End‐user involvement to improve predictions and management of populations with complex dynamics and multiple drivers

Informing natural resources policy making using participatory rapid economic valuation (PREV): the case of the Togean Islands, Indonesia

The expansion, densification and proliferation of urban areas around the world is currently occurring at a rate that is unprecedented in human history. It is predicted that global urban land cover will triple between 2000 and 2030, with some regions (including biodiversity hotspots) experiencing a ninefold increase in urban land cover over the same time period (Seto, G€ uneralp & Hutyra 2012). Accompanying the expansion of urban landscapes, it is anticipated that the human population living in cities and towns globally will increase from 3 5 to 5 billion people within the next 20 years (Fragkias et al. 2013). Thus, the demands of an expanding and urbanizing human population are one of the pressing ecological problems our world is facing (Sanderson et al. 2002), alongside, and in combination with, global climate change and changes to biodiversity at local and global scales (Pimm et al. 2014). Yet, urban environments also present a unique opportunity to expand our fundamental knowledge related to ecology and evolution due to the presence of intense and often novel selection pressures. In the inaugural issue of this journal, Calow (1987) defined functional ecology as the sum of three interactive processes: (i) those occurring between organisms and their environment, (ii) biotic interactions between organisms and (iii) adaptive processes driven by natural selection. The same three processes were highlighted 1 year earlier by Jared Diamond in Nature, when he called for biologists to pay more attention to the potential of using the unprecedented environmental conditions that exist within towns and cities to develop and test evolutionary and ecological theory (Diamond 1986). There is thus a natural synergy between functional ecology and urban ecology, as exemplified by some of the classic papers that have appeared in this journal, such as Rydell (1992) who demonstrated that the form of echolocation system determined the impact of light pollution on bat foraging behaviour. The potential of combining functional ecological research with urban ecology is, however, a long way from being fully realized. This is in part explained by the youth of urban ecology as a discipline. Scientific enquiry into the ecological consequences of urban environments has been underway for over half a century, although most of the momentum emerged after the mid 1990s (McDonnell 2011; Wu 2014). Thus, the focus of much urban research to date has involved describing patterns along environmental gradients (Gagn e 2013; McDonnell & Hahs 2013) rather than investigating the mechanistic processes that lie at the heart of functional ecology. To be effective in addressing the global challenges of urbanization, a much better understanding of how the urban environment affects the ecology and evolution of organisms needs to be developed (Grimm et al. 2008; Marzluff 2012; Gil & Brumm 2014; McDonnell & Hahs 2015). The purpose of this special feature is to draw attention to the plethora of opportunities that await researchers investigating the ecology and evolution of organisms in urban environments. The combination of environmental stressors and conditions within urban areas provides a novel opportunity to test and expand our theories related to ecology and evolution of organisms, and some intriguing insights are already beginning to emerge. For example, the detailed understanding of the molecular, genetic and developmental mechanisms of beak evolution that has arisen from studying Galapagos finches has been significantly advanced by studying beak evolution in the house finch Carpodacus mexicanus in response to novel urban food sources and its consequences for acoustic communication (Badyaev 2010, 2014). Thus, urban ecology has the potential to extend our understanding of extremely well-studied ecological and evolutionary problems.

The initial issue of complexity management in companies is the identification of the drivers of complexity. However, current literature lacks methods for assisting practitioners in the initial identification of such drivers. This paper, therefore, presents a novel framework for assisting practitioners with identifying complexity drivers in manufacturing companies. The framework uses a generic value chain and a generic product structure as its two dimensions. Multiple workshops are then conducted with company representatives across different value chain fields focusing on two main parts: First, surveys are used to assign complexity ratings to different generic product structure elements. Secondly, the complexity ratings are elaborated on by workshop participants. The process provides valuable insights into the perceived complexity drivers. The framework is then verified through a case study in the process industry. Based on the case study, multiple complexity drivers were identified across both value chain fields and product structure elements. The case study findings show that the framework facilitates practitioners in identifying organization-wide perceived complexity drivers. The framework contributes to both industry and research by addressing a neglected aspect of complexity management. It achieves this by providing a comprehensive and structured approach for the initial identification of complexity drivers across product elements and value chain fields.

