Ecological Model Research Articles

Analysis of Ecological Environment in the Shanxi Section of the Yellow River Basin and Coal Mining Area Based on Improved Remote Sensing Ecological Index.

As a major coal-producing area, the Shanxi section of the Yellow River Basin has been significantly affected by coal mining activities in the local ecological environment. Therefore, an in-depth study of the ecological evolution in this region holds great scientific significance and practical value. In this study, the Shanxi section of the Yellow River Basin, including its planned coal mining area, was selected as the research subject. An improved remotely sensed ecological index model (NRSEI) integrating the remotely sensed ecological index (RSEI) and net primary productivity (NPP) of vegetation was constructed utilizing the Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, and the Sen + Mann-Kendall analysis method was employed to comprehensively assess the ecological environment quality and its evolutionary trends in the study area. The findings in this paper indicate the following data: (1) The contribution of the first principal component of the NRSEI model is more than 70%, and the average correlation coefficient is higher than 0.79. The model effectively integrates the information of multiple ecological indicators and enhances the applicability of regional ecological environment evaluation. (2) Between 2003 and 2022, the ecological environment quality in the Shanxi section of the Yellow River Basin showed an overall upward trend, with the average NRSEI value experiencing phases of fluctuation, increase, decline, and stabilization. The NRSEI values in non-coal mining areas consistently remained higher than those in coal mining areas. (3) Over 60% of the areas have improved ecological conditions, especially in coal mining areas. (4) The impact of coal mining on the ecological environment is significant within a 6 km radius, while the effects gradually diminish in the 6 to 10 km range. This study not only offers a reliable methodology for evaluating ecological environment quality on a large scale and over a long time series but also holds significant guiding value for the ecological restoration and sustainable development of the Shanxi section of the Yellow River Basin and its coal mining area.

The use of respiratory patient reported outcome measures (PROMs) in the management of COPD: Perceptions of Australian osteopaths

BackgroundPatient reported outcome measures (PROMs) are widely used to capture patients' perspectives of their health status and treatment outcomes and to enable practitioners to evaluate the effectiveness of interventions. The aim of this study was to explore Australian osteopaths’ perceptions of the use of respiratory PROMS in the management of chronic lung conditions. MethodsThis study drew on the social ecological model (SEM), which highlights the interdependence of contextual structures and processes. Osteopaths who were initially part of a larger mixed-methods study were invited to participate in semi-structured interviews. Transcripts were thematically analysed using the SEM. ResultsSeven of the original study osteopaths were interviewed. When presented with a patient who had a co-morbid respiratory condition, they focused on the musculoskeletal aspects of that condition (intrapersonal factors). Participants described sporadic use of musculoskeletal and quality of life PROMs in practice, and scarce use of respiratory PROMs (intrapersonal and organizational factors). Participants’ perceptions of their scope of practice strongly influenced their use of respiratory PROMs (environmental factors). ConclusionIntrapersonal and environmental factors were dominant drivers for participants’ scant use of respiratory PROMs. Further education on the scope and contribution of osteopaths to the management of chronic lung conditions and the use of respiratory PROMS is called for to promote multidisciplinary patient care.

Compensation Mechanism for Ecological Diversity Governance in Chinese River Basins Application Based on Low-Carbon Water Quality Game Theory

Background: Taking the construction of ecological civilization as an important core of the overall layout of the “Five in One” and the coordinated promotion of the “Four Comprehensives” strategic layout, combined with the global concept of ecological environment governance, provides a new direction for the reform and innovation of China’s watershed ecological compensation system through diversified governance. Subjects and methods: This article focuses on ecological compensation in river basins, exploring collaborative cooperation models between upstream and downstream of the basin under the dual constraints of “low-carbon” and “water quality”, to achieve a “win-win” situation between the ecological environment of the basin and all parties involved in basin protection. Based on the theory of evolutionary game theory, the indicators of “carbon emissions” and “water quality” are introduced to construct a diversified ecological co-governance compensation strategy model for the watershed. By exploring the optimal strategies among various entities in the upstream and downstream of the watershed. Results: (1) In the initial stage, the optimal strategy for ecological compensation in the watershed among stakeholders cannot achieve a stable balance through their evolution; (2) In the mature stage, based on the regulation of the superior government, interest subjects will choose a mutual supervision strategy to avoid bearing high penalties, to achieve Pareto effectiveness in achieving a stable overall economy of the basin; (3) By paying for high-quality resources from downstream and implementing carbon trading among basin entities, we can promote internal resource digestion, reduce intermediate transaction costs, and deeply promote the overall green and sustainable development of the basin. Through analysis, it has been proven that the conclusion is effective, providing decision support for the diversified co-governance of watershed ecosystems. Based on building an ecological community with a shared future in the watershed, we aim to achieve the construction of a community with a shared future for mankind.

