Hasil untuk "Human ecology. Anthropogeography"

Allan A. Pacey

J. Lockwood, P. Cassey, T. Blackburn

R. Gibb, Ella Browning, Paul Glover-Kapfer et al.

High‐throughput environmental sensing technologies are increasingly central to global monitoring of the ecological impacts of human activities. In particular, the recent boom in passive acoustic sensors has provided efficient, noninvasive, and taxonomically broad means to study wildlife populations and communities, and monitor their responses to environmental change. However, until recently, technological costs and constraints have largely confined research in passive acoustic monitoring (PAM) to a handful of taxonomic groups (e.g., bats, cetaceans, birds), often in relatively small‐scale, proof‐of‐concept studies. The arrival of low‐cost, open‐source sensors is now rapidly expanding access to PAM technologies, making it vital to evaluate where these tools can contribute to broader efforts in ecology and biodiversity research. Here, we synthesise and critically assess the current emerging opportunities and challenges for PAM for ecological assessment and monitoring of both species populations and communities. We show that terrestrial and marine PAM applications are advancing rapidly, facilitated by emerging sensor hardware, the application of machine learning innovations to automated wildlife call identification, and work towards developing acoustic biodiversity indicators. However, the broader scope of PAM research remains constrained by limited availability of reference sound libraries and open‐source audio processing tools, especially for the tropics, and lack of clarity around the accuracy, transferability and limitations of many analytical methods. In order to improve possibilities for PAM globally, we emphasise the need for collaborative work to develop standardised survey and analysis protocols, publicly archived sound libraries, multiyear audio datasets, and a more robust theoretical and analytical framework for monitoring vocalising animal communities.

Michał Wawer, Jarosław A. Chudziak

When LLM-based multi-agent systems disagree, current practice treats this as noise to be resolved through consensus. We propose it can be signal. We focus on hate speech moderation, a domain where judgments depend on cultural context and individual value weightings, producing high legitimate disagreement among human annotators. We hypothesize that convergent disagreement, where agents reason similarly but conclude differently, indicates genuine value pluralism that humans also struggle to resolve. Using the Measuring Hate Speech corpus, we embed reasoning traces from five perspective-differentiated agents and classify disagreement patterns using a four-category taxonomy based on reasoning similarity and conclusion agreement. We find that raw reasoning divergence weakly predicts human annotator conflict, but the structure of agent discord carries additional signal: cases where agents agree on a verdict show markedly lower human disagreement than cases where they do not, with large effect sizes (d>0.8) surviving correction for multiple comparisons. Our taxonomy-based ordering correlates with human disagreement patterns. These preliminary findings motivate a shift from consensus-seeking to uncertainty-surfacing multi-agent design, where disagreement structure - not magnitude - guides when human judgment is needed.

Vojin Šerbedžija

Der Beitrag untersucht anhand eines prozessorientierten Verständnisses von Segregation die Entwicklungspfade junger migrantisierter Bewohner aus Berlin-Kreuzberg. Dieser Ansatz ermöglicht es, soziale und räumliche Dimensionen getrennt voneinander zu analysieren. Dabei liegt der Fokus auf Aspekten segregierter sozialer Nutzungen der Stadt und Erfahrungen mit urbanen Institutionen – aus der Perspektive der Heranwachsenden. Die longitudinale empirische Analyse basiert auf qualitativen Daten aus zwei zusammenhängenden Forschungsprojekten (2017/2018 und 2023/2024) mit Erst- und Folgeinterviews in einem Zeitraum von fünf bis sechs Jahren. Anhand von Vignetten stellt der Beitrag die teilweise kontrastreichen Entwicklungspfade ausgewählter junger Männer sowie deren Überschneidungen dar. Diese verweisen trotz tendenziell gesteigerter räumlicher Alltagsradien auf Muster einer dauerhaften sozialen Segregation.

