Ecological Processes Research Articles

Stepwise Construction and Integration of Ecological Network in Resource-Based Regions: A Case Study on Liaoning Province, China

Ecological networks are an effective strategy to maintain regional ecological security. However, current research on ecological network construction in areas with large-scale resource extraction is limited. Moreover, classic ecological network construction methods do not perform satisfactorily when implemented in heavily damaged mining landscapes. Taking the example of Liaoning Province, China, a framework for stepwise renewal of ecological networks was proposed, which integrates basic ecological sources and other sources that include mining areas. The framework was based on multi-source ecological environment monitoring data, and all potential ecological sources were extracted and screened using an MSPA model and the area threshold method. Further, ecological sources were classified into two types and three levels based on the influence of abandoned mines and the characteristics of ecosystem services in the ecological sources. Ecological corridors were extracted using the MCR model. An ecological corridor optimization process based on combining the gravity model with addition and removal rules of corridors was proposed. The results indicated that the basic ecological network in Liaoning Province included 101 ecological sources and 162 ecological corridors, and the supplementary ecological network included 28 ecological sources and 67 ecological corridors. The ecological sources were divided into two types, and corridors were divided into three types. The basic ecological network exhibited a spatial distribution of discrete connections in the west and close connections in the east. Changes in ecological network topological indicators indicated that a supplementary ecological network strengthened the structural performance of the regional ecological network, expanding spatial coverage, filling hollow areas, and enriching local details of the regional ecological network. Regulation strategies were proposed for ecological sources with different connection modes. The number of ecological sources implementing restrictive development, pattern optimization, and protective development were 101, 12, and 16, respectively. This paper provides a constructing framework of ecological networks adapted for resource-based regions. This method can support decisions for the environmental governance of mines, thus contributing to a balance between resource exploitation and ecological protection in regions.

Spatial asymmetry of temporal ecological processes can shift in riverine macroinvertebrates responding to fluctuating climate conditions

Exploring the temporal dynamics of biological communities can offer valuable insights into the underlying mechanisms driving changes in biodiversity in the context of short and long-term effects of climate fluctuations. However, an understanding of how temporal shifts in climatic fluctuations influence the spatial patterns of the temporary ecological processes remains unexplored. This study examined the relative importance of temporary deterministic and stochastic processes (i.e., the influence of environmental filtering compared to stochastic variation within the same community) on community dynamics across watersheds in 15 rivers of the European Iberian Peninsula using 21 years of data. This study was divided into two time periods (i.e., 1997–2006 and 2007–2017). The climatic differences between the periods included decreasing levels and heightened variability of precipitation. Additionally, there were declining minimum temperatures and rising maximum temperatures, accompanied by reduced fluctuations in both minimum and maximum temperatures. Water quality and its variations also occur along an elevation pattern and changed over the time period studied. Spatial patterns of the relative importance of the ecological processes shifted between the two decades. The significance of stochastic processes increased with elevation in the earlier period, although no clear elevation pattern emerged in the later period. At the same time, the importance of deterministic processes decreased with elevation in the earlier period, and there was no clear pattern of elevation in the later period. An understanding of the patterns in community dynamics existing at various elevations over time can lay the groundwork for predicting and mitigating the impacts of short-term climate changes on biodiversity and guide appropriate conservation actions.

Integrating AI enhanced remote sensing technologies with IOT networks for precision environmental monitoring and predicative ecosystem management

Detection of hazardous substances in the environment is paramount in safeguarding human health and ecosystems. With the continuous advancement of technology, artificial intelligence (AI) has emerged as a promising tool in the development of sensors capable of efficiently detecting and analyzing these substances. Environmental monitoring, modeling, and management are very essential for gaining a deeper insight into the fundamental processes and methodologies employed in handling environmental transformations. Hence, the objective of this study is to investigate recent progress in the utilization of AI, sensors, and IoT devices for monitoring environmental pollution, while considering the challenges associated with predicting and monitoring these variations due to the dynamic nature of the environment. The integration of these systems is actively revolutionizing environmental monitoring and enhancing our understanding of how to implement a comprehensive approach to the management of natural resources and ecological processes that are crucial for our societal, economic, and cultural well-being. Consequently, we are able to uncover the transformative impact of this collaborative effort on our comprehension of Earth, as it tackles obstacles, conducts in-depth analysis of long-term environmental data monitoring, and lays the foundation for a promising future.