Coevolution promotes the coexistence of Tasmanian devils and a fatal, transmissible cancer.

Emerging infectious diseases threaten natural populations, and data-driven modeling is critical for predicting population dynamics. Despite the importance of integrating ecology and evolution in models of host-pathogen dynamics, there are few wild populations for which long-term ecological datasets have been coupled with genome-scale data. Tasmanian devil (Sarcophilus harrisii ) populations have declined range-wide due to devil facial tumor disease (DFTD), a fatal transmissible cancer. Although early ecological models predicted imminent devil extinction, diseased devil populations persist at low densities, and recent ecological models predict long-term devil persistence. Substantial evidence supports evolution of both devils and DFTD, suggesting coevolution may also influence continued devil persistence. Thus, we developed an individual-based, eco-evolutionary model of devil-DFTD coevolution parameterized with nearly two decades of devil demography, DFTD epidemiology, and genome-wide association studies. We characterized potential devil-DFTD coevolutionary outcomes and predicted the effects of coevolution on devil persistence and devil-DFTD coexistence. We found a high probability of devil persistence over 50 devil generations (100 years) and a higher likelihood of devil-DFTD coexistence, with greater devil recovery, than predicted by previous ecological models. These novel results add to growing evidence for long-term devil persistence and highlight the importance of eco-evolutionary modeling for emerging infectious diseases.

Long-term alien marsh grass in China brings high carbon uptake capacity but cannot sustain high-temperature weather

Coastal wetlands, crucial in the global carbon cycle, face increasing challenges brought by extreme climate events, particularly high temperatures above plant tolerance thresholds. These conditions often exert great impact on plant, thereby potentially reducing overall ecosystem productivity. However, it has been observed that alien species, typically exhibiting higher productivity compared to native plant. Would plant invasion offset the loss of productivity caused by high-temperature events at ecosystem scale? In this study, we utilized data from 2020 to 2023 in China's Yangtze Estuary to investigate the responses of Spartina alterniflora (alien) and Phragmites australis (native) to high-temperature stress. Our results demonstrate that though the alien vegetation exhibits higher productivity before high temperature events, it experiences significant declines during high temperatures. In average, net ecosystem productivity (NEP) and gross primary productivity (GPP) of alien plant drops by 21.03% overall, with a notable 29.59% reduction during Neap tide. In contrast, native vegetation maintains a more stable productivity profile under the same conditions. Spring tide alleviate the negative impact of high temperatures on the alien vegetation, exhibiting a distinct environmental buffering effect. Photosynthetic photon flux density emerged as a crucial factor driving productivity, yet its effectiveness was moderated by aerodynamic conductance for heat transfer (Ga_h). Through the application of the Michaelis-Menten model, we confirmed that both species maintain similar maximum light utilization efficiencies, yet native vegetation demonstrates greater resilience to thermal stress. Additionally, we observed a 33.82% overestimation in productivity by the vegetation photosynthesis model (VPM) under high temperatures, emphasizing the need to refine how Ga_h impacts are integrated, particularly when comparing the resilience of native and alien species. We emphasize necessity of incorporating canopy structure factors into ecological models and underscore the importance of maintaining tidal dynamics for coastal wetland management.