Fatemeh poorbafarani, aboozar vafaei, Esmaeil Mazroui Nasrabadi

1. IntroductionToday, creative tourism is one of the most important ways to improve the economic status of cities, but despite the benefits of developing this model of tourism, its implementation is not easy and there are numerous challenges to its realization. In this regard, the city of Nain is one of the urban areas that, despite benefiting from various forms of tourism, namely historical, agricultural, natural, handicrafts and physical, and allocating a share of the city's economy to this activity, faces challenges in various dimensions in realizing creative tourism. Therefore, the present study aims to identify and model the challenges of creative tourism in the city of Nain, to form the basis for proper policy and decision-making by the authorities in this field, and ultimately to remove the obstacles to realizing creative tourism in the city.2. Research MethodologyThe research type is applied in terms of purpose and descriptive-analytical in terms of method. The statistical population of the research consists of two levels including officials, city managers and city tourism activists, and academic experts and specialists. The sampling method is judgmental and the sample size for the first group is 17 people in the form of semi-structured interviews based on theoretical saturation and for the second group, 10 people in the form of questionnaires. The data collection method is field-based and its tool is semi-structured interviews in the field of creative tourism challenges and a questionnaire developed by the researcher in the field of modeling creative tourism challenges. To design the interview protocol, after reviewing the relevant literature, the PESTEL technique was used to design questions. Pairwise comparisons between factors were used to design researcher-made questionnaires. Thematic analysis was used to analyze data in the stage of identifying creative tourism challenges and interpretive structural modeling (ISM) was used to model creative tourism challenges.3. Results and discussionThe results of the interviews revealed 39 challenges of creative tourism in the city, which were divided into 17 subcategories, including "presence of various types of pollution in the city's tourism space", "excessive use of the city's pristine and natural space", "ignorance of local customs and traditions", "lack of use of traditional elements in the recreation of urban spaces", "lack of motivation and willingness to invest", "weakness of government finances in supporting various tourism sectors", "lack of concerned managers in the tourism sector", "divergence of tourism sector managers and lack of teamwork", "lack of necessary tools for guidance and advertising", "lack of primary tourism infrastructure", "weakness of executive management of the tourism sector", "lack of training, preparation and accompanying the host community in tourism activities", "lack of necessary preparation for tourists to familiarize themselves with the culture of the local community", "lack of educational and specialized centers in the tourism sector", "lack of interactions and communications with tourism sector activists in all parts of the country and the world", "ignorance of the city's tourism capacities", "Lack of planning to implement traditional and local ceremonies continuously throughout the year" and 9 main categories including "Existence of environmental pollutants and damage to nature tourism", "Forgetting the original culture and identity of the city", "Lack of a sustainable tourism economy", "Lack of a unified policy and strategy in the field of tourism", "Lack of facilities, equipment and services in the field of tourism", "Lack of creative and convergent management", "Lack of culture and trust building for the local community and tourists", "Lack of specialized and practical training", "Lack of a comprehensive tourism package to offer" were categorized. Next, in order to more accurately analyze the challenges of the city's creative tourism, their interpretative structural model was drawn and the position of each challenge was examined in it.4. ConclusionThe present study has identified and modeled the challenges of creative tourism in the city of Nain. The results of the theoretical study of the research show that creative tourism is a type of tourism that distinguishes and develops the creative experiences of tourists and prioritizes sustainability. However, there have always been obstacles and challenges to the sustainability of this type of tourism, which include infrastructure challenges such as the lack of adequate and suitable accommodation and amenities, as well as a weak structure for creating jobs, inadequate education, lack of smart technologies, lack of guidelines, and inadequate training. On the other hand, comparing the research findings with theoretical foundations shows that Nain city is one of the urban areas that, despite benefiting from various forms of tourism and allocating a share of the city's economy to this activity, faces challenges in the field of creative tourism, including the lack of specialized training centers in various fields of tourism, a shortage of specialized personnel in the field of tourism, the lack of facilities and equipment necessary for the development of city tourism, lack of investment in various tourism affairs, and the weakness and incompetence of tourism sector managers. These challenges can hinder the path of creative and dynamic economic formation and ultimately the sustainable development of the city's tourism. Therefore, the results of the present study show that there are several challenges in the development of creative tourism in this city. The output of the structural model showed that the challenge of lack of creative and convergent management is the most important of all challenges; Because experts believe that the lack of creative and convergent management in the city of Nain has led to the lack of support from senior city managers for the tourism sector, the lack of alignment between executive institutions and the private sector in this area, the lack of a real and concerned custodian in the city's tourism sector, and the inability of executive managers to actualize the city's existing capacities and capabilities in the tourism sector.