Invasive species pose one of the greatest global threats to biodiversity. There has been a long history of importing coevolved natural enemies to act as biological control agents to try to suppress densities of invasive species, with historically limited success and frequent adverse impacts on native biodiversity. Our understanding of the processes and drivers of successful biological control has been focussed on invertebrates and is evidently limited and potentially ill‐suited with respect to biological control of vertebrate populations. The restoration of native vertebrate predator populations provides a promising nature‐based solution for slowing, halting, or even reversing the spread of some invasive vertebrates over spatial scales relevant to the management of wildlife populations. Here, we first review the growing literature and data from the pine marten‐red and grey squirrel system in Europe. We synthesise a multi‐decadal dataset to show that the recovery of a native predator has resulted in rapid, landscape‐scale declines of an established invasive species. We then use the model system, predator–prey interaction theory, and examples from the literature to develop ecological theory relating to natural biological control in vertebrates and evolutionary processes in native‐invasive predator–prey interactions. We find support for the hypotheses that evolutionary naivety of invasive species to native predators and lack of local refuges results in higher predation of naive compared to coevolved prey. We apply lessons learnt from the marten‐squirrel model system to examine the plausibility of specific native predator solutions to some of the Earth's most devastating invasive vertebrates. Given the evidence, we conclude that depletion of vertebrate predator populations has increased ecosystem vulnerability to invasions and thus facilitated the spread of invasive species. Therefore, restoration of vertebrate predator populations is an underappreciated, fundamental, nature‐based solution to the crisis of invasive species and should be a priority for vertebrate invasive species management globally.

Summary1. Identification of suitable habitats for small, endangered populations is important to preserve key areas for potential augmentation. However, replicated spatial data from a sufficient number of individuals are often unavailable for such populations, leading to unreliable habitat models. This is the case for the endangered Pyrenean brown bear Ursus arctos population, with only about 20 individuals surviving in two isolated groups.2. We conducted habitat suitability analyses at two spatial scales (coarse and local). Given the limited available data, we used information from the nearby Cantabrian brown bear population in Spain to develop a two‐dimensional model (human and natural variables) at a coarse scale, based on logistic regression, which we applied in the Pyrenees. At a local scale, we used bear presence in the Pyrenees to describe the population’s ecological niche and develop a habitat suitability model using presence‐only methods. We combined these models to obtain a more integrative understanding of bear requirements.3. The coarse‐scale model showed a good transferability to the Pyrenees, identifying preference for areas with high forest connectivity, masting trees, rugged terrain and shrubs and avoidance of areas with anthropogenic structures. The local‐scale model was consistent with the coarse‐scale model. Bears showed a trade‐off between food resources (scarcer at high elevations) and human presence (higher at low elevations).4. Our models illustrated that there is unoccupied good habitat for bears in the Pyrenees that could host new individuals. Combining two scales allowed us to identify areas that should be prioritized for management actions and also those that should be easier to manage for bears.5. Synthesis and applications. Our study illustrates how a nested‐scale approach, combining coarse data from a different population and fine‐scale local data, can aid in the management of small populations with limited data. This was applied to remnant brown bear populations to identify priorities for conservation management.

Genome-wide evaluations of genetic diversity and population structure are important for informing management and conservation of trailing-edge populations. North American moose (Alces alces) are declining along portions of the southern edge of their range due to disease, species interactions, and marginal habitat, all of which may be exacerbated by climate change. We employed a genotyping by sequencing (GBS) approach in an effort to collect baseline information on the genetic variation of moose inhabiting the species’ southern range periphery in the contiguous United States. We identified 1920 single nucleotide polymorphisms (SNPs) from 155 moose representing three subspecies from five states: A. a. americana (New Hampshire), A. a. andersoni (Minnesota), and A. a. shirasi (Idaho, Montana, and Wyoming). Molecular analyses supported three geographically isolated clusters, congruent with currently recognized subspecies. Additionally, while moderately low genetic diversity was observed, there was little evidence of inbreeding. Results also indicated > 20% shared ancestry proportions between A. a. shirasi samples from northern Montana and A. a. andersoni samples from Minnesota, indicating a putative hybrid zone warranting further investigation. GBS has proven to be a simple and effective method for genome-wide SNP discovery in moose and provides robust data for informing herd management and conservation priorities. With increasing disease, predation, and climate related pressure on range edge moose populations in the United States, the use of SNP data to identify gene flow between subspecies may prove a powerful tool for moose management and recovery, particularly if hybrid moose are more able to adapt.

