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Abstract The unsustainable harvest of species for the global wildlife trade is a major cause of vertebrate extinction. Through the anthropogenic Allee effect (AAE), overexploitation to extinction can occur when a species' rarity drives up its market price, enabling profitable harvest of all remaining individuals. Even in the absence of rarity value, however, the harvest of other species can subsidize the overexploitation of a rare species to the point of extinction, a phenomenon termed opportunistic exploitation. These two pathways to extinction have been considered independently, but many traded species experience them simultaneously.In this study, we develop a simple model that incorporates these mechanisms simultaneously and demonstrate that including multiple harvest strategies with market‐based feedbacks fundamentally alters rare species extinction risk and the rate at which overexploitation occurs. As a pertinent case study, we consider the harvest of ground pangolinsSmutsia temminckii.Our results show that pangolin extinction was generally associated with high rarity value, the use of multiple harvest strategies and the simultaneous harvest of a common species that has a fast life history. Pangolin population depletion and short‐term extinction risk were greatest when harvesters used a combination of pursuit and opportunistic (i.e. multi‐species) harvest strategies.Policy implications.Our results suggest that feedbacks between multiple financial incentives to overharvest can exacerbate the risk of extinction of rare species. As a result, continuing to address AAE and opportunistic exploitation as separate extinction pathways may insufficiently capture extinction risk for many exploited species. Criteria for assessing extinction risk or harvest sustainability of exploited species should incorporate multiple drivers of harvest pressure, with an expanded focus on including species with high rarity value that are exploited in multi‐species harvest regimes. 

Abstract Although biological invasions play an important role in ecosystem change worldwide, little is known about how invasions are influenced by local abiotic stressors. Broadly, abiotic stressors can cause large-scale community changes in an ecosystem that influence its resilience. The possibility for these stressors to increase as global changes intensify highlights the pressing need to understand and characterize the effects that abiotic drivers may have on the dynamics and composition of a community. Here, we analyzed 26 years of weekly abundance data using the theory of regime shifts to understand how the structure of a resident community of dung beetles (composed of dweller and tunneler functional groups) responds to climatic changes in the presence of the invasive tunnelerDigitonthophagus gazella. Although the community showed an initial dominance by the invader that decreased over time, the theory of regime shifts reveals the possibility of an ecological transition driven by climate factors (summarized here in a climatic index that combines minimum temperature and relative humidity). Mid and low values of the driver led to the existence of two alternative stable states for the community structure (i.e. dominance of either dwellers or tunnelers for similar values of the climatic driver), whereas large values of the driver led to the single dominance by tunnelers. We also quantified the stability of these states against climatic changes (resilience), which provides insight on the conditions under which the success of an invasion and/or the recovery of the previous status quo for the ecosystem are expected. Our approach can help understand the role of climatic changes in community responses, and improve our capacity to deal with regime shifts caused by the introduction of exotic species in new ecosystems. 

Depinning of elastic systems advancing on disordered media can usually be described by the quenched Edwards-Wilkinson equation (qEW). However, additional ingredients such as anharmonicity and forces that cannot be derived from a potential energy may generate a different scaling behavior at depinning. The most experimentally relevant is the Kardar-Parisi-Zhang (KPZ) term, proportional to the square of the slope at each site, which drives the critical behavior into the so-called quenched KPZ (qKPZ) universality class. We study this universality class both numerically and analytically: by using exact mappings we show that at least for d = 1, 2 this class encompasses not only the qKPZ equation itself, but also anharmonic depinning and a well-known class of cellular automata introduced by Tang and Leschhorn. We develop scaling arguments for all critical exponents, including size and duration of avalanches. The scale is set by the confining potential strength m2 . This allows us to estimate numerically these exponents as well as the m-dependent effective force correlator (w), and its correlation length ρ := (0)/|′ (0)|. Finally, we present an algorithm to numerically estimate the effective (m-dependent) elasticity c, and the effective KPZ nonlinearity λ. This allows us to define a dimensionless universal KPZ amplitude A := ρλ/c, which takes the value A = 1.10(2) in all systems considered in d = 1. This proves that qKPZ is the effective field theory for all these models. Our work paves the way for a deeper understanding of depinning in the qKPZ class, and in particular, for the construction of a field theory that we describe in a companion paper. 

Self-organized spatial patterns are ubiquitous in ecological systems and allow populations to adopt non-trivial spatial distributions starting from disordered configurations. These patterns form due to diverse nonlinear interactions among organisms and between organisms and their environment, and lead to the emergence of new (eco)system-level properties unique to self-organized systems. Such pattern consequences include higher resilience and resistance to environmental changes, abrupt ecosystem collapse, hysteresis loops, and reversal of competitive exclusion. Here, we review ecological systems exhibiting self-organized patterns. We establish two broad pattern categories depending on whether the self-organizing process is primarily driven by nonlinear density-dependent demographic rates or by nonlinear density-dependent movement. Using this organization, we examine a wide range of observational scales, from microbial colonies to whole ecosystems, and discuss the mechanisms hypothesized to underlie observed patterns and their system-level consequences. For each example, we review both the empirical evidence and the existing theoretical frameworks developed to identify the causes and consequences of patterning. Finally, we trace qualitative similarities across systems and propose possible ways of developing a more quantitative understanding of how self-organization operates across systems and observational scales in ecology.