Jérôme Bocquet

Ana Davila, Jacinto Colan, Yasuhisa Hasegawa

Ambiguity in natural language instructions poses significant risks in safety-critical human-robot interaction, particularly in domains such as surgery. To address this, we propose a framework that uses Large Language Models (LLMs) for ambiguity detection specifically designed for collaborative surgical scenarios. Our method employs an ensemble of LLM evaluators, each configured with distinct prompting techniques to identify linguistic, contextual, procedural, and critical ambiguities. A chain-of-thought evaluator is included to systematically analyze instruction structure for potential issues. Individual evaluator assessments are synthesized through conformal prediction, which yields non-conformity scores based on comparison to a labeled calibration dataset. Evaluating Llama 3.2 11B and Gemma 3 12B, we observed classification accuracy exceeding 60% in differentiating ambiguous from unambiguous surgical instructions. Our approach improves the safety and reliability of human-robot collaboration in surgery by offering a mechanism to identify potentially ambiguous instructions before robot action.

Florian Mai, David Kaczér, Nicholas Kluge Corrêa et al.

Two core challenges of alignment are 1) scalable oversight and 2) accounting for the dynamic nature of human values. While solutions like recursive reward modeling address 1), they do not simultaneously account for 2). We sketch a roadmap for a novel algorithmic framework that trains a superhuman reasoning model to decompose complex tasks into subtasks that are still amenable to human-level guidance. Our approach relies on what we call the part-to-complete generalization hypothesis, which states that the alignment of subtask solutions generalizes to the alignment of complete solutions. We advocate for the need to measure this generalization and propose ways to improve it in the future.

Katie Seaborn

Social identity theory (SIT) and social categorization theory (SCT) are two facets of the social identity approach (SIA) to understanding social phenomena. SIT and SCT are models that describe and explain how people interact with one another socially, connecting the individual to the group through an understanding of underlying psychological mechanisms and intergroup behaviour. SIT, originally developed in the 1970s, and SCT, a later, more general offshoot, have been broadly applied to a range of social phenomena among people. The rise of increasingly social machines embedded in daily life has spurned efforts on understanding whether and how artificial agents can and do participate in SIA activities. As agents like social robots and chatbots powered by sophisticated large language models (LLMs) advance, understanding the real and potential roles of these technologies as social entities is crucial. Here, I provide a primer on SIA and extrapolate, through case studies and imagined examples, how SIT and SCT can apply to artificial social agents. I emphasize that not all human models and sub-theories will apply. I further argue that, given the emerging competence of these machines and our tendency to be taken in by them, we experts may need to don the hat of the uncanny killjoy, for our own good.

Kewei Sui, Anindita Ghosh, Inwoo Hwang et al.

Humans inhabit a world defined by interactions -- with other humans, objects, and environments. These interactive movements not only convey our relationships with our surroundings but also demonstrate how we perceive and communicate with the real world. Therefore, replicating these interaction behaviors in digital systems has emerged as an important topic for applications in robotics, virtual reality, and animation. While recent advances in deep generative models and new datasets have accelerated progress in this field, significant challenges remain in modeling the intricate human dynamics and their interactions with entities in the external world. In this survey, we present, for the first time, a comprehensive overview of the literature in human interaction motion generation. We begin by establishing foundational concepts essential for understanding the research background. We then systematically review existing solutions and datasets across three primary interaction tasks -- human-human, human-object, and human-scene interactions -- followed by evaluation metrics. Finally, we discuss open research directions and future opportunities.

J. Wall, Nathan R. Hahn, Sarah Carroll et al.

Understanding drivers of space use by African elephants is critical to their conservation and management, particularly given their large home-ranges, extensive resource requirements, ecological role as ecosystem engineers, involvement in human-elephant conflict and as a target species for ivory poaching. In this study we investigated resource selection by elephants inhabiting the Greater Mara Ecosystem in Southwestern Kenya in relation to three distinct but spatially contiguous management zones: (i) the government protected Maasai Mara National Reserve (ii) community-owned wildlife conservancies, and (iii) elephant range outside any formal wildlife protected area. We combined GPS tracking data from 49 elephants with spatial covariate information to compare elephant selection across these management zones using a hierarchical Bayesian framework, providing insight regarding how human activities structure elephant spatial behavior. We also contrasted differences in selection by zone across several data strata: sex, season and time-of-day. Our results showed that the strongest selection by elephants was for closed-canopy forest and the strongest avoidance was for open-cover, but that selection behavior varied significantly by management zone and selection for cover was accentuated in human-dominated areas. When contrasting selection parameters according to strata, variability in selection parameter values reduced along a protection gradient whereby elephants tended to behave more similarly (limited plasticity) in the human dominated, unprotected zone and more variably (greater plasticity) in the protected reserve. However, avoidance of slope was consistent across all zones. Differences in selection behavior was greatest between sexes, followed by time-of-day, then management zone and finally season (where seasonal selection showed the least differentiation of the contrasts assessed). By contrasting selection coefficients across strata, our analysis quantifies behavioural switching related to human presence and impact displayed by a cognitively advanced megaherbivore. Our study broadens the knowledge base about the movement ecology of African elephants and builds our capacity for both management and conservation.

