Javier Jarillo

Impacts of environmental change on ecosystems are seemingly highly context‐dependent and contingent on details. Here, we provide mathematical and numerical evidence that there is some generality to the resistance of food webs to species loss. To this end, we mathematically analyse simple food web models, run simulations with randomly wired food webs, develop a spatially explicit meta‐community model for realistic macroinvertebrate communities inhabiting European streams, and analyse field data. These approaches jointly support three general rules for food web resistance: (1) all else equal, predators are more vulnerable than prey, and predator diversity declines before prey diversity; (2) food webs with higher prey diversity tend to be less resistant to environmental change; and (3) food web resistance decreases with the mean taxon tolerance and reaches a maximum at an optimal ratio of predator to prey tolerance. Our findings elucidate characteristics that make food webs vulnerable, fostering more effective conservation practices.

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs regional) and ecological scale (species vs community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are ``scale-free'' properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e. region or community) size.

Understanding the drivers of species coexistence is essential in ecology. Niche and fitness differences (i.e. how species limit themselves compared to others and species' differences in competitive ability, respectively) permit studying the consequences of species interactions. Yet, the multitude of methods to compute niche and fitness differences hampers cross‐community comparisons. Such shortcoming leaves a gap in our understanding of the natural drivers of species coexistence and whether niche or/and fitness differences capture them. Here, we standardised niche and fitness differences across 953 species pairs to investigate species coexistence across ecological groups and methodological settings (experimental setup, natural co‐occurrence, population model used and growth method). Using data gathered from 29 empirical papers, we asked whether large niche differences, small fitness differences or both explain predicted coexistence. Moreover, we performed an automated clustering algorithm to understand whether different underlying mechanisms drive species interactions. Finally, we tested whether any ecological or/and methodological settings drive these clusters. Species pairs predicted to coexist have larger niche differences but not smaller fitness differences than species pairs predicted not to coexist. Also, species pairs group into two clear clusters along the niche difference axis: those predicted to coexist and those that are not. Surprisingly, ecological or methodological settings do not drive these clusters. Synthesis. Overall, our results show that species coexistence is mainly influenced by mechanisms acting on niche differences, highlighting the importance of sustaining mechanisms that promote niche differences to maintain species coexistence. In addition, our results provide evidence that communities predicted to coexist differ from those that are not in ways that transcend their ecological grouping.

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs. regional) and ecological scale (species vs. community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are “scale-free” properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e., region or community) size. In conclusion, we find that scaling of stability depends on the metric considered, and we present a reliable framework to estimate these metrics.

Understanding the drivers of species coexistence is an important objective in ecology. Yet, the multitude of methods to study coexistence hampers cross-community comparisons. Here, we standardized niche and fitness differences (i.e how species limit themselves compared to others and their competitive ability, respectively) across 1018 species pairs to investigate species coexistence across ecological groups and methodological settings (experimental setup, natural co-occurrence, population model used, and growth method). We find that, first, coexistence is driven by large niche differences, not by small fitness differences. Second, species group into clear clusters of coexisting and non-coexisting species along the niche axis. Finally, these clusters are not driven by ecological or methodological settings. This suggests differences between coexisting and non-coexisting communities transcending those measured in our empirical systems. Overall, our results show that species coexistence is mainly influenced by mechanisms acting on niche differences.

Many species show synchronous fluctuations in population size over large geographical areas, which are likely to increase their regional extinction risk. Here we examine how the degree of spatial synchrony in population dynamics is affected by trophic interactions using a two-species predator-prey model with spatially correlated environmental noise. We show that the predator has a larger spatial scale of population synchrony than the prey if the population fluctuations of both species are mainly determined by the direct effect of stochastic environmental variations in the prey. This result implies that in ecosystems regulated from the bottom up, the spatial scale of synchrony of the predator population increases beyond the scale of the spatial autocorrelation in the environmental noise and in the prey fluctuations. Harvesting the prey increases the spatial scale of population synchrony of the predator, while harvesting the predator reduces the spatial scale of the population fluctuations of its prey. Hence, the development of sustainable harvesting strategies should also consider the impact on unharvested species at other trophic levels as well as human perturbations of ecosystems, whether the result of exploitation or an effect on dispersal processes, as they can affect food web structures and trophic interactions over large geographical areas.