Climate change and other anthropogenic pressures have led to the ongoing ocean global change, including ocean acidification, sea surface warming, deoxygenation, and changes in nutrient and light regimes. These changes simultaneously alter multiple chemical and physical seawater properties of marine ecosystems, which propagate to diverse marine microorganisms inhabiting these environments. On the other hand, the changes in marine microbial communities provide feedbacks to the environment via diverse metabolic activities, further modulate the dwelling environments, and ultimately influence the global climate. It is noteworthy that the changes in various environmental drivers in the marine environment tend to occur simultaneously and thus have complex mulplicative effects on marine ecosystems. In order to make more precise projections of the ecological consequences of global ocean change, it is essential to elucidate the biological responses to a complex matrix of environmental changes.Marine microbial communities, particularly phytoplankton, are the first responders of these complex environmental changes. As the

Ecologists and oceanographers inform population and ecosystem management by identifying the physical drivers of ecological dynamics. However, different research communities use different analytical tools where, for example, physical oceanographers often apply rank-reduction techniques (a.k.a. empirical orthogonal functions [EOF]) to identify indicators that represent dominant modes of physical variability, whereas population ecologists use dynamical models that incorporate physical indicators as covariates. Simultaneously modeling physical and biological processes would have several benefits, including improved communication across sub-fields; more efficient use of limited data; and the ability to compare importance of physical and biological drivers for population dynamics. Here, we develop a new statistical technique, EOF regression, which jointly models population-scale dynamics and spatially distributed physical dynamics. EOF regression is fitted using maximum-likelihood techniques and applies a generalized EOF analysis to environmental measurements, estimates one or more time series representing modes of environmental variability, and simultaneously estimates the association of this time series with biological measurements. By doing so, it identifies a spatial map of environmental conditions that are best correlated with annual variability in the biological process. We demonstrate this method using a linear (Ricker) model for early-life survival ("recruitment") of three groundfish species in the eastern Bering Sea from 1982 to 2016, combined with measurements and end-of-century projections for bottom and sea surface temperature. Results suggest that (a) we can forecast biological dynamics while applying delta-correction and statistical downscaling to calibrate measurements and projected physical variables, (b) physical drivers are statistically significant for Pacific cod and walleye pollock recruitment, (c) separately analyzing physical and biological variables fails to identify the significant association for walleye pollock, and (d) cod and pollock will likely have reduced recruitment given forecasted temperatures over future decades.

Many mammal species have been extensively impacted by human interventions in the past. It was especially important for endangered or key species such as European bison Bison bonasus, which has a long history of human interventions and is currently a refugee species confined by anthropogenic activities to suboptimal forest habitats. Using archival information (1795–1915) on bison population dynamics and management practices in Eastern Poland’s Białowieża Primeval Forest (BPF) in three periods (1795–1860, 1861–1888, 1889–1915) differing in management goals, we identify the main factors affecting bison numbers and discuss implications of this knowledge for modern conservation of the species. Mean annual increase rate of bison population varied between 3.03% in the first, − 3.04% in the second, and 2.69% in the third period. The most important drivers of European bison population dynamics were the increasing supplementary feeding and anthropogenic offtake (annual number of individuals hunted, live-captured and poached), along with opening of the forest by different traditional activities. Although this management was solely directed at hunting goals, relatively low intensity of animal removal and counteracting effect of supplementary feeding secured the survival of the species. However, management practices applied in all three periods acted against natural selection and increased animal dependence on human support. Collected historical data presents a unique long-term assessment of management practices and their effectiveness and allows to draw conclusions for the current management of the species. Historical management was not based on evidence. The general principles of traditional bison management were adapted by the twentieth-century management of reinstated population. To avoid repeating the same mistakes, the contemporary management model needs revaluation and changes to conform to up-to-date knowledge on the species habitat selection and forage requirements. Continuation of traditional management practices will sustain species refugee status.

Strengthening coastal adaptation planning through scenario analysis: A beneficial but incomplete solution

The subject matter of this article is cyber hygiene of the digital twin of the occupational safety management system of engineering and technical personnel of civil aviation. The goal is to develop a methodology for assessing the cyber hygiene of the digital twin of the occupational safety management system of engineering and technical personnel of civil aviation in the context of transformation into the quantum future. The tasks: to develop a methodology for assessing the state of the digital twin of the occupational safety management system of engineering and technical personnel of civil aviation using an integral cyber hygiene index; to develop a model of transitions of the functional state of the digital twin, allowing to predict its cybersecurity, cyber vulnerability and recovery capabilities in case of cyber-attacks; to determine cyber hygiene measures for the digital twin in the context of quantum transformation. Results: a methodology for assessing the cyber hygiene of the digital twin of the occupational safety management system of engineering and technical personnel of civil aviation in the context of quantum transformation has been developed; it has been proven that the process of transition of the cyber hygiene system from one state to another, in response to the measures taken, is an iterative process, which allows dynamically monitoring the effectiveness of the taken measures on DT cyber hygiene and predicting its further state; algorithm for the sequence of stages of assessing the state of DT cyber hygiene and their relationship within a cyclic process has been developed. Conclusions: a method for assessing the state of DT cyber hygiene has been developed, which, due to its iterative nature and the use of Markov chains, allows determining the probability of the transition of the cyber hygiene system from one state to another, as a response to the measures taken. The application of this method in practice will allow dynamic monitoring of the cyber hygiene of the digital twin and the effectiveness of the measures taken, as well as predicting its future state.

