Hasil untuk "General. Including nature conservation, geographical distribution"

Erle C. Ellis

Humans, unlike any other multicellular species in Earth's history, have emerged as a global force that is transforming the ecology of an entire planet. It is no longer possible to understand, predict, or successfully manage ecological pattern, process, or change without understanding why and how humans reshape these over the long term. Here, a general causal theory is presented to explain why human societies gained the capacity to globally alter the patterns, processes, and dynamics of ecology and how these anthropogenic alterations unfold over time and space as societies themselves change over human generational time. Building on existing theories of ecosystem engineering, niche construction, inclusive inheritance, cultural evolution, ultrasociality, and social change, this theory of anthroecological change holds that sociocultural evolution of subsistence regimes based on ecosystem engineering, social specialization, and non-kin exchange, or “sociocultural niche construction,” is the main cause of both the long-term upscaling of human societies and their unprecedented transformation of the biosphere. Human sociocultural niche construction can explain, where classic ecological theory cannot, the sustained transformative effects of human societies on biogeography, ecological succession, ecosystem processes, and the ecological patterns and processes of landscapes, biomes, and the biosphere. Anthroecology theory generates empirically testable hypotheses on the forms and trajectories of long-term anthropogenic ecological change that have significant theoretical and practical implications across the subdisciplines of ecology and conservation. Though still at an early stage of development, anthroecology theory aligns with and integrates established theoretical frameworks including social–ecological systems, social metabolism, countryside biogeography, novel ecosystems, and anthromes. The “fluxes of nature” are fast becoming “cultures of nature.” To investigate, understand, and address the ultimate causes of anthropogenic ecological change, not just the consequences, human sociocultural processes must become as much a part of ecological theory and practice as biological and geophysical processes are now. Strategies for achieving this goal and for advancing ecological science and conservation in an increasingly anthropogenic biosphere are presented.

Steph Bennington, Peter W. Dillingham, Lindsay Wickman et al.

Abstract Prediction of future population trajectories is vital in the management of threatened species but requires accurate estimates of demographic rates. One such parameter is fecundity, which is commonly expressed as the number of offspring produced per female per year. The endangered Hector's dolphin (Cephalorhynchus hectori) is Aotearoa New Zealand's only endemic cetacean and is threatened by bycatch from inshore trawl and gillnet fisheries. Here, we take advantage of 40 years of continued photo‐identification effort at Banks Peninsula to construct a Bayesian open‐population multi‐event capture–recapture model. We estimated fecundity for Hector's dolphins at 0.29 (95% credible interval [CI]: 0.22–0.39) which corresponds to an average calving frequency of one calf every 3.4 years (95% CI: 2.5–4.7 years). This new estimate is substantially lower and more precise than the previous estimate of fecundity for Hector's dolphins (e.g., 0.409, 95% CI: 0.267–0.635), but is based on a larger dataset, and aligns closely with estimates from other dolphin species. This updated estimate of fecundity indicates a lower capacity for population growth and reduced resilience to anthropogenic threats, including bycatch in fisheries.

Willem D. Briers-Louw, Tamar A. Kendon, Matthew S. Rogan et al.

The spotted hyaena Crocuta crocuta is relatively understudied across its range despite evidence of widespread declines. It is therefore essential that robust baseline population density assessments are conducted to inform current management and future conservation policy. In Mozambique this is urgent as decades of armed conflict followed by unchecked poaching have resulted in large-scale wildlife declines and extirpations. We conducted the first robust population density estimate for a spotted hyaena population in Mozambique using spatially explicit capture–recapture methodologies. We recorded a relatively low population density of 0.8–2.1 hyaenas/100 km2 in the wildlife management area Coutada 11 in the Zambezi Delta of central Mozambique in 2021. These densities are well below the estimated carrying capacity for the landscape and are comparable to published densities in high human-impact, miombo woodland-dominated and arid environments. The combination of historical armed conflict, marginal trophy hunting and bushmeat poaching using wire snares and gin traps (with physical injuries evident in 9% of identified individuals) presents persistent anthropogenic pressure, limiting the post-war recovery of this resident hyaena population. We provide insights into the dynamics of hyaena population status and recovery in such post-war landscapes, adding to mounting evidence that the species is less resilient to severe anthropogenic disturbances than previously believed. We recommend long-term monitoring of this and other carnivore populations in post-war landscapes to ascertain demographic trends and implement effective conservation interventions for population recovery.