Brownian ratchets are small-scale systems which rectify thermal fluctuations to produce a net current of particles. They have inspired many models of molecular motors that perform transport in the noisy environment of living cells. For the most common ratchet systems, this rectification is achieved by means of the switching of a periodic and spatially asymmetric potential (flashing ratchets) or by means of a rocking force (rocking ratchets). The rectification mechanism can be applied without information on the state of the system (open-loop ratchets) or using information on the state of the system (feedback or closed-loop ratchets). In order to characterize the transport, the most used quantity is the mean velocity of the center of mass of the system. However, another important transport attribute that has not received much attention is its quality. Here we analyze the quality of transport by studying the coherence and reproducibility of the transport induced by several representative open- and closed-loop rectification protocols under the maximum mean velocity conditions. We find that for few-particle systems, the best protocol is the rocked feedback protocol, producing the transport of particles with the highest coherence and reproducibility per distance traveled at the maximum mean velocity, while for larger systems it is overtaken by its open-loop counterpart. Our results also show that protocols with similar maximum mean velocities can have quite different coherences and reproducibilities. This highlights the importance of studying the reliability of rectified transport to develop performant synthetic rectification devices. These contributions to the emerging field of reliable transport in noisy environments are expected also to provide insight into the performance of natural molecular motors.

Theoretical analyses of single‐species models have revealed that the degree of synchrony in fluctuations of geographically separated populations increases with increasing spatial covariation in environmental fluctuations and increased interchange of individuals, but decreases with local strength of density dependence. Here we extend these results to include interspecific competition between two species as well as harvesting. We show that the effects of interspecific competition on the geographical scale of population synchrony are dependent on the pattern of spatial covariation of environmental variables. If the environmental noise is uncorrelated between the competing species, competition generally increases the spatial scale of population synchrony of both species. Otherwise, if the environmental noises are strongly correlated between species, competition generally increases the spatial scale of population synchrony of at least one, but also often of both species. The magnitude of these spatial scaling effects is, however, strongly influenced by the dispersal capacity of the two competing species. If the species are subject to proportional harvesting, this may synchronise population dynamics over large geographical areas, affecting the vulnerability of harvested species to environmental changes. However, the strength of interspecific competition may strongly modify this effect of harvesting on the spatial scale of population synchrony. For example, harvesting of one species may affect the spatial distribution of competing species that are not subject to harvesting. These analytical results provide an important illustration of the importance of applying an ecosystem rather than a single‐species perspective when developing harvest strategies for a sustainable management of exploited species.

Single-stranded DNA-binding proteins (SSBs) play a key role in genome maintenance, binding and organizing single-stranded DNA (ssDNA) intermediates. Multimeric SSBs, such as the human mitochondrial SSB (HmtSSB), present multiple sites to interact with ssDNA, which has been shown in vitro to enable them to bind a variable number of single-stranded nucleotides depending on the salt and protein concentration. It has long been suggested that different binding modes might be used selectively for different functions. To study this possibility, we used optical tweezers to determine and compare the structure and energetics of long, individual HmtSSB–DNA complexes assembled on preformed ssDNA and on ssDNA generated gradually during ‘in situ’ DNA synthesis. We show that HmtSSB binds to preformed ssDNA in two major modes, depending on salt and protein concentration. However, when protein binding was coupled to strand-displacement DNA synthesis, only one of the two binding modes was observed under all experimental conditions. Our results reveal a key role for the gradual generation of ssDNA in modulating the binding mode of a multimeric SSB protein and consequently, in generating the appropriate nucleoprotein structure for DNA synthetic reactions required for genome maintenance.

Ligands binding to polymers regulate polymer functions by changing their physical and chemical properties. This ligand regulation plays a key role in many biological processes. We propose here a model to explain the mechanical, thermodynamic, and kinetic properties of the process of binding of small ligands to long biopolymers. These properties can now be measured at the single molecule level using force spectroscopy techniques. Our model performs an effective decomposition of the ligand-polymer system on its covered and uncovered regions, showing that the elastic properties of the ligand-polymer depend explicitly on the ligand coverage of the polymer (i.e., the fraction of the polymer covered by the ligand). The equilibrium coverage that minimizes the free energy of the ligand-polymer system is computed as a function of the applied force. We show how ligands tune the mechanical properties of a polymer, in particular its length and stiffness, in a force dependent manner. In addition, it is shown how ligand binding can be regulated applying mechanical tension on the polymer. Moreover, the binding kinetics study shows that, in the case where the ligand binds and organizes the polymer in different modes, the binding process can present transient shortening or lengthening of the polymer, caused by changes in the relative coverage by the different ligand modes. Our model will be useful to understand ligand-binding regulation of biological processes, such as the metabolism of nucleic acid. In particular, this model allows estimating the coverage fraction and the ligand mode characteristics from the force extension curves of a ligand-polymer system.