The EICAT+ framework enables classification of positive impacts of alien taxa on native biodiversity.

Species introduced through human-related activities beyond their native range, termed alien species, have various impacts worldwide. The IUCN Environmental Impact Classification for Alien Taxa (EICAT) is a global standard to assess negative impacts of alien species on native biodiversity. Alien species can also positively affect biodiversity (for instance, through food and habitat provisioning or dispersal facilitation) but there is currently no standardized and evidence-based system to classify positive impacts. We fill this gap by proposing EICAT+, which uses 5 semiquantitative scenarios to categorize the magnitude of positive impacts, and describes underlying mechanisms. EICAT+ can be applied to all alien taxa at different spatial and organizational scales. The application of EICAT+ expands our understanding of the consequences of biological invasions and can inform conservation decisions.

Severe, rapid and widespread impacts of an Atlantic blue crab invasion.

The Atlantic blue crab (Callinectes sapidus) has rapidly invaded coastal environments in the western Mediterranean, but there is no consistent assessment of its impacts yet. We use interviews and long-term data series in the Ebro Delta (NE Spain) to: i) characterise the evolution of the blue crab invasion; and ii) identify its impacts. The blue crab was first recorded in 2012, but its expansion started around 2016, with an exponential increase in abundance between 2017 and 2018. Aquatic communities have tended to be dominated by the blue crab, coinciding with the steep and consistent declines of several species, including threatened and commercially exploited ones. Blue crab impacts seem to be exerted even at low abundances, arguably hindering the recovery of declining species. The blue crab is becoming a keystone species in invaded systems and efforts should be made to understand its many-folds impacts in order to prevent or mitigate them.

Positive associations among rare species and their persistence in ecological assemblages.

According to the competitive exclusion principle, species with low competitive abilities should be excluded by more efficient competitors; yet, they generally remain as rare species. Here, we describe the positive and negative spatial association networks of 326 disparate assemblages, showing a general organization pattern that simultaneously supports the primacy of competition and the persistence of rare species. Abundant species monopolize negative associations in about 90% of the assemblages. On the other hand, rare species are mostly involved in positive associations, forming small network modules. Simulations suggest that positive interactions among rare species and microhabitat preferences are the most probable mechanisms underpinning this pattern and rare species persistence. The consistent results across taxa and geography suggest a general explanation for the maintenance of biodiversity in competitive environments.

Exploring the solution landscape enables more reliable network community detection.

To understand how a complex system is organized and functions, researchers often identify communities in the system's network of interactions. Because it is practically impossible to explore all solutions to guarantee the best one, many community-detection algorithms rely on multiple stochastic searches. But for a given combination of network and stochastic algorithms, how many searches are sufficient to find a solution that is good enough? The standard approach is to pick a reasonably large number of searches and select the network partition with the highest quality or derive a consensus solution based on all network partitions. However, if different partitions have similar qualities such that the solution landscape is degenerate, the single best partition may miss relevant information, and a consensus solution may blur complementary communities. Here we address this degeneracy problem with coarse-grained descriptions of the solution landscape. We cluster network partitions based on their similarity and suggest an approach to determine the minimum number of searches required to describe the solution landscape adequately. To make good use of all partitions, we also propose different ways to explore the solution landscape, including a significance clustering procedure. We test these approaches on synthetic networks and a real-world network using two contrasting community-detection algorithms: The algorithm that can identify more general structures requires more searches, and networks with clearer community structures require fewer searches. We also find that exploring the coarse-grained solution landscape can reveal complementary solutions and enable more reliable community detection.

Human activity is altering the world's zoogeographical regions.

Zoogeographical regions, or zooregions, are areas of the Earth defined by species pools that reflect ecological, historical and evolutionary processes acting over millions of years. Consequently, researchers have assumed that zooregions are robust and unlikely to change on a human timescale. However, the increasing number of human-mediated introductions and extinctions can challenge this assumption. By delineating zooregions with a network-based algorithm, here we show that introductions and extinctions are altering the zooregions we know today. Introductions are homogenising the Eurasian and African mammal zooregions and also triggering less intuitive effects in birds and amphibians, such as dividing and redefining zooregions representing the Old and New World. Furthermore, these Old and New World amphibian zooregions are no longer detected when considering introductions plus extinctions of the most threatened species. Our findings highlight the profound and far-reaching impact of human activity and call for identifying and protecting the uniqueness of biotic assemblages.

From groups to communities in western lowland gorillas.

Social networks are the result of interactions between individuals at different temporal scales. Thus, sporadic intergroup encounters and individual forays play a central role in defining the dynamics of populations in social species. We assessed the rate of intergroup encounters for three western lowland gorilla ( Gorilla gorilla gorilla) groups with daily observations over 5 years, and non-invasively genotyped a larger population over four months. Both approaches revealed a social system much more dynamic than anticipated, with non-aggressive intergroup encounters that involved social play by immature individuals, exchanges of members between groups likely modulated by kinship, and absence of infanticide evidenced by infants not fathered by the silverback of the group where they were found. This resulted in a community composed of groups that interacted frequently and not-aggressively, contrasting with the more fragmented and aggressive mountain gorilla ( G. beringei beringei) societies. Such extended sociality can promote the sharing of behavioural and cultural traits, but might also increase the susceptibility of western lowland gorillas to infectious diseases that have decimated their populations in recent times.