Multiple habitat graphs: how connectivity brings forth landscape ecological processes

PurposeHabitat connectivity is integral to current biodiversity science and conservation strategies. Originally, the connectivity concept stressed the role of individual movements for landscape-scale processes. Connectivity determines whether populations can survive in sub-optimal patches (i.e., source-sink effects), complete life cycles relying on different habitat types (i.e., landscape complementation), and benefit from supplementary resources distributed over the landscape (i.e., landscape supplementation). Although the past decades have witnessed major improvements in habitat connectivity modeling, most approaches have yet to consider the multiplicity of habitat types that a species can benefit from. Without doing so, connectivity analyses potentially fail to meet one of their fundamental purposes: revealing how complex individual movements lead to landscape-scale ecological processes.MethodsTo bridge this conceptual and methodological gap, we propose to include multiple habitat types in spatial graph models of habitat connectivity, where nodes traditionally represent a single habitat type. Multiple habitat graphs will improve how we model connectivity and related landscape ecological processes, and how they are impacted by land cover changes.ResultsIn three case studies, we use these graphs to model (i) source-sink effects, (ii) landscape supplementation, and (iii) complementation processes, in urban ecosystems, agricultural landscapes, and amphibian habitat networks, respectively. A new version of the Graphab open-source software implements the proposed approach.ConclusionMultiple habitat graphs help address crucial conservation challenges (e.g., urban sprawl, biological control, climate change) by representing more accurately the dynamics of populations, communities, and their interactions. Our approach thereby extends the ecologist’s toolbox and aims at fostering the alignment between landscape ecology theory and practice.

Bridging ecological processes to diversity formation and functional profiles in belowground bacterial communities

Revealing the generation and maintenance of biodiversity is a central goal in ecology, but how dispersal, selection, and regional taxon pool size shape soil microbial communities is not well understood. Here, we examined how dispersal and environmental selection affected soil bacterial diversity and their related metabolic functions by leveraging large-scale cross-biome soil surveys of ∼1400 samples from diverse ecosystems across China, including agricultural, forest, grassland, and wetland soils. Our results showed that high dispersal increased α-diversity and decreased β-diversity, whereas strong selection generated the opposite pattern in various ecosystems. This is likely due to dispersal enabling species access to otherwise unreachable habitats, and environmental selection excluding non-adapted species from communities. The α-diversity increased with γ-diversity, whereas β-diversity did not covary. We also showed that bacterial phylotypes positively associated with dispersal and selection exhibited distinct metabolic diversity. Dispersal-induced phylotypes, which were abundant in agricultural soils, exhibited more metabolic diversity in fructose and mannose, starch and sucrose, and nitrogen metabolism. Conversely, selection-induced phylotypes, dominated in wetland soils, were primarily associated with sulfur and methane metabolism. In addition, the complexity of taxon associations increased when communities had higher selection increasing β-diversity. Our study establishes the predictive links of ecological processes to microbial diversity, metabolic functions, and taxon coexistence, thus facilitating a better understanding of the mechanisms underlying biodiversity generation and conservation.

Ecologically Regenerative Building Systems through Exergy Efficiency: Designing for Structural Order and Ecosystem Services