Karthika Sangilidurai, Sivasubramanian Karuppusamy, Dhevagi Periyasamy et al.

Although plastics provide numerous conveniences for human life, concerns about ecosystems and human life are rising tremendously due to increased plastic production and consumption. The ubiquitous presence and undeniable distribution of microplastics (MPs) in agricultural usage created a major risk concern for soil ecology and human health. The ecological risk assessment of microplastics in agricultural sites in the Coimbatore region of South India has been evaluated using three ecological risk indices: Pollution Hazard Index (PHI), Pollution Load Index (PLI), and Potential Ecological Risk Index (PERI). Based on the concentration of hazardous MPs (Polyethylene, polystyrene, polyacrylonitrile, polyacrylamide, polyacrylamide, polypropylene, polyvinyl chloride) in sampling sites, risk assessment indicated the major risk level in inorganic fertilizers applied site. Meanwhile, PLI indicated that all the sites were in category I with low pollution load in the region. However, the hazard scores of polymers increased the PERI values and exhibited their values in the extremely dangerous category. Since the models for evaluating MPs risk in agricultural sites are not yet developed, this calculation is cautiously calculated and further research could gradually add base reference data for understanding the distribution, ecological risk, and trophic transfer of MPs.

A. Bevan, B. Cutler, C. Hennig et al.

Quantifiable, spatially-resolved, large-scale evidence about traditional food storage facilities is extremely rare, and yet highly insightful for researchers across subjects such as human ecology, anthropology, agronomy, archaeology and economic history. This paper takes advantage of some unusually detailed French colonial era records of cereal storage and agro-pastoral practice in 19th century central Algeria that inventory the underground food stores of different sedentary and nomadic tribes at a moment of colonial confrontation in which these stores were central to ecological and political resilience. We consider how different aspects of these food stores relate to environmental, social and economic variables across the study area. The overall results suggest important north-south trends in agro-pastoral lifestyle and storage practice.

A. D’Agostino, G. Di Marco, M. Rolfo et al.

Abstract Plants have always represented a key element in landscape delineation. Indeed, plant diversity, whose distribution is influenced by geographic/climatic variability, has affected both environmental and human ecology. The present contribution represents a multi‐proxy study focused on the detection of starch, pollen and non‐pollen palynomorphs in ancient dental calculus collected from pre‐historical individuals buried at La Sassa and Pila archaeological sites (Central Italy). The collected record suggested the potential use of plant taxa by the people living in Central Italy during the Copper‐Middle Bronze Age and expanded the body of evidence reported by previous palynological and palaeoecological studies. The application of a microscopic approach provided information about domesticated crops and/or gathered wild plants and inferred considerations on ancient environments, water sources, and past health and diseases. Moreover, the research supplied data to define the natural resources (e.g., C4‐plant intake) and the social use of the space during that period. Another important aspect was the finding of plant clues referable to woody habitats, characterised by broad‐leaved deciduous taxa and generally indicative of a warm‐temperate climate and grassy vegetation. Other unusual records (e.g., diatoms, brachysclereids) participated in defining the prehistoric ecological framework. Thus, this work provides an overview on the potential of the human dental calculus analysis to delineate some features of the ancient plant ecology and biodiversity.

Jordyn Young, Laala M Jawara, Diep N Nguyen et al.

Generative Artificial Intelligence (AI) is integrated into everyday technology, including news, education, and social media. AI has further pervaded private conversations as conversational partners, auto-completion, and response suggestions. As social media becomes young people's main method of peer support exchange, we need to understand when and how AI can facilitate and assist in such exchanges in a beneficial, safe, and socially appropriate way. We asked 622 young people to complete an online survey and evaluate blinded human- and AI-generated responses to help-seeking messages. We found that participants preferred the AI-generated response to situations about relationships, self-expression, and physical health. However, when addressing a sensitive topic, like suicidal thoughts, young people preferred the human response. We also discuss the role of training in online peer support exchange and its implications for supporting young people's well-being. Disclaimer: This paper includes sensitive topics, including suicide ideation. Reader discretion is advised.