Weak magnetic field for enhanced degradation of sulfamethoxazole by the CoFe2O4/PAA system: Insights into performance and mechanism

In this work, a novel approach coupling a heterogeneous weak magnetic field (WMF) with the CoFe2O4/peroxyacetic acid (PAA) system was employed to enhance the degradation of sulfamethoxazole (SMX). Under the optimized conditions of 50 mT WMF, 0.1 g/L CoFe2O4, 0.2 mM PAA, and initial pH 6.0, a complete degradation of 10 μM SMX was achieved in 25 min, exhibiting a high synergistic coefficient of 1.61. This result indicates a significant synergistic effect among WMF, CoFe2O4, and PAA in effectively degrading SMX. The introduction of WMF did not alter the pH application range of the CoFe2O4/PAA system. Furthermore, the degradation efficiency of SMX by the CoFe2O4/PAA/WMF system was significantly reduced in the presence of humic acid (HA) and bicarbonate ions (HCO3−), while chloride ions (Cl−) exhibited a minor inhibitory effect. Quenching experiments and electron paramagnetic resonance (EPR) analysis reveal that WMF did not alter the types of reactive oxygen species (ROS) generated in the CoFe2O4/PAA system. The degradation of SMX in the CoFe2O4/PAA/WMF system involved both radical (CH3C(O)O∙ and CH3C(O)OO∙) and non-radical (1O2) oxidation pathways, driven by the redox cycling between ≡Co2+/≡Co3+ and PAA, as well as the rapid adsorption and transformation of oxygen (O2) at oxygen vacancies (OV), respectively. The presence of WMF enhanced the utilization of PAA by CoFe2O4 by improving the convection and mass transport in the solution, facilitating the formation of superoxide anion (O2∙−) and supplemented lattice oxygen (O2−) through the directional migration of paramagnetic O2 towards the CoFe2O4 surface, thus significantly promoting ROS formation. Additionally, the degradation pathways of SMX in the CoFe2O4/PAA/WMF system were proposed based on density functional theory (DFT) calculations and the detected transformation products (TPs). The toxicity of SMX was effectively reduced, as verified by predictions from the Ecological Structure-Activity Relationship Model (ECOSAR) procedure. The excellent catalytic performance, reusability, and effective degradation of various organic pollutants demonstrated by the CoFe2O4/PAA/WMF system suggest its potential as a promising strategy for water treatment.

Use of an Ecological Compensation Model in Water Resource Development: A Case Study from Shaanxi Province, China

This study aims to analyze the current situation of water resource management in Shaanxi Province, study the basic principles of ecological compensation, evaluate the impact of water conservation projects on the ecological environment by establishing a model, and propose a sustainable water resource management model. Hanzhong City has certain typicality and representativeness within Shaanxi Province, and the problems it faces in water resource management and ecological environment may represent the entire province or similar regions. At the same time, Hanzhong City has rich data and research foundations. Therefore, by conducting a detailed analysis of the current water resource status in the Hanzhong City area of Shaanxi Province, the problems in current water resource management are revealed, and the basic principles of ecological compensation are intensely studied. The original ecological compensation plan in Shaanxi Province has been summarized. Guided by the concept of sustainable development, an ecological compensation model is established using algorithms, and the model is applied to sustainable water resource management. Establish a model for water conservation and water resource management through data collection, preprocessing, and cleaning, and apply it to practical cases in Hanzhong City. Through simulation and analysis of Hanzhong City, the new water resource management model effectively mitigates the adverse effects of water conservation projects on the ecological environment while improving water resource utilization efficiency. The changes in various environmental parameters indicate that the new plan has improved the ecological environment. Through the application of the model, the ecological compensation plan formulated has achieved sustainable protection of the ecological environment while promoting economic development. This study proposes a sustainable water resource management model through a comprehensive study of water resource management and ecological compensation in Shaanxi Province and verifies it in practical cases, demonstrating that the model has not only good applicability but also has significant effects in promoting economic growth and ecological environment protection.