Regenerative design is being increasingly explored in urban environments to counteract and adapt to the changing climate and degradation of ecosystems. A critical success factor for the implementation of regenerative design is the evaluation of urban and building systems in relation to ecological performance and benefits. In biological ecosystems, the availability of high-quality energy, called exergy, and structural order can be used as indicators of the efficiency of on-going ecological processes. Structural order refers to the organization and systematic arrangements of biotic and abiotic elements within an ecosystem based on the available space and interactions with the goal to form a functional system. Ecological processes use the available exergy and generate ecosystem services (ESs) upon which human survival and that of other living organisms depend. In this article, structural order and ESs generation are proposed as indicators for exergy efficiency and accumulation in building systems, respectively, which can evaluate to what extent they are ecologically functional and regenerative. Based on this insight, design strategies are derived from the functioning of ecosystems that describe how buildings could become habitats that host living, non-living, and hybrid systems with optimized thermodynamic efficiency and that can generate ESs. This research suggests that when buildings improve structural order (an ecological concept) and implement ESs generating processes similar to biological ecosystems, they can facilitate regenerative processes more effectively that consume and generate resources and, with this, destroy but also accumulate exergy.

Phosphorus resource partitioning underpins diversity patterns and assembly processes of microbial communities in plateau karst lakes

Eutrophication triggered by internal phosphorus (P) poses a substantial threat to the biodiversity of organisms in freshwater ecosystems. However, little is known about the linkages between P resource partitioning and microbial succession, especially in karst sediments. Here, we studied the diversity patterns and assembly processes of bacterial and archaeal communities in sediment cores from two historically hyper-eutrophicated karst lakes, Hongfeng Lake and Aha Lake, and investigated the relative contribution of P fractions to them. Our null and neutral models consistently indicated that bacterial and archaeal community assembly was judged to be deterministic rather than stochastic. We found a monotonically decreasing pattern for bacterial Shannon diversity toward deep sediments in Aha Lake, but U- or hump-shaped patterns for archaea in Hongfeng and Aha Lakes. Intriguingly, the community dissimilarity Bray–Curtis of bacteria and archaea consistently increased with increasing depth distance, with slopes of 0.0080 and 0.0069 in Hongfeng Lake and 0.0078 and 0.0087 in Aha Lake, respectively. Such cross-taxon congruence was well-supported by equivalent ecological processes (i.e., environmental selection). For bacteria and archaea, Shannon diversity was primarily affected by the total P (TP) fractions such as the loosely adsorbed TP or calcium-bound TP and sediment TP. Their community composition was significantly (P < 0.05) affected by calcium-bound inorganic P (Pi), loosely adsorbed Pi and reductant-soluble Pi. Although sediment properties were important, bacterial and archaeal diversity or community composition were well-explained by the Pi fractions, with high direct or indirect effects. In particular, Pi fractions exhibited stronger effects on bacterial and archaeal characteristics than organic P fractions. Taken together, our study provides novel insights into the ecological importance of P resource partitioning to microbial succession, which has crucial implications for disentangling the biogeochemical processes of P cycling in aquatic ecosystems.

Spatial Correlation of Landscape Fragmentation and Ecological Sensitivity in China’s Giant Panda National Park and Surrounding Areas

The Giant Panda National Park (GPNP) and its surrounding areas constitute a comprehensive ecosystem aimed at protecting the natural habitat of giant pandas, maintaining biodiversity, and ensuring ecological balance. Investigating the spatial correlation between landscape pattern indices and ecological sensitivity (ES) in this area is a crucial step in the construction of ecological civilization and contributes significantly to ecological conservation, restoration, and environmental management. This study utilized Geographic Information Systems (GIS) and Fragstats software to select nine ecological evaluation factors and four landscape pattern indices to comprehensively evaluate the ES and landscape patterns of the GPNP and its surrounding areas. This study discovered that the ecological sensitivity of the GPNP is substantially higher than that of the neighboring areas, with the northern Qionglai Mountain area and the western Minshan area showing the highest concentrations of exceptionally high sensitivity. Highly sensitive areas account for 35.22% of the study region, concentrated in areas within the national park, except the Qinling area, as well as the western and southern surrounding areas. The distribution of moderately sensitive areas is more uniform, while low and insensitive areas are found primarily in the northern and eastern areas, along with the national park’s environs. Patch density (PD) within the GPNP is lower than in surrounding areas, with higher PD in the northern and central parts. The landscape division index (DIVISION) decreases from west to east, and the landscape disturbance index (LDI) is significantly lower within the national park than in surrounding areas, with small areas of high LDI in the entire study region. Moran’s index analysis of the GPNP and its surrounding areas shows that ecological sensitivity is positively correlated with landscape pattern indices (PD, SPLIT, DIVISION, and LDI), with the strongest correlation between DIVISION and ecological sensitivity. Spatially, the internal areas of the national park have lower landscape pattern indices but higher ecological sensitivity, while the eastern region exhibits severe landscape fragmentation. Major clusters of high and low values are found around the Qionglai-Daxiangling area, indicating that these areas of high ecological sensitivity have complex landscape structures, numerous habitat edges, and significant impacts on biodiversity and ecological processes. Overall, the areas surrounding the GPNP exhibit lower ecological sensitivity levels and higher landscape fragmentation, emphasizing the need for focused ecological protection in the northern part of the QLS region and the western part of the MS region. Additionally, attention should be given to the impact of landscape fragmentation in the surrounding areas in the interior of the GPNP. These results provide scientific evidence for the sustainable development of the GPNP and its surrounding areas.

Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data

Abstract. Land surface temperature (LST) serves as a crucial variable in characterizing climatological, agricultural, ecological, and hydrological processes. Thermal infrared (TIR) remote sensing provides high temporal and spatial resolutions for obtaining LST information. Nevertheless, TIR-based satellite LST products frequently exhibit missing values due to cloud interference. Prior research on estimating all-weather instantaneous LST has predominantly concentrated on regional or continental scales. This study involved generating a global all-weather instantaneous and daily mean LST product spanning from 2000 to 2020 using XGBoost. Multisource data, including Moderate-Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) observations, surface radiation products, and reanalysis data, were employed. Validation using an independent dataset of 77 individual stations demonstrated the high accuracy of our products, yielding root mean squared errors (RMSEs) of 2.787 K (instantaneous) and 2.175 K (daily). The RMSE for clear-sky conditions was 2.614 K for the instantaneous product, which is slightly lower than the cloudy-sky RMSE of 2.931 K. Our instantaneous and daily mean LST products exhibit higher accuracy compared to the MODIS official LST product (instantaneous RMSE = 3.583 K; daily 3.105 K) and the land component of the fifth generation of the European ReAnalysis (ERA5-Land) LST product (instantaneous RMSE = 4.048 K; daily 2.988 K). Significant improvements are observed in our LST product, notably at high latitudes, compared to the official MODIS LST product. The LST dataset from 2000 to 2020 at the monthly scale, the daily mean LST on the first day of 2010 can be freely downloaded from https://doi.org/10.5281/zenodo.4292068 (Li et al., 2024), and the complete product will be available at https://glass-product.bnu.edu.cn/ (last access: 22 August 2024).

Dispersal limitation determines the ecological processes that regulate the seasonal assembly of bacterial communities in a subtropical river.

Bacteria play a crucial role in pollutant degradation, biogeochemical cycling, and energy flow within river ecosystems. However, the underlying mechanisms governing bacterial community assembly and their response to environmental factors at seasonal scales in subtropical rivers remain poorly understood. In this study, we conducted 16S rRNA gene amplicon sequencing on water samples from the Liuxi River to investigate the composition, assembly processes, and co-occurrence relationships of bacterial communities during the wet season and dry season. The results demonstrated that seasonal differences in hydrochemistry significantly influenced the composition of bacterial communities. A more heterogeneous community structure and increased alpha diversity were observed during the dry season. Water temperature emerged as the primary driver for seasonal changes in bacterial communities. Dispersal limitation predominantly governed community assembly, however, during the dry season, its contribution increased due to decreased immigration rates. Co-occurrence network analysis reveals that mutualism played a prevailing role in shaping bacterial community structure. Compared to the wet season, the network of bacterial communities exhibited higher modularity, competition, and keystone species during the dry season, resulting in a more stable community structure. Although keystone species displayed distinct seasonal variations, Proteobacteria and Actinobacteria were consistently abundant keystone species maintaining network structure in both seasons. Our findings provide insights into how bacterial communities respond to seasonal environmental changes, uncovering underlying mechanisms governing community assembly in subtropical rivers, which are crucial for the effective management and conservation of riverine ecosystems.