Michael Timothy Bennett

Artificial general intelligence (AGI) is an established field of research. Yet some have questioned if the term still has meaning. AGI has been subject to so much hype and speculation it has become something of a Rorschach test. Melanie Mitchell argues the debate will only be settled through long term, scientific investigation. To that end here is a short, accessible and provocative overview of AGI. I compare definitions of intelligence, settling on intelligence in terms of adaptation and AGI as an artificial scientist. Taking my cue from Sutton's Bitter Lesson I describe two foundational tools used to build adaptive systems: search and approximation. I compare pros, cons, hybrids and architectures like o3, AlphaGo, AERA, NARS and Hyperon. I then discuss overall meta-approaches to making systems behave more intelligently. I divide them into scale-maxing, simp-maxing, w-maxing based on the Bitter Lesson, Ockham's and Bennett's Razors. These maximise resources, simplicity of form, and the weakness of constraints on functionality. I discuss examples including AIXI, the free energy principle and The Embiggening of language models. I conclude that though scale-maxed approximation dominates, AGI will be a fusion of tools and meta-approaches. The Embiggening was enabled by improvements in hardware. Now the bottlenecks are sample and energy efficiency.

Dung T. Tran, Huyen Ngoc Huyen, Hong Nguyen et al.

Rainfall forecasting in Vietnam is highly challenging due to its diverse climatic conditions and strong geographical variability across river basins, yet accurate and reliable forecasts are vital for flood management, hydropower operation, and disaster preparedness. In this work, we propose a Matrix Profile-based Weighted Ensemble (MPWE), a regime-switching framework that dynamically captures covariant dependencies among multiple geographical model forecasts while incorporating redundancy-aware weighting to balance contributions across models. We evaluate MPWE using rainfall forecasts from eight major basins in Vietnam, spanning five forecast horizons (1 hour and accumulated rainfall over 12, 24, 48, 72, and 84 hours). Experimental results show that MPWE consistently achieves lower mean and standard deviation of prediction errors compared to geographical models and ensemble baselines, demonstrating both improved accuracy and stability across basins and horizons.

Yan Tang

Existing solutions to the hotspot prediction problem in the field of geographic information remain at a relatively preliminary stage. This study presents a novel approach for detecting and predicting geographical hotspots, utilizing point cloud-voxel-community partition clustering. By analyzing high-dimensional data, we represent spatial information through point clouds, which are then subdivided into multiple voxels to enhance analytical efficiency. Our method identifies spatial voxels with similar characteristics through community partitioning, thereby revealing underlying patterns in hotspot distributions. Experimental results indicate that when applied to a dataset of archaeological sites in Turkey, our approach achieves a 19.31% increase in processing speed, with an accuracy loss of merely 6%, outperforming traditional clustering methods. This method not only provides a fresh perspective for hotspot prediction but also serves as an effective tool for high-dimensional data analysis.

Carlo Saccardi, Maximilian Pierzyna, Haitz Sáez de Ocáriz Borde et al.

Kilometer-scale weather data is crucial for real-world applications but remains computationally intensive to produce using traditional weather simulations. An emerging solution is to use deep learning models, which offer a faster alternative for climate downscaling. However, their reliability is still in question, as they are often evaluated using standard machine learning metrics rather than insights from atmospheric and weather physics. This paper benchmarks recent state-of-the-art deep learning models and introduces physics-inspired diagnostics to evaluate their performance and reliability, with a particular focus on geographic generalization and physical consistency. Our experiments show that, despite the seemingly strong performance of models such as CorrDiff, when trained on a limited set of European geographies (e.g., central Europe), they struggle to generalize to other regions such as Iberia, Morocco in the south, or Scandinavia in the north. They also fail to accurately capture second-order variables such as divergence and vorticity derived from predicted velocity fields. These deficiencies appear even in in-distribution geographies, indicating challenges in producing physically consistent predictions. We propose a simple initial solution: introducing a power spectral density loss function that empirically improves geographic generalization by encouraging the reconstruction of small-scale physical structures. The code for reproducing the experimental results can be found at https://github.com/CarloSaccardi/PSD-Downscaling

Masato Kimura, Hisanori Miyata

The Smoluchowski coagulation equation (SCE) is a population balance model that describes the time evolution of cluster size distributions resulting from particle aggregation. Although it is formally a mass-conserving system, solutions may exhibit a gelation phenomenon-a sudden loss of mass-when the coagulation kernel grows superlinearly. In this paper, we rigorously analyze mass conservation and gelation for weak solutions to the SCE with inhomogeneous coagulation kernels. By introducing a generalized moment framework, we derive sharp sufficient conditions for both mass conservation and gelation, expressed in terms of the initial data and the properties of the coagulation kernel.