Spatio-temporal Situation, Regional Differences, and Dynamic Evolution of the Distribution of Ecological Compensation in the Yellow River Basin

In the context of regional coordinated development and modernization of ecological and environmental governance capacity, the spatial collaborative governance of transboundary river basins has received extensive attention, but the ecological compensation of river basins is faced with the intertwined relationship of rights and responsibilities, and the horizontal ecological compensation mechanism has not yet been perfected. Based on the emergy ecological footprint model, the ecological compensation amount of 90 cities in the Yellow River Basin in 2007-2021 was measured, and the spatiotemporal pattern, regional differences, and dynamic evolution characteristics of distribution were explored by combining exploratory spatial data analysis, Dagum Gini coefficient, kernel density estimation, and spatial Markov chain analysis. The results showed that： ① The spatiotemporal pattern of ecological compensation in the Yellow River Basin was different, the ecological compensation amount decreased slightly in the fluctuation and increased from the northwest to southeast gradient in general, and the high-value areas were concentrated in the areas with a superior ecological background or developed economy, and some upstream cities had given up many development opportunities to maintain the ecological security of the Yellow River Basin, however, failed to obtain reasonable ecological compensation. ② A significant positive spatial agglomeration phenomenon was observed in ecological compensation and the overall spatial distribution trend was "cold in the north and hot in the south." The number of low-payment areas and low-compensation areas gradually decreased, showing a gradually shrinking agglomeration layout from the periphery to the center, whereas the number of high-payment areas and high-compensation areas continued to increase and formed a spatial evolution characteristic of the coexistence of scattered distribution and group distribution. ③ The overall regional differences in ecological compensation expanded. The over-variation density was the main source of the overall differences, and the focus on alleviating the intra-regional and inter-regional differences was located in the downstream areas. ④ A slight multi-level differentiation phenomenon was present in ecological compensation. The influence of different neighbors on the horizontal transfer of ecological compensation was quite different. This spatial spillover effect easily formed a "space club convergence" phenomenon within a certain geographical spatial range, but with the expansion of time, the probability of maintaining the original level of ecological compensation in each city decreased, and mobility gradually increased. Therefore, increasing the investment in ecological compensation in different fields, strengthening the coordinated development between regions, and giving full play to the spatial spillover effect are important ways to solve the current spatial imbalance of ecological compensation in the Yellow River Basin.

Comparative Study of Potential Habitats for Two Endemic Grassland Caterpillars on the Qinghai-Tibet Plateau Based on BIOMOD2 and Land Use Data.

This study has systematically investigated and compared the geographical distribution patterns and population density of G. menyuanensis (Gm) and G. qinghaiensis (Gq), which are endemic to the QTP region and inflict severe damage. Using a method combining the BIOMOD2 integration model (incorporating nine ecological niche models) and current species distribution data, this study has compared changes in potential habitats and distribution centers of these two species during ancient, present, and future climate periods and conducted a correlation test on the prediction results with land use types. The study results indicate that there are differences in geographical distribution patterns, distribution elevations, and population density of these two species. Compared with single models, the integration model exhibits prominent accuracy and stability with higher KAPPA, TSS, and AUC values. The distribution of suitable habitats for these two species is significantly affected by climatic temperature and precipitation. There is a significant difference between the potential habitats of these two species. Gm and Gq are distributed in the northeastern boundary area and the central and eastern areas of the QTP, respectively. The areas of their suitable habitats are significantly and positively correlated with the area of grassland among all land use types of QTP, with no correlations with the areas of other land use types of QTP. The potential habitats of both species during the paleoclimate period were located in the eastern and southeastern boundary areas of the QTP. During the paleoclimate period, their potential habitats expanded towards the Hengduan Mountains (low-latitude regions) in the south compared with their current suitable habitats. With the subsequent temperature rising, their distribution centers shifted towards the northeast (high-latitude) regions, which could validate the hypothesis that the Hengduan Mountains were refuges for these species during the glacial period. In the future, there will be more potential suitable habitats for these two species in the QTP. This study elucidates the ecological factors affecting the current distribution of these grass caterpillars, provides an important reference for designating the prevention and control areas for Gm and Gq, and helps protect the alpine meadow ecosystem in the region.

Characteristics of Spatiotemporal Changes in China's Carbon Budget at Different Administrative Scales

Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of "double carbon" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales （provinces, cities, and counties） in China. The results showed that： ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of "high in the north and low in the south, high in the east and low in the west." ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows： In the spatial pattern of "hot in the east and cold in the west," the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that： ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions （such as different provinces） and lower-level administrative regions at another scale （such as different cities in the same province） showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination between provinces, which is expected to better promote the implementation of relevant policies.

Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset

Remote sensing and process-coupled ecological models are widely used for the simulation of GPP, which plays a key role in estimating and monitoring terrestrial ecosystem productivity. However, most such models do not differentiate the C3 and C4 photosynthetic pathways and neglect the effect of nitrogen content on Vmax and Jmax, leading to considerable bias in the estimation of gross primary productivity (GPP). Here, we developed a model driven by the leaf area index, climate, and atmospheric CO2 concentration to estimate global GPP with a spatial resolution of 0.1° and a temporal interval of 1 day from 2000 to 2022. We validated our model with ground-based GPP measurements at 128 flux tower sites, which yielded an accuracy of 72.3%. We found that the global GPP ranged from 116.4 PgCyear−1 to 133.94 PgCyear−1 from 2000 to 2022, with an average of 125.93 PgCyear−1. We also found that the global GPP showed an increasing trend of 0.548 PgCyear−1 during the study period. Further analyses using the structure equation model showed that atmospheric CO2 concentration and air temperature were the main drivers of the global GPP changes, total associations of 0.853 and 0.75, respectively, while precipitation represented a minor but negative contribution to global GPP.

Anthropogenic and climate change-driven coastline dynamics will erode future nesting habitats of the kentish plover on the central adriatic coast

Shorebirds play a crucial role in assessing the health of coastal ecosystems due to their life history, behaviour, migratory patterns, and feeding preferences. Many shorebird species are experiencing population declines worldwide, driven by habitat loss and climate change. Understanding these challenges requires extensive data on their distribution and breeding ecology. The Kentish Plover (Anarhynchus alexandrinus) is a small shorebird that constructs its nests on sandy beaches. However, there is a scarcity of data regarding the reproductive ecology of this species in many areas, including the Molise region of Southern Italy. This study aimed at assessing the potential role of environmental variables derived from remote sensing to model current and future Kentish Plover nesting habitat suitability accounting for future scenarios of coastal dynamics in 2040. Data on Kentish Plover nests were collected along the Molise coast over several years and used to calibrate ecological niche models (ENMs) relying on environmental variables derived from coastal images. Kentish Plover nesting habitat suitability was mostly affected by distance from open sand, artificial surfaces, shoreline, and herbaceous vegetation and forested areas. The study predicts an average decline of more than 22% in suitable nesting environments for the Kentish Plover within the next two decades. Results indicated that our modelling approach can offer valuable insights for the conservation strategy of Kentish Plover in the region. In conclusion, we assert that preserving the nesting habitat of the Kentish Plover will not only safeguard this species, but also other species that inhabit similar environments, along with providing protection for coastal landscapes and associated ecosystem services.

Emerging Adults’ Experiences of Dating Violence: A Qualitative Exploration

ABSTRACT Dating violence is a significant issue among emerging adults. Using Bronfenbrenner’s ecological model, this study investigates its precursors through interviews with 21 individuals aged 18–25 who experienced dating abuse. By applying the social-ecological model, this study underscores the complexity of dating violence, highlighting the necessity of addressing it through a multifaceted approach. Four main themes emerged: personal experiences of dating violence, precursors to violence, technology’s impact, and coping strategies. Psychological violence, particularly controlling behavior, being most common. Findings highlight the importance of individual and relational factors, social networks, and media influence. Overall, a comprehensive approach integrating social support, professional intervention, and societal changes seem to be essential.

Impact of short-term total dissolved gas supersaturation on cognitive function and swimming performance in medaka (Oryzias latipes)

During the flood season, high dam discharge rates result in total dissolved gas (TDG) supersaturation. This condition causes gas bubble trauma and can lead to fish mortality, which poses a significant threat to downstream river ecosystems. Assessing the ecological risks of TDG supersaturation is a challenge in waterpower-intensive river basins worldwide. Few studies have explored the impact of TDG supersaturation on fish behaviours, such as aggression and memory, which are crucial for feeding, reproduction, and predator avoidance. In this study, behavioural tests were conducted in a T-maze to investigate the effects of acute TDG supersaturation on swimming behaviour, aggression, and memory in medaka (Oryzias latipes). The results demonstrated that medaka exposed to TDG levels of 115% and 130% for 2 h had significantly reduced swimming performance.At TDG levels of 100%, 115% and 130%, medaka activity rates in the mirror arm of the maze in the mirror test were 44.34 ± 12.88%, 40.27 ± 15.44% and 35.35 ± 16.07%, respectively. Similarly, the activity rates of medaka in the active stimulus arm of the maze in the memory test were 50.35 ± 14.75%, 40.76 ± 12.51% and 35.35 ± 18.47%, respectively. The behaviour of medaka changed with increasing TDG supersaturation. These findings contribute to the development of an ecological risk assessment model for TDG supersaturation based on memory and aggression in fish and provide data for developing management strategies to mitigate the adverse effects of TDG supersaturation.

