Broad‐scale changes in tundra‐nesting bird abundance in response to hyperabundant geese

Predator home range size mediates indirect interactions between prey species in an arctic vertebrate community

Indirect interactions are widespread among prey species that share a common predator, but the underlying mechanisms driving these interactions are often unclear, and our ability to predict their outcome is limited. Changes in behavioural traits that impact predator space use could be a key proximal mechanism mediating indirect interactions, but there is little empirical evidence of the causes and consequences of such behavioural-numerical response in multispecies systems. Here, we investigate the complex ecological relationships between seven prey species sharing a common predator. We used a path analysis approach on a comprehensive 9-year data set simultaneously tracking predator space use, prey densities and prey mortality rate on key species of a simplified Arctic food web. We show that high availability of a clumped and spatially predictable prey (goose eggs) leads to a twofold reduction in predator (arctic fox) home range size, which increases local predator density and strongly decreases nest survival of an incidental prey (American golden plover). On the contrary, a scattered cyclic prey with potentially lower spatial predictability (lemming) had a weaker effect on fox space use and an overall positive impact on the survival of incidental prey. These contrasting effects underline the importance of studying behavioural responses of predators in multiprey systems and to explicitly integrate behavioural-numerical responses in multispecies predator-prey models.

Climate-related range shifts in Arctic-breeding shorebirds

Aim

To test whether the occupancy of shorebirds has changed in the eastern Canadian Arctic, and whether these changes could indicate that shorebird distributions are shifting in response to long-term climate change.

Location

Foxe Basin and Rasmussen Lowlands, Nunavut, Canada.

Methods

We used a unique set of observations, made 25 years apart, using general linear models to test if there was a relationship between changes in shorebird species' occupancy and their species temperature Index, a simple version of a species climate envelope.

Results

Changes in occupancy and density varied widely across species, with some increasing and some decreasing. This is despite that overall population trends are known to be negative for all of these species based on surveys during migration. The changes in occupancy that we observed were positively related to the species temperature index, such that the warmer-breeding species appear to be moving into these regions, while colder-breeding species appear to be shifting out of the regions, likely northward.

Main Conclusions

Our results suggest that we should be concerned about declining breeding habitat availability for bird species whose current breeding ranges are centered on higher and colder latitudes.

EcoQBNs: First Application of Ecological Modeling with Quantum Bayesian Networks

A recent advancement in modeling was the development of quantum Bayesian networks (QBNs). QBNs generally differ from BNs by substituting traditional Bayes calculus in probability tables with the quantum amplification wave functions. QBNs can solve a variety of problems which are unsolvable by, or are too complex for, traditional BNs. These include problems with feedback loops and temporal expansions; problems with non-commutative dependencies in which the order of the specification of priors affects the posterior outcomes; problems with intransitive dependencies constituting the circular dominance of the outcomes; problems in which the input variables can affect each other, even if they are not causally linked (entanglement); problems in which there may be >1 dominant probability outcome dependent on small variations in inputs (superpositioning); and problems in which the outcomes are nonintuitive and defy traditional probability calculus (Parrondo’s paradox and the violation of the Sure Thing Principle). I present simple examples of these situations illustrating problems in prediction and diagnosis, and I demonstrate how BN solutions are infeasible, or at best require overly-complex latent variable structures. I then argue that many problems in ecology and evolution can be better depicted with ecological QBN (EcoQBN) modeling. The situations that fit these kinds of problems include noncommutative and intransitive ecosystems responding to suites of disturbance regimes with no specific or single climax condition, or that respond differently depending on the specific sequence of the disturbances (priors). Case examples are presented on the evaluation of habitat conditions for a bat species, representing state-transition models of a boreal forest under disturbance, and the entrainment of auditory signals among organisms. I argue that many current ecological analysis structures—such as state-and-transition models, predator–prey dynamics, the evolution of symbiotic relationships, ecological disturbance models, and much more—could greatly benefit from a QBN approach. I conclude by presenting EcoQBNs as a nascent field needing the further development of the quantum mathematical structures and, eventually, adjuncts to existing BN modeling shells or entirely new software programs to facilitate model development and application.

COVID19-induced reduction in human disturbance enhances fattening of an overabundant goose species

Overabundant species can have major impacts on their habitat and induce trophic cascades within ecosystems. In North America, the overabundant greater snow goose (Anser caerulescens atlanticus) has been successfully controlled through special spring hunting regulations since 1999. Hunting is a source of mortality but also of disturbance, which affects the behavior and nutrient storage dynamics of staging snow geese. In 2020, the lockdown imposed by the COVID19 pandemic reduced hunting activity during their migratory stopover in Québec by at least 31%. This provided a unique opportunity to assess the effects of a sudden reduction in hunting disturbance on geese. We used long-term data on body mass combined with movement data from GPS-tracked birds in 2019 and 2020 to assess the effects of the 2020 lockdown on the spring body condition and behavior of greater snow geese. Body condition was higher in 2020 than in all years since the inception of spring hunting in 1999, except for 2019. However, in 2020 geese reached maximal body condition earlier during the staging period than in any other year and reduced by half time spent feeding in highly profitable but risky agricultural habitat in late spring compared to 2019. Although our study was not designed to evaluate the effects of the lockdown, the associated reduction in disturbance in 2020 supports the hypothesis that hunting-related disturbance negatively affects foraging efficiency and body condition in geese. Since spring body condition is related to subsequent breeding success, the lockdown could increase productivity in this overabundant population.