Graphene oxide inhibits the transfer of ARGs in rice by reducing the root endophytic bacterial complexity

Antibiotic resistance genes (ARGs) as an emerging contaminant have attracted much attention for their transfer in agricultural ecosystems. Meanwhile, graphene oxide (GO), due to its high adsorption capacity and antibacterial properties, poses potential environmental ecological risks to the occurrence of ARGs, bacteria, and plant physiological ecology. However, the impact and mechanism of GO on the transfer of ARGs in host plants remain unclear. Therefore, this study selected rice as the research object and inoculated Bacillus subtilis carrying ARGs to investigate the influence of GO on the migration of ARGs into rice and its microbiological mechanism. The study found that GO had a certain inhibitory effect on the transfer of ARGs in rice. Although GO reduced the rhizosphere pH in rice, leading to a transition in endophytic bacteria from dominance by Burkholderia to dominance by Gordonia, this process did not directly affect the transfer of ARGs in rice. Further analysis of bacterial interactions revealed that GO could inhibit the transfer of ARGs in rice by reducing the network complexity of endophytic bacteria. Additionally, GO inhibited the formation of endophytic bacterial biofilms and mobile elements, which might affect ARGs’ migration in rice. This study elucidated the key microbiological ecological processes of GO on the transfer of ARGs in rice, providing fundamental information for the ecological risk assessment of GO.

Ecological function maintained despite mesomammal declines

Mid-sized mammals (i.e., mesomammals) fulfill important ecological roles, serving as essential scavengers, predators, pollinators, and seed dispersers in the ecosystems they inhabit. Consequently, declines in mesomammal populations have the potential to alter ecological processes and fundamentally change ecosystems. However, ecosystems characterized by high functional redundancy, where multiple species can fulfil similar ecological roles, may be less impacted by the loss of mesomammals and other vertebrates. The Greater Everglades Ecosystem in southern Florida is a historically biodiverse region that has recently been impacted by multiple anthropogenic threats, most notably the introduction of the Burmese python (Python molurus bivittatus). Since pythons became established, mesomammal populations have become greatly reduced. To assess whether these declines in mesomammals have affected two critical ecosystem functions—scavenging and frugivory—we conducted experiments in areas where mesomammals were present and absent. We did not observe significant differences in scavenging or frugivory efficiency in areas with and without mesomammals, but we did observe significant differences in the communities responsible for scavenging and frugivory. Despite the observed evidence of redundancy, the changes in community composition could potentially lead to indirect consequences on processes like seed dispersal and disease dynamics within this ecosystem, emphasizing the need for further study.

Diversity patterns and ecological assembly mechanisms of bacterial communities in the northeastern Indian Ocean epipelagic waters during the northeast monsoon

Disentangling microbial community diversity patterns and assembly mechanisms is critical for understanding ecological processes and evaluating biogeochemical cycling in ecosystems. However, the diversity patterns and assembly mechanism of the microbial communities in the epipelagic waters in the northeastern Indian Ocean (NEIO) on the spatial scale are still unclear. In this study, we investigated the spatial dynamics, geographic distribution pattern, and assembly process of the bacterial community using 532 samples collected from the epipelagic waters in the NEIO during the northeast monsoon. The results indicate that the bacterial richness and Bray-Curtis dissimilarity exhibited the strongest correlations with depth compared to the latitudinal and longitudinal scales. The dissolved oxygen was identified as the most important environmental factor affecting the bacterial richness and Bray-Curtis dissimilarity compared to temperature and salinity. The distance–decay relationship (DDR) of the bacterial community strengthened with increasing water depth. Turnover was the predominant β-diversity component influencing the spatial changes in the whole bacterial community. The dispersal limitation of the stochastic process and homogeneous selection of the deterministic process governed the bacterial ecological assembly process of the whole bacterial community. Abundant and rare subcommunities differed in terms of the niche breath, composition changes. The abundant subcommunities exhibited a much wider niche breath than the rare subcommunities. Regarding the abundant subcommunity species changes, the contributions of the turnover and nestedness varied with the water depth and oceanic region. In contrast, turnover was the major β-diversity component regarding the changes in the rare species. These data improve our understanding of the ecological processes of bacterial community assemblages in the NEIO.