Herbicide‐resistant weed management with robots: A weed ecological–economic model

AbstractThe heavy reliance on herbicides for weed control has led to an increase in resistant weeds in the United States. Robotic weed control is emerging as an alternative technology for removing weeds mechanically using artificial intelligence. We develop an integrated weed ecological and economic dynamic (I‐WEED) model to examine the biophysical and economic drivers of adopting robotic weed management and simulate the optimal timing and intensity of robotic adoption within and across growing seasons. We specify a cohort‐based weed growth model that relates yield damages to effective weed density and treats the susceptibility of weeds to herbicides as a renewable resource that can be regenerated by using mechanical weeding robots, due to a fitness cost that makes resistant weeds less prolific. Compared to myopic weed management which ignores resistance development, forward‐looking management leads to earlier adoption of robots and treating robots as complements instead of substitutes to herbicides. This weed management results in adopting fewer robots, deploying robots on a smaller portion of the land, higher profitability, and lower yield loss in the long run, relative to myopic management. Counterintuitively, myopic management leads to a lower resistance level through its higher robot adoption intensity. We also find that a lower level of initial weed seed resistance and/or a higher fitness cost result in a higher level of resistance because they create incentives for farmers to delay the adoption of robotic weed control. Our analysis shows the importance of jointly considering the interactions between weed ecology and economics in analyzing the incentives and effects of robotic weed management on weed resistance.

Translating macroecological models to predict microbial establishment probability in an agricultural inoculant introduction

The use of potentially beneficial microorganisms in agriculture (microbial inoculants) has rapidly accelerated in recent years. For microbial inoculants to be effective as agricultural tools, these organisms must be able to survive and persist in novel environments while not destabilizing the resident community or spilling over into adjacent natural ecosystems. Despite the importance of propagule pressure to species introductions, few tools exist in microbial ecology to predict the outcomes of agricultural microbial introductions. Here, we adapt a macroecological propagule pressure model to a microbial scale and present an experimental approach for testing the role of propagule pressure in microbial inoculant introductions. We experimentally determined the risk-release relationship for an IAA-expressing Pseudomonas simiae inoculant in a model monocot system. We then used this relationship to simulate establishment outcomes under a range of application frequencies (propagule number) and inoculant concentrations (propagule size). Our simulations show that repeated inoculant applications may increase establishment, even when increased inoculant concentration does not alter establishment probabilities. Applying ecological modeling approaches like those presented here to microbial inoculants may aid their sustainable use and provide a monitoring tool for microbial inoculants.

Spinoza, Liberation From Causation, and Community Health Promotion.

What sense does it make to say that a new program implemented in a community with roots as old as evolution caused an observed health benefit? Evaluation of community approaches has often sought to isolate the causal roles of interventions. Central to this is the assumption that there are causes to be proven and isolated. Benedict Spinoza (1632-1677) dismissed the concept of cause, arguing that all things, "substances," are not caused but simply are. Actions of things in nature can influence each other, e.g., erosion of a mountain, but their substance, the mountains simply are. For Spinoza, satisfaction in life comes from realizing and acting in accord with our substance, but this requires communities that support such realization and action. Thus, communities and the vast influences they contain are central to human welfare. Interventions within them do not cause benefits but join with the history, culture, and numerous other features of the community in becoming part of how the community influences its members. Implications include a) expanding the social ecological model fully to embrace multiple influences - including innovative programs - and interactions among them, and c) varied research methods to identify practical lessons about how communities may adopt and incorporate innovations to engender change, rather than a catalogue of interventions that are supposed to change them.

