This patient is alive without disease. The other 2 patients were treated by biopsy plus radiotherapy and chemotherapy, because they were considered unresectable, and one of them is alive with disease and the other one is dead of disease. Radiotherapy was performed in all cases and chemotherapy in 5 cases. The hystopathological grading system of Hyams was considered statistically significant as a prognostic factor of disease-free survival. CONCLUSIONS. When the hystopathological diagnosis of ENB is considered, the Hyams classification can be valid considering grade IV as an advanced stage that is sometimes difficult to differentiate from other undiferentiated tumors. The subcranial approach or craneofacial resection in advanced stages (Kadish C and some B) should be considered as the first treatment of choice. Radiotherapy is indicated in all cases and chemotherapy in selected cases. Hyams' classification was the only staging system that proved useful as a prognostic factor in our series.

INTRODUCTION. Esthesioneuroblastoma (ENB) is a very uncommon malignant tumor with a neuroectodermal origin that usually involves the anterior cranial fossa and nasal cavity. OBJECTIVES. To review our experience in the management of ENB and assess the validity of the histopathological diagnosis, modality of treatment and prognostic factors of the disease comparing our findings with the literature. METHODS. A retrospective study of 11 cases with the diagnosis of esthesioneuroblastoma treated in our hospital between 2000 and 2008. Statistical analysis was performed in search for prognostic factors. The bibliography about ENB published between 1990 and 2009 was reviewed RESULTS. There were 3 women and 8 men, with a mean age of 42 years old (range 20-71y). Their symptoms upon admission were nasal obstruction (81%), epistaxis (27%), visual loss (18%), headache and others. According to the Kadish Stage, 2 were stage B and 9 were stage C. Dulguerov and Calcaterra Classification was also used: 2 were T2, 3 were T3 and 6 were T4. The hystopathological result according to the Hyams classification was: 2 cases in stage I, 4 in stage II, 3 in stage III and 2 in stage IV. The two cases classified in stage IV changed the diagnosis to undifferenciate tumor in the second biopsy. A subcranial approach was performed in 8 cases combined with endonasal endoscopy to confirm the total removal, followed by radiotherapy in all and chemotherapy in one case, resulting on 62% (5 patients) being alive without disease, 12,5% (1 p) alive with disease, and 25% (2 p) dead of disease. Another patient was operated by a single endonasal endoscopic approach and a subtotal removal was achieved. This patient is alive without disease. The other 2 patients were treated by biopsy plus radiotherapy and chemotherapy, because they were considered unresectable, and one of them is alive with disease and the other one is dead of disease. Radiotherapy was performed in all cases and chemotherapy in 5 cases. The hystopathological grading system of Hyams was considered statistically significant as a prognostic factor of disease-free survival. CONCLUSIONS. When the hystopathological diagnosis of ENB is considered, the Hyams classification can be valid considering grade IV as an advanced stage that is sometimes difficult to differentiate from other undiferentiated tumors. The subcranial approach or craneofacial resection in advanced stages (Kadish C and some B) should be considered as the first treatment of choice. Radiotherapy is indicated in all cases and chemotherapy in selected cases. Hyams' classification was the only staging system that proved useful as a prognostic factor in our series.

The recent debate on both the existence and the cause of fractal (LEvy) patterns in animal movement resonates with much deeper and richer problems in movement ecology: (1) establishing mechanistic links between animal behavior and statistical patterns of movement, and (2) understanding what is the role of randomness (stochasticity) in animal motion. Here, the idea of behavioral intermittence is shown to be crucial to establish mechanistic connections between the behavior of organisms and the statistical properties they generate when moving. Attention is drawn to the fact that some random walk modeling procedures can impair the identification of intermittent biological mechanisms which could govern major statistical properties of movement. This fact, together with some misconceptions and prejudices regarding the role of randomness in animal motion may explain why stochastic processes have been disregarded as a potential source of adaptation in animal movement. In the near future, the advances in biotelemetry together with a more explicit consideration of behavioral intermittence, and the development of novel random walk approaches, could help us to set up the bases for a landscape-level behavioral ecology.

Random walk methods and diffusion theory pervaded ecological sciences as methods to analyze and describe animal movement. Consequently, statistical physics was mostly seen as a toolbox rather than as a conceptual framework that could contribute to theory on evolutionary biology and ecology. However, the existence of mechanistic relationships and feedbacks between behavioral processes and statistical patterns of movement suggests that, beyond movement quantification, statistical physics may prove to be an adequate framework to understand animal behavior across scales from an ecological and evolutionary perspective. Recently developed random search theory has served to critically re-evaluate classic ecological questions on animal foraging. For instance, during the last few years, there has been a growing debate on whether search behavior can include traits that improve success by optimizing random (stochastic) searches. Here, we stress the need to bring together the general encounter problem within foraging theory, as a mean for making progress in the biological understanding of random searching. By sketching the assumptions of optimal foraging theory (OFT) and by summarizing recent results on random search strategies, we pinpoint ways to extend classic OFT, and integrate the study of search strategies and its main results into the more general theory of optimal foraging.