Revisiting evapotranspiration inputs in eco-hydrological modeling for climate change assessment

Evapotranspiration (ET) is an essential variable linking hydrological and ecological processes and is typically modeled as a function of potential evapotranspiration and soil moisture in traditional hydrological models. However, commonly used empirical ET models typically do not recognize the underlying vegetation dynamics. This can have implications when models are extrapolated under future climate change. In this study, the traditional HYMOD-BVM (THV) eco-hydrological model is adopted as a benchmark model. A modified HYMOD-BVM (MHV) is developed using an actual ET substitute for the traditional PET input to consider vegetation dynamics under climate change. The THV and MHV models are compared to evaluate how streamflow (Q) and leaf area index (LAI) vary under future climate in the Florentine River (FR, energy-limited) catchment and Murray River (MR, water-limited) catchment in Australia. Six global climate models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP6) are bias-corrected and employed in the calibrated THV and MHV models, and ensemble mean results are analyzed. Results suggest that the streamflow projected by the MHV model tends to be higher than that from the THV model, while LAI presents an opposite trend. The energy-limited catchment appears more susceptible to climate change whereas larger vegetation effects are seen in the water-limited catchment. Overall, our research highlights the effects of evapotranspiration on future climate change scenario analysis and prompts the need for the development of spatial and temporal continuously accurate ET models for both current and future climates.

Forest plant indicator values for moisture reflect atmospheric vapour pressure deficit rather than soil water content.

Soil moisture shapes ecological patterns and processes, but it is difficult to continuously measure soil moisture variability across the landscape. To overcome these limitations, soil moisture is often bioindicated using community-weighted means of the Ellenberg indicator values of vascular plant species. However, the ecology and distribution of plant species reflect soil water supply as well as atmospheric water demand. Therefore, we hypothesized that Ellenberg moisture values can also reflect atmospheric water demand expressed as a vapour pressure deficit (VPD). To test this hypothesis, we disentangled the relationships among soil water content, atmospheric vapour pressure deficit, and Ellenberg moisture values in the understory plant communities of temperate broadleaved forests in central Europe. Ellenberg moisture values reflected atmospheric VPD rather than soil water content consistently across local, landscape, and regional spatial scales, regardless of vegetation plot size, depth as well as method of soil moisture measurement. Using in situ microclimate measurements, we discovered that forest plant indicator values for moisture reflect an atmospheric VPD rather than soil water content. Many ecological patterns and processes correlated with Ellenberg moisture values and previously attributed to soil water supply are thus more likely driven by atmospheric water demand.

A novel AMSR2 retrieval algorithm for global C-band vegetation optical depth and soil moisture (AMSR2 IB): Parameters' calibration, evaluation and inter-comparison