Weiqi Wan, Weiqi Wan, Xingru Feng et al.

The coastal regions of Southeast China frequently experience unusual positive storm surges on the left side of landfalling typhoons, a phenomenon historically overlooked and inadequately explained by conventional circular wind field models. In this study, a high resolution, two-dimensional storm surge model based on ADCIRC along with tide gauge data were used to investigate the spatiotemporal distribution of these surges and proposes underlying mechanisms, informed by a comparative analysis of circular and ERA5 reanalysis wind fields during typical typhoon event 9711 Winnie. Analyzing tide gauge data spanning from 1986 to 2016, the study uncovers a distinct pattern of left-side positive storm surges along the southeastern coast, notably on the Fujian coast and within the Taiwan Strait, which are found to be comparable to those on the cyclone’s right side. The research also documents a significant escalation in both the frequency and intensity of these left-side surges over the past three decades. Simulation results highlights the inadequacies of circular wind field models in operational forecasting and emphasizes the necessity of accounting for topographic influences and the structural complexity of wind fields in storm surge predictions. This is particularly pertinent in semi-enclosed seas with intricate hydrodynamics, such as the Taiwan Strait. The insights gleaned from this study are pivotal for enhancing the real-time simulation and prediction of storm surges, which are vital for coastal safety and disaster prevention measures.

Chloe Steventon, Leanne Wicker, Elizabeth Dobson et al.

Abstract Leadbeater's possums (Gymnobelideus leadbeateri) are a critically endangered marsupial found in a restricted area of cold, wet forest in South‐Eastern Australia. The majority of Leadbeater's possums inhabit highland forest, with one outlying lowland population. In 2012, a breeding program was established for the lowland Leadbeater's possums when this genetically distinct population faced imminent extinction. Successful reproduction by highland Leadbeater's possums in the international zoo‐based population between 1970 and 2010 led to the widespread belief that the species bred readily in captivity. Lowland possums have not bred in the 2012–2021 contemporary captive conservation breeding program. This study reviewed the historic captive‐breeding data and found that of the 84% (162/194) that reached reproductive maturity; 37% of males (n = 30) and 39.5% of females (n = 32) bred, and this success was highly skewed towards a subset of highly fecund individuals (14% of females and 15% of males produced 75% and 80% of all offspring). Although lack of reproductive output in the captive lowland animals could be explained if age at mortality was lower than that of highlands possums, comparison of the longevity of highland and lowland animals had no significant difference. Conservation objectives that specify how captive breeding may support in situ recovery of wild populations are integral to the success of captive programs. A lack of reflective analysis of past husbandry records allowed misconceptions of success and approaches implemented in the management of the breeding program, reducing the benefits for the conservation of this high profile threatened species. This case study provides a lesson for the management of conservation breeding programs and illustrates the importance of well‐defined conservation objectives, integration of in situ and ex situ strategies, and the importance of objective, systematic and timely analysis of available evidence to inform management objectives and improve conservation outcomes in real time.

Shijie Zhou, Weidi Zhu, Yuhang He et al.

Achieving carbon neutrality in wastewater treatment plants relies heavily on mainstream anaerobic ammonia oxidation. However, the stability of this process is often compromised, largely due to the significant influence of microbial morphology. This study analyzed 208 microbial samples using bioinformatics and machine learning (ML) across four different morphologies: Suspended Sludge (SS), Biofilm, Granular Sludge (GS) and the Integrated Fixed-film Activated Sludge process (IFAS). The results revealed IFAS’s notably complex and stable community structure, along with the identification of endemic genera and common genera among the four microbial morphologies. Through co-occurrence network analysis, the interaction between microorganisms of various genera was displayed. Utilizing the Extreme Gradient Boosting (XGBoost) model, a ML modeling framework based on microbiome data was developed. The ML-based feature importance analysis identified LD-RB-34 as a key organism in SS and BSV26 was an important bacterium in IFAS. Additionally, functional bacteria KF-JG30-C25 occupied a higher proportion in GS, and Unclassified Brocadiaceae occupied a higher proportion in Biofilm. Furthermore, dissolved oxygen, temperature and pH were identified as the primary factors determining microbial communities and influencing anammox activity. Overall, this study deepens our understanding of bacterial communities to enhance the mainstream anammox nitrogen removal.

