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Ecologists and space agencies must forge a global monitoring strategy, say Andrew K. Skidmore, Nathalie Pettorelli and colleagues.

When an animal settles preferentially in a habitat within which it does poorly relative to other available habitats, it is said to have been caught in an \"ecological trap.\" Although the theoretical possibility that animals may be so trapped is widely recognized, the absence of a clear mechanistic understanding of what constitutes a trap means that much of the literature cited as support for the idea may be weak, at best. Here, we develop a conceptual model to explain how an ecological trap might work, outline the specific criteria that are necessary for demonstrating the existence of an ecological trap, and provide tools for researchers to use in detecting ecological traps. We then review the existing literature and summarize the state of empirical evidence for the existence of traps. Our conceptual model suggests that there are two basic kinds of ecological traps and three mechanisms by which traps may be created. To this point in time, there are still only a few solid empirical examples of ecological traps in the published literature (although those few examples suggest that both types of traps and all three of the predicted mechanisms do exist in nature). Therefore, ecological traps are either rare in nature, are difficult to detect, or both. An improved library of empirical studies will be essential if we are to develop a more synthetic understanding of the mechanisms that can trigger maladaptive behavior in general and the specific conditions under which ecological traps might occur.

Sustainable model for fisheries One approach to more sustainable fisheries is that of co-management, in which fishers and managers take joint responsibility for regulation. The evidence that this works is largely anecdotal, so Nicolás Gutiérrez and colleagues systematically examined 130 co-managed fisheries to find which attributes of co-management are required for success. Leadership, social cohesion, clear incentives and conservation efforts topped the list. On their evidence, the authors suggest, the co-management model could solve many of the problems facing commercial fisheries around the world. One approach to sustainable fisheries is that of co-management, in which fishers and managers take joint responsibility for regulation. The evidence that this works is largely anecdotal, so this study systematically examined 130 co-managed fisheries. Several attributes of co-management were required for success, with leadership being the most important. A total of 8 attributes of co-management were required for a successful fishery, and above this number there was a linear relationship between the extent of co-management and success. One billion people depend on seafood as their primary source of protein and 25% of the world’s total animal protein comes from fisheries 1 . Yet a third of fish stocks worldwide are overexploited or depleted 1 , 2 . Using individual case studies, many have argued that community-based co-management 3 should prevent the tragedy of the commons 4 because cooperative management by fishers, managers and scientists often results in sustainable fisheries 3 , 5 , 6 . However, general and multidisciplinary evaluations of co-management regimes and the conditions for social, economic and ecological success within such regimes are lacking. Here we examine 130 co-managed fisheries in a wide range of countries with different degrees of development, ecosystems, fishing sectors and type of resources. We identified strong leadership as the most important attribute contributing to success, followed by individual or community quotas, social cohesion and protected areas. Less important conditions included enforcement mechanisms, long-term management policies and life history of the resources. Fisheries were most successful when at least eight co-management attributes were present, showing a strong positive relationship between the number of these attributes and success, owing to redundancy in management regulations. Our results demonstrate the critical importance of prominent community leaders and robust social capital 7 , combined with clear incentives through catch shares and conservation benefits derived from protected areas, for successfully managing aquatic resources and securing the livelihoods of communities depending on them. Our study offers hope that co-management, the only realistic solution for the majority of the world’s fisheries, can solve many of the problems facing global fisheries.

While an increasing number of indices for estimating the functional trait diversity of biological communities are being proposed, there is a growing demand by ecologists to clarify their actual implications and simplify index selection. Several key indices relate to mean trait dissimilarity between species within biological communities. Among them, the most widely used include (a) the mean species pairwise dissimilarity (MPD) and (b) the Rao quadratic entropy (and related indices). These indices are often regarded as redundant and promote the unsubstantiated yet widely held view that Rao is a form of MPD. Worryingly, existing R functions also do not always simplify the use and differentiation of these indices. In this paper, we show various distinctions between these two indices that warrant mathematical and biological consideration. We start by showing an existing form of MPD that considers species abundances and is different from Rao both mathematically and conceptually. We then show that the mathematical relationship between MPD and Rao can be presented simply as Rao = MPD × Simpson, where the Simpson diversity index is defined as 1 − dominance. We further show that this relationship is maintained for both species abundances and presence/absence. This evidence dismantles the paradigm that the Rao diversity is an abundance-weighted form of MPD and indicates that both indices can differ substantially at low species diversities. We discuss the different interpretations of trait diversity patterns in biological communities provided by Rao and MPD and then provide a simple R function, called “melodic,” which avoids the unintended results that arise from existing mainstream functions.