Effective monitoring of soil and vegetation properties on a global scale is essential for better understanding climate changes, hydrological dynamics, and ecological processes. Passive microwave remote sensing at C-band radio frequency, with long observation period and relatively high penetration capability, has been widely used to retrieve soil moisture (SM) and vegetation optical depth (C-VOD). The retrieval process is generally achieved by inversion of the τ-ω radiative transfer model, which depends on crucial parameters such as effective scattering albedo (ω) and soil roughness (HR) for accurate retrievals. Current SM/C-VOD retrieval algorithms, such as the Land Parameter Retrieval Model (LPRM), predominantly rely on globally-constant ω and HR values, ignoring the inherent sensitivity of those parameters to varying soil conditions and vegetation types. To evaluate the impact of ω and HR variables on SM and C-VOD retrievals and to improve their accuracy, this study proposed and evaluated a novel retrieval approach from AMSR2 C-band observations during 2017–2020 using the C-band Microwave Emission of the Biosphere (C-MEB) model. We evaluated two new retrieval algorithms, considering either a globally-constant calibration or a land cover-based calibration of ω and HR. As a benchmark for the calibration, we optimized the values of ω and HR by evaluating the retrieved SM against in situ measurements from the International Soil Moisture Network (ISMN) and OzNet hydrological monitoring networks. The main originality compared to previous algorithms is that i) it includes a comprehensive calibration exploring the optimal values of ω and HR, applicable globally or tailored to specific land cover; ii) field SM measurements were leveraged to constrain the calibrated value of ω and HR.For the globally-constant calibration, the optimal values of ω = 0.05 and HR = 0.1 were found to yield the best results. For the land cover-based calibration, an inverse relationship between ω/HR and canopy height was observed, with ω ranging from 0.04 to 0.06 and HR ranging from 0.1 to 0.7 for heights between 0 and 30 m. The algorithm employing a land cover-based calibration (INRAE Bordeaux 2, IB2) exhibited better performance than the one utilizing a globally-constant calibration (INRAE Bordeaux 1, IB1) in evaluating retrieved SM against in situ measurements, as well as in evaluating C-VOD vs various vegetation variables including aboveground biomass (AGB), tree cover, canopy height and several optical vegetation indices. Comparison with LPRM suggested that our IB2 C-VOD retrievals present improved performances in terms of both spatial and temporal results with all considered vegetation variables (spatial correlation (R) between various vegetation variables and C-VOD of 0.76–0.83 for IB2 vs 0.69–0.79 for LPRM), and exhibited lower saturation effects when compared with AGB. In addition, the IB2 SM produced lower root mean squared error (RMSE) (0.147 vs 0.217 m3/m3), bias (−0.03 vs 0.09 m3/m3), and ubRMSE (0.066 vs 0.067 m3/m3) when compared with in situ measurements, although it showed a lower R compared to LPRM SM.

The relative importance of local versus regional habitat structure variation on the abundance of two generalist mutualists along a forest disturbance gradient

Mutualistic interactions are key to biodiversity generation and maintenance, being pollination and seed dispersal interactions essential for plant reproduction. However, anthropogenic habitat disturbance can alter these interactions. We studied the regional and local effects of habitat disturbance on two generalist mutualist animals of southern Chile temperate rainforests: the hummingbird Sephanoides sephaniodes and the marsupial Dromiciops gliroides, which perform key roles as pollinator and seed disperser, respectively. We sampled 12 sites corresponding to four disturbance conditions (mature native forest, secondary forest, native forest under selective logging, and exotic forest plantations) in which we estimated the number of S. sephaniodes and D. gliroides records (as a proxy of relative abundance) using camera traps. We measured seven habitat structure variables at each site, known to influence their occurrence. Specifically, we examined S. sephaniodes and D. gliroides abundance variation at (i) a regional scale (among disturbance conditions) and (ii) at a local scale (among sampling sites). Dromiciops gliroides abundance decreased as disturbance increased, but S. sephaniodes abundance was highly variable. At the local scale, S. sephaniodes and D. gliroides abundances were largely variable among sites, influenced by habitat structural features, such as bamboo and shrub cover and woody debris. Our results show that although habitat disturbance may influence mutualist abundances, they can tolerate disturbance if minimum structure and resource requirements are met, but respond idiosyncratically to local conditions. Examining local-scale variability may provide valuable information on ecological processes, which often goes unnoticed when local sites are considered as replicates in landscape-level studies.

Multi-mission virtual monitoring station for streamflow monitoring and hydrodynamic model calibration