Transferability of ecological forecasting models to novel biotic conditions in a long-term experimental study.

Ecological forecasting models play an increasingly important role for managing natural resources and assessing our fundamental knowledge of processes driving ecological dynamics. As global environmental change pushes ecosystems beyond their historical conditions, the utility of these models may depend on their transferability to novel conditions. Because species interactions can alter resource use, timing of reproduction, and other aspects of a species' realized niche, changes in biotic conditions, which can arise from community reorganization events in response to environmental change, have the potential to impact model transferability. Using a long-term experiment on desert rodents, we assessed model transferability under novel biotic conditions to better understand the limitations of ecological forecasting. We show that ecological forecasts can be less accurate when the models generating them are transferred to novel biotic conditions and that the extent of model transferability can depend on the species being forecast. We also demonstrate the importance of incorporating uncertainty into forecast evaluation with transferred models generating less accurate and more uncertain forecasts. These results suggest that how a species perceives its competitive landscape can influence model transferability and that when uncertainties are properly accounted for, transferred models may still be appropriate for decision making. Assessing the extent of the transferability of forecasting models is a crucial step to increase our understanding of the limitations of ecological forecasts.

An ecological niche model that considers local relationships among variables: The Environmental String Model

AbstractMany methods have been proposed to model the spatial distribution of a species. While some methods have been specifically designed for this purpose, others are well‐known statistical tools that can be used in many scientific fields. In this paper, I propose a new ecological niche model, called the Environmental String Model (ESM), that is based on the concept of environmental string, which is defined as being a combination of environmental variables, with as many nodes as environmental variables. There are two types of environmental strings: (1) the abundance‐known string and (2) the abundance‐unknown string (or target string) for which an estimation of abundance is searched. The novelty of the model is that it assesses the abundance associated with a target string from nearby abundance‐known strings, which preserve the local multidimensional relationships with the target string. The model does not provide an abundance estimate in the absence of data from a similar environment and it can therefore deal with truncated spatial distributions or niches. It is tested in the North Atlantic Ocean on two key copepod species, Calanus finmarchicus and Calanus helgolandicus, which have been monitored by the Continuous Plankton Recorder (CPR) survey for decades. I investigate the influence of variables on model performance. I show that the model reconstructs the mean spatial distribution and seasonal fluctuations in both Calanus well. When compared with generalized linear models (GLMs), generalized additive models (GAMs) and generalized regression neural network (GRNN), the ESM gives the best performance. I propose a number of indicators to evaluate the robustness of estimated abundance in space and time and show how the model may be extended to presence/absence or presence‐only data. I think that the ESM could be used to fill gaps in any sampling program such as the CPR survey and many satellite databases (e.g., ocean color and photosynthetically active radiation).

Genetic Structure of Monochamus alternatus (Hope) in Qinling-Daba Mountains and Expansion Trend: Implications for Pest Prevention and Management.

Pine wilt disease (PWD), caused by Bursaphelenchus xylophilus, severely threatens global pine forests. Monochamus alternatus is the primary vector of B. xylophilus in East Asia. Understanding the population structure and evolutionary forces of vector insects is critical for establishing effective PWD management strategies. The present work explores the genetic structure and phylogenetic relationships of 20 populations of M. alternatus from the Qinling-Daba Mountains (QDM) in China using the mitochondria DNA dataset, supplemented by ecological niche modeling (ENM). All M. alternatus populations were categorized into three phylogeographic clusters (Clade A, Clade B, and Clade C), with Clade A and Clade B corresponding to the western and eastern QDM, respectively. The results of divergence time estimation concur with environmental changes induced by Quaternary glacial climate oscillations in QDM of China. M. alternatus populations exhibited significant genetic differentiation, with expansion in their population size. Ecological niche modeling (ENM) demonstrated that precipitation and temperature significantly influence the distribution of M. alternatus and the species is anticipated to grow into higher latitude and higher altitude regions in the future. In a nutshell, exploring the genetic structure and evolutionary dynamics of M. alternatus can provide valuable insights into the prevention and occurrence of B. xylophilus. These findings also serve as a reference for research on population differentiation and phylogeography of other species in QDM and adjacent areas.