The form of the species richness-productivity relationship (SRPR) is both theoretically important and contentious. In an effort to distill general patterns, ecologists have undertaken meta-analyses, within which each SRPR data set is first classified into one of five alternative forms: positive, humped (unimodal), negative, U-shaped (unimodal), and no relationship. Herein, I first provide a critique of this approach, based on 68 plant data sets/studies used in three meta-analyses published in Ecology. The meta-analyses are shown to have resulted in highly divergent outcomes, inconsistent and often highly inappropriate classification of data sets, and the introduction and multiplication of errors from one meta-analysis to the next. I therefore call on the ecological community at large to adopt a far more rigorous and critical attitude to the use of meta-analysis. Second, I develop the argument that the literature on the SRPR continues to be bedeviled by a common failing to appreciate the fundamental importance of the scale of analysis, beginning with the confusion evident between concepts of grain, focus, and extent. I postulate that variation in the form of the SRPR at fine scales of analysis owes much to artifacts of the sampling regime adopted. An improved understanding may emerge from combining sampling theory with an understanding of the factors controlling the form of species abundance distributions and species accumulation curves.

History has profoundly affected the composition, distribution, and abundances of species in contemporary ecosystems. A full understanding of how ecosystems work and change must therefore take history into account. We offer four well-studied examples illustrating how a knowledge of history has strengthened interpretations of modern systems: the development of molluscan antipredatory defenses in relation to shell-breaking predators; the North Pacific kelp ecosystem with sea otters, smaller predators, sea urchins, and large herbivores; estuarine ecosystems affected by the decline in oysters and other suspension feeders; and the legacy of extinct large herbivores and frugivores in tropical American forests. Many current ecological problems would greatly benefit from a historical perspective. We highlight four of these: soil depletion and tree stunting in forests related to the disappearance of large consumers; the spread of anoxic dead zones in the ocean, which we argue could be mitigated by restoring predator and suspension-feeding guilds; ocean acidification, which would be alleviated by more nutrient recycling by consumers in the aerobic ecosystem; and the relation between species diversity and keystone predators, a foundational concept that is complicated by simplified trophic relationships in modern ecosystems.

The language that scientists use to frame biological invasions may reveal inherent bias-including how data are interpreted. A frequent critique of invasion biology is the use of value-laden language that may indicate context bias. Here we use a systematic study of language and interpretation in papers drawn from invasion biology to evaluate whether there is a link between the framing of papers and the interpretation of results. We also examine any trends in context bias in biological invasion research. We examined 651 peer-reviewed invasive species competition studies and implemented a rigorous systematic review to examine bias in the presentation and interpretation of native and invasive competition in invasion biology. We predicted that bias in the presentation of invasive species is increasing, as suggested by several authors, and that bias against invasive species would result in misinterpreting their competitive dominance in correlational observational studies compared to causative experimental studies. We indeed found evidence of bias in the presentation and interpretation of invasive species research; authors often introduced research with invasive species in a negative context and study results were interpreted against invasive species more in correlational studies. However, we also found a distinct decrease in those biases since the mid-2000s. Given that there have been several waves of criticism from scientists both inside and outside invasion biology, our evidence suggests that the subdiscipline has somewhat self-corrected apparent biases.

To investigate the sensitivity of model choice on the results, I used a Bayesian approach to sample the posterior distributions of competition (αij), growth rate (λi) and treatment effect parameters for seven different alternative competition models of similar complexity. Because coexistence is predicted using invasion analysis at these equilibria, it is important to acknowledge the potential trade-off between models' predictive performance on observed data (affecting estimates ofA and a), and realism when these are used to extrapolate carrying capacities. [...]of the original ten species pairs that were predicted to have switched coexistence outcomes between treatments, only four such switches are now predicted at probabilities greater than 0.5 (Fig. 1), including for two species pairs that were scored as not having switched in the original analysis. Carrying the posterior means of model 7's niche and fitness differences forward through the remaining analyses results in the loss of statistically significant differences between competition and demographic differences between treatments (Extended Data Fig. 1).

Wide distribution of findings shows how analytical choices drive conclusions. Wide distribution of findings shows how analytical choices drive conclusions. Credit: Laurence Dutton/Getty A young woman is surrounded by monitors & their reflections displaying scrolling text & data.

Modern life depends on the petrochemical industry--most drugs, paints and plastics derive from oil. But current processes for making chemical products are not sustainable in terms of resources and environmental impact. Green chemistry aims to tackle this problem, and real progress is being made.