The main drivers of global environmental change (CO2 enrichment, nitrogen deposition, climate, biotic invasions and land use) cause extinctions and alter species distributions, and recent evidence shows that they exert pervasive impacts on various antagonistic and mutualistic interactions among species. In this review, we synthesize data from 688 published studies to show that these drivers often alter competitive interactions among plants and animals, exert multitrophic effects on the decomposer food web, increase intensity of pathogen infection, weaken mutualisms involving plants, and enhance herbivory while having variable effects on predation. A recurrent finding is that there is substantial variability among studies in both the magnitude and direction of effects of any given GEC driver on any given type of biotic interaction. Further, we show that higher order effects among multiple drivers acting simultaneously create challenges in predicting future responses to global environmental change, and that extrapolating these complex impacts across entire networks of species interactions yields unanticipated effects on ecosystems. Finally, we conclude that in order to reliably predict the effects of GEC on community and ecosystem processes, the greatest single challenge will be to determine how biotic and abiotic context alters the direction and magnitude of GEC effects on biotic interactions.

IntroductionThe Da Xing’an Mountains region harbors China's only cold-temperate coniferous forests and serves as a critical ecological barrier, playing a vital role in forest ecosystems and carbon sequestration. Stand age, shaped by population dynamics, disturbance regimes, and management practices, significantly influences the global carbon cycle. Although forest development is known to correlate with productivity shifts, how production varies across specific stand developmental stages and the relative contributions of driving factors remain poorly understood.MethodsUsing data from the National Forest Continuous Inventory (NFCI, 2005–2010) in the eastern Da Xing’an Mountains, we analyzed the effects of stand characteristics, structural diversity, and environmental variables on Net Ecosystem Carbon Change (NECC) across a spectrum of developmental stages, from young to overaged forests.ResultsOur findings demonstrate that: (1) Net Ecosystem Carbon Change (NECC) is co-limited by stand characteristics, structural diversity, and environmental factors, with stand characteristics exerting the strongest influence, primarily via direct effects. (2) As stands develop, the impacts of structural diversity (effect increasing from 8.68% to 16.44%) and soil factors (from 8.80% to 10.30%) on productivity intensify. (3) In contrast, the influence of climate (decreasing from 30.40% to 17.67%) and terrain (from 14.55% to 6.28%) diminishes with advancing growth stages.DiscussionThis study provides a comprehensive, system-level analysis of the determinants of Net Ecosystem Carbon Change (NECC). By integrating multiple drivers, our work establishes a theoretical foundation for predicting Net Ecosystem Carbon Change (NECC) changes under global change scenarios. These insights are crucial for formulating effective forest management strategies to mitigate the challenges of climate change and biodiversity loss.

Gaining insight into the impact of anthropogenic change on ecosystems requires investigation into interdependencies between multiple drivers of ecological change and multiple biotic responses. Global environmental change drivers can act simultaneously to impact the abundance and diversity of biota, but few studies have also measured the impact across trophic levels. We firstly investigated whether climate (using temperature differences across a latitudinal gradient as a surrogate) interacts with habitat fragmentation (measured according to fragment area and distance to habitat edges) to impact a New Zealand tri-trophic food chain (plant, herbivore and natural enemy). Secondly, we examined how these interactions might differentially impact both the density and biotic processes of species at each of the three trophic levels. We found evidence to suggest that these drivers act non-additively across trophic levels. The nature of these interactions however varied: location synergistically interacted with fragmentation measures to exacerbate the detrimental effects on consumer density; and antagonistically interacted to ameliorate the impact on plant density and on the interactions between trophic levels (herbivory and parasitoid attack rate). Our findings indicate that the ecological consequences of multiple global change drivers are strongly interactive and vary according to the trophic level studied and whether density or ecological processes are investigated.

Environmental effects are stronger than human effects on mammalian predator-prey relationships in arid Australian ecosystems