A comprehensive understanding of the streamflow dynamic along the river system is one of the significant components for preserving biodiversity and ensuring sustainable ecological processes. Understanding this requirement, streamflow estimation using remote sensing (RS) has evolved as an alternate approach in the hydrologic literature during the last decade due to its extensive spatiotemporal coverage. However, the existing RS-based approaches have limited applications for deriving the continuous time series in tropical river reaches due to narrow water widths during the low flow and frequent cloud covers during the high flow periods. Therefore, this study proposed frameworks to establish a virtual monitoring station (VMS) where multi-mission satellites are being used to derive continuous streamflow time series. From the multi-mission satellites, the optical RS images are used to develop a Copula-based fusion (CFUS) model by integrating the Frank copula with the 30m × 1-day resolution synthetic Landsat images, derived from the fusion of 250m × 1-day resolution MODIS images and 30m × 16-days resolution Landsat images; whereas the water levels are retrieved from the altimeters to derive discharge using the rating curve. Additionally, the potential utility of the established VMS for hydrodynamic model (MIKE11-NAM-HD) calibration under data-scarce conditions is also demonstrated. Finally, a coupled RS-hydrodynamic (RS-HD) framework is also proposed to establish VMS both at semi-gauged and ungauged sections of the rivers. The efficacy of the aforementioned framework was tested along the lower Brahmani river reach. The results reveal that the advocated framework could perform satisfactorily with the Nash-Sutcliffe efficiency (NSE) and Kling-Gupta efficiency (KGE) ≥0.8. This approach has the potential to be upscaled to other river reaches as one of the next-generation hydrometry for daily streamflow monitoring using high-frequent observation of multi-mission satellites.

Supralittoral isopod (Oniscidea) diversity at three ecoregions along the Colombian Caribbean: useful data for environmental management

Introduction: Terrestrial isopods (Oniscidea) play important roles in the ecological processes of the soil in tropical ecosystems and are employed as indicators of environmental impact. Despite their importance, studies on the ecology of this suborder in the Neotropics are scarce. Objective: To assess spatial changes in alpha and beta diversity of Oniscidea in the supralittoral zone across Archipiélagos Coralinos (ARCO), Magdalena (MAG), and Morrosquillo (MOR) ecoregions in the Colombian Caribbean. Methods: We conducted Direct Intuitive Searches of specimens and measured soil temperature and moisture in 19 transects with logs, leaf litter, coral remains, and decomposing plant material. Results: A total of 1 970 individuals representing 17 species were collected, with Tylidae, Halophilosciidae, and Ligiidae being the most abundant families. Alpha diversity orders were higher in ARCO than MAG and MOR ecoregions. MAG and MOR differed in observed richness. The structure of the assemblage varied in dominant species and abundances. In ARCO, the indicator species were Tylos niveus, Littorophiloscia denticulata, Halophiloscia trichoniscoides, and Ligia baudiniana; in MOR, it was Tylos marcuzzii, and in MAG, it was Littorophiloscia tropicalis. High beta diversity (&gt; 60 %), with significant differences in the assemblage structure among ecoregions, was confirmed by the NMDS, which distinctly separated each group. CCA analysis revealed a negative relationship between most species with soil temperature and moisture, with a positive relationship observed with T. marcuzzii. Conclusions: This is the first effort to describe spatial changes in the diversity of oniscideans in the supralittoral zone of the Neotropical region, providing a baseline for future studies. This information could be instrumental in identifying priority areas for conservation efforts.

Good modelling practice in ecology, the hierarchical Bayesian perspective

Ecological modelling often involves addressing challenges such as dependence in responses, e.g., spatial and/or temporal correlation, heterogeneity of variance, and hierarchical structures inherent in ecological processes and data. A constant challenge is the inadequacy of the data to well address the questions of interest. What is observable may not be sufficiently informative. What has been observed may not have been well designed. Carefully conceived modelling can take us to improved inference compared with adopting standard inference tools like basic regression and analysis of variance. Hierarchical modelling techniques provide a powerful framework for capturing these complexities by explicitly modelling the multi-level structure of ecological systems.In this paper we focus on good modelling practice in the hierarchical Bayesian framework. We discuss good modelling practice in the form of 10 steps, elaborated with a running example, to aid quantitative ecologists interested in employing Bayesian modelling. Two of the authors are statisticians who view themselves primarily as stochastic modellers. The other two are quantitative ecologists who view such stochastic tools as essential for advancing ecological knowledge. Hence, implicitly, we pay careful attention to good modelling practice. Further, we argue the benefits that accrue to working in a Bayesian framework as the paper is developed.It is worth noting that the steps we propose, though presented in the context of ecological modelling, are appropriate for effective model building across most fields of application.