David Pehlke

The steering of the residential development on the regional level is one of the major tasks of regional planning. Nevertheless, no nationwide information is yet available on the implementation of the planning instruments in regional plans. Moreover, for potential steering types, only one approach on the level of the German federal states exists. To reduce this information deficit, a plan content analysis is used to determine which positive planning instruments were implemented in the state development plans and regional plans valid in 2017. The data basis for negative planning instruments is the spatial development plan monitor of the Federal Office for Building and Regional Planning (BBSR). With these data, a non-linear principal component analysis and a cluster analysis is carried out to identify specific steering types. As a result, six regional planning steering types of pre-use planning, quantitative control, settlement axes, positive planning location control, intra-municipal framework with extensive mono-functional open space protection and extensive location control through multifunctional open space protection can be identified. The different steering types are often spatially clustered, so that a significant influence of state planning requirements can be assumed.

Nada Samir Farag, Gehan Elsayed Abd eldayem, Ahmed Saleh Abd Elfatah

Cities confront massive issues like Disasters, climate change, urbanization, population growth, and economic growth; it is necessary to reduce their impact to the minimum possible. To accomplish this, A smart, resilient society intended to manage cities using Big Data, the Internet of Things (IoT), and intelligent information technologies to improve the ability to resist, absorb, and adapt to external changes resulting in urban resilience. Beyond that, constructing a smart, resilient city is a more advanced strategy for reducing vulnerabilities to emergencies like the COVID-19 pandemic and natural disasters like earthquakes and tsunamis. This study proposes a conceptual design for smart resilience cities and explores how a system can improve risk reduction and adaptation approaches and natural disaster recovery. Using various examples, the various states how smart cities' characteristics help cities be more resilient to disasters. The paper explains the differences and similarities between a smart city and a resilient city.

Ran Tian, Masayoshi Tomizuka, Anca Dragan et al.

Humans have internal models of robots (like their physical capabilities), the world (like what will happen next), and their tasks (like a preferred goal). However, human internal models are not always perfect: for example, it is easy to underestimate a robot's inertia. Nevertheless, these models change and improve over time as humans gather more experience. Interestingly, robot actions influence what this experience is, and therefore influence how people's internal models change. In this work we take a step towards enabling robots to understand the influence they have, leverage it to better assist people, and help human models more quickly align with reality. Our key idea is to model the human's learning as a nonlinear dynamical system which evolves the human's internal model given new observations. We formulate a novel optimization problem to infer the human's learning dynamics from demonstrations that naturally exhibit human learning. We then formalize how robots can influence human learning by embedding the human's learning dynamics model into the robot planning problem. Although our formulations provide concrete problem statements, they are intractable to solve in full generality. We contribute an approximation that sacrifices the complexity of the human internal models we can represent, but enables robots to learn the nonlinear dynamics of these internal models. We evaluate our inference and planning methods in a suite of simulated environments and an in-person user study, where a 7DOF robotic arm teaches participants to be better teleoperators. While influencing human learning remains an open problem, our results demonstrate that this influence is possible and can be helpful in real human-robot interaction.

Viktor Kewenig, Andrew Lampinen, Samuel A. Nastase et al.

The potential of multimodal generative artificial intelligence (mAI) to replicate human grounded language understanding, including the pragmatic, context-rich aspects of communication, remains to be clarified. Humans are known to use salient multimodal features, such as visual cues, to facilitate the processing of upcoming words. Correspondingly, multimodal computational models can integrate visual and linguistic data using a visual attention mechanism to assign next-word probabilities. To test whether these processes align, we tasked both human participants (N = 200) as well as several state-of-the-art computational models with evaluating the predictability of forthcoming words after viewing short audio-only or audio-visual clips with speech. During the task, the model's attention weights were recorded and human attention was indexed via eye tracking. Results show that predictability estimates from humans aligned more closely with scores generated from multimodal models vs. their unimodal counterparts. Furthermore, including an attention mechanism doubled alignment with human judgments when visual and linguistic context facilitated predictions. In these cases, the model's attention patches and human eye tracking significantly overlapped. Our results indicate that improved modeling of naturalistic language processing in mAI does not merely depend on training diet but can be driven by multimodality in combination with attention-based architectures. Humans and computational models alike can leverage the predictive constraints of multimodal information by attending to relevant features in the input.