Peeter Saari, Ioannis M. Besieris

Hall and Abouraddy [1] have reported first experimental observation of optical de Broglie-Mackinnon wave packets, which is a seminal achievement in the study of so-called non-diffracting optical pulses. These wave packets propagate in free space without spreading with subluminal relativistic velocities, i.e., with speeds slower but close to the velocity of light in vacuum. The experiments in [1] became possible thanks to the application of quite a witty method. Unfortunately, the explanation of the physical nature of the wave packets and their graphical and mathematical descriptions in the theoretical part of [1] suffer from some ambiguities that need to be clarified.

E. Wilson

Megan L. Moran, Janet C. Steven, Jason A. Williams et al.

Abstract Abandoned mines offer important roosting habitat for several species of bats throughout the western United States. Currently, abandoned mine reclamation programs are tasked with closing abandoned mines to ameliorate safety, health, and environmental hazards found in and around these sites. Without appropriate pre‐closure evaluations to determine use of mine workings prior to closure, bats that depend on abandoned mines may be negatively impacted. To mitigate impacts of abandoned mine reclamation on bats, surveyors typically conduct pre‐closure biological evaluations and recommend wildlife compatible closures (e.g., bat gates) for ecologically important sites. Due to hazardous conditions found in many abandoned mines, internal surveys cannot always be conducted, and external surveys are not reliable for determining underground habitat or inferring past, future, or potential use of mines by bats when they are absent during external surveys. The purpose of our study was to use internal mine surveys to examine relationships between abandoned mine use by bats and characteristics of the mine and landscape, including portal area and shape, number of portals, mine depth, elevation, proximity to water and land use type. We found that surface features including land use type, distance to water, and elevation were associated with bat use, as were several mine features including depth of workings and portal shape. To best conserve sensitive species of bats, it is essential that pre‐closure biological evaluations be as detailed as possible to enhance biological understanding of species' roosting associations and distribution throughout the landscape. Further information will best facilitate development of ecologically sound closure recommendations for abandoned mine openings.

Qiaoling Liang, Zhengtao Shi, Yuehao Chen et al.

[Objective] The current level of ecological environmental change in the Yuanmou dry-hot valley from 2000 to 2020 was determined, and the dynamic monitoring and driving force of the regional ecology were analyzed in order to provide a theoretical basis for ecological environmental protection and sustainable development of the dry-hot valley. [Methods] Three Landsat TM/OIL image datasets were selected to calculate the greenness (NDVI), humidity (WET), dryness (NDBSI), and heat (LST) indexes to construct the remote sensing ecological index (RSEI) evaluation system. The ecological environmental factors affecting the region were quantified and analyzed by geographic detector. [Results] ① The mean values of RSEI in the Yuanmou dry-hot valley in 2000, 2010 and 2020 were 0.628, 0.609, and 0.684, respectively, showing a trend of initially decreasing and then increasing. ② During the 20-year study period, the area of ecological environmental improvement accounted for 29.58% of the total area, mainly located on both sides of the river valley. The area of ecological deterioration accounted for 21.45% of the total area, and was mainly scattered around agricultural areas and residential areas. ③ The driving force analysis of 10 factors affecting RSEI in the Yuanmou dry-hot valley showed that NDVI and land use had the strongest explanatory power for the spatial differentiation characteristics of RSEI. [Conclusion] The interaction results of multiple factors showed that the ecological environment of the Yuanmou dry-hot valley was the result of multiple factors, and all factors produced synergistic enhancement effects under the interaction. NDVI and land use were the main driving factors of eco-environmental quality in the study area. Therefore, in the exploration of Yuanmou ecological environmental restoration and protection, we should rationally plan and use land resources, and implement vegetation protection and restoration policies and measures.