Local Pool Research Articles

Improved Deep Residual Shrinkage Network for Intelligent Interference Recognition with Unknown Interference.

In complex battlefield environments, flying ad-hoc network (FANET) faces challenges in manually extracting communication interference signal features, a low recognition rate in strong noise environments, and an inability to recognize unknown interference types. To solve these problems, one simple non-local correction shrinkage (SNCS) module is constructed. The SNCS module modifies the soft threshold function in the traditional denoising method and embeds it into the neural network, so that the threshold can be adjusted adaptively. Local importance-based pooling (LIP) is introduced to enhance the useful features of interference signals and reduce noise in the downsampling process. Moreover, the joint loss function is constructed by combining the cross-entropy loss and center loss to jointly train the model. To distinguish unknown class interference signals, the acceptance factor is proposed. Meanwhile, the acceptance factor-based unknown class recognition simplified non-local residual shrinkage network (AFUCR-SNRSN) model with the capacity for both known and unknown class recognition is constructed by combining AFUCR and SNRSN. Experimental results show that the recognition accuracy of the AFUCR-SNRSN model is the highest in the scenario of a low jamming to noise ratio (JNR). The accuracy is increased by approximately 4-9% compared with other methods on known class interference signal datasets, and the recognition accuracy reaches 99% when the JNR is -6 dB. At the same time, compared with other methods, the false positive rate (FPR) in recognizing unknown class interference signals drops to 9%.

A novel noise-robustness and rotation-invariant LADAR point cloud target classification method

Identifying targets of LAser Detection And Ranging (LADAR) point clouds that are affected by noise and different poses throws a significant challenge. This paper proposes a novel LADAR point cloud target classification method that is both noise-robust and rotation-invariant. Specifically, the proposed method transforms the point cloud target into a slice image that is resilient to noise and holds rotation-invariance. Next, a designed 2D Convolutional Neural Network (CNN) is utilized to classify the corresponding point cloud target based on the slice image. To overcome the challenge of lacking prior knowledge about the discriminative features of the slice image, the 2D CNN is designed with the Local Importance-based Pooling (LIP) layer. This layer extracts the discriminative feature in a data-driven manner, thereby improving the accuracy of the classification process. The proposed method is evaluated through multiple experiments on the public ModelNet40 dataset. The experimental results demonstrate that the designed LIP-CNN can better learn the discriminative features of the slice image, achieving high classification accuracy. Moreover, the proposed slice-image-based method is capable of accurately classifying the target, even in the presence of noise and different poses.

Local prediction pools

AbstractWe propose local prediction pools as a method for combining the predictive distributions of a set of experts conditional on a set of variables believed to be related to the predictive accuracy of the experts. This is done in a two‐step process where we first estimate the conditional predictive accuracy of each expert given a vector of covariates—or pooling variables—and then combine the predictive distributions of the experts conditional on this local predictive accuracy. To estimate the local predictive accuracy of each expert, we introduce the simple, fast, and interpretable caliper method. Expert pooling weights from the local prediction pool approaches the equal weight solution whenever there is little data on local predictive performance, making the pools robust and adaptive. We also propose a local version of the widely used optimal prediction pools. Local prediction pools are shown to outperform the widely used optimal linear pools in a macroeconomic forecasting evaluation and in predicting daily bike usage for a bike rental company.

Exotic success following disturbance explained by weak native resilience and ruderal exotic bias

Abstract Disturbance is a primary driver of exotic plant invasions, but why disturbance commonly favours exotics over natives is unresolved. To address this question, we conducted the first biogeographic study of disturbance across multiple plant species. We experimentally disturbed grasslands and added seeds of 34 plant species to plots in their native range and in two introduced ranges that differed in invasibility (susceptibility to invasion) to evaluate recruitment while examining potential influences of resource availability, native community recovery from disturbance (resilience) and life‐history traits in local species pools. Species pools in the native (donor) range were more strongly skewed towards ruderal taxa than species pools in the introduced ranges. This bias in the donor pool was exacerbated by introduction filters that further selected for ruderal traits, strongly skewing exotic species pools in the introduced ranges towards ruderals. Sown species, which reflected these trait patterns, benefited from disturbance universally, but their disturbance response was 10‐fold greater in the more invasible introduced range. This result was not explained by nutrient availability, which responded similar to disturbance across ranges. Nor was it driven by background propagule pressure, which was minimal. Rather, the exaggerated disturbance effect in the more invasible introduced range appeared to be driven by weak recovery of the native plant community that allowed ruderal‐biased exotics to proliferate. Overall, disturbance appeared to favoured exotics because they were much more likely than natives to be ruderal. However, this trait bias only corresponded with an invader advantage in the more invasible range where weak community resilience was linked to slow‐growing, stress‐tolerant natives that failed to rapidly recover space and resources. In contrast, in the less invasible introduced range, highly competitive native perennials quickly filled the disturbance gap, demonstrating high community resilience that appeared to limit invader recruitment. Synthesis: Biogeographic influences on local species pools can facilitate invader success following disturbance, but final invasion outcomes are conditioned by native community resilience.

Are public health policies associated with corporate innovation? Evidence from U.S. nonsmoking laws

We use a natural experiment resulting from the staggered adoption of local workplace nonsmoking laws over the past fifty years to examine whether these public health policies also are associated with corporate innovation. We find a positive association between innovation and nonsmoking laws enacted near companies' headquarters locations, particularly in earlier years when smoking rates were highest. We use multiple difference-in-differences specifications, matched samples, companies headquartered in contiguous counties across state lines, and falsification tests to establish the robustness of the observed association and reduce the likelihood of alternative explanations. We then use an inductive approach to explore multiple potential mechanisms behind this correlation. We find evidence suggestive of the following mechanisms: improved health; improvements to employee creativity, productivity, and absenteeism; and increases in the local employee pool. Other mechanisms likely exist, but the collective evidence suggests that policy-based efforts to improve health are associated with a positive externality—increased corporate innovation.

Mode of formation of cryogenic cave carbonates: Experimental evidence from an Alpine ice cave

Coarsely crystalline carbonates that formed cryogenically in caves (CCCcoarse for short) are important paleoenvironmental archives that provide evidence of former perennial ice deposits in currently ice-free caves and allow the timing of the past freezing conditions close to 0 °C in the subsurface to be determined. Despite their significance, the mode of formation of these deposits has never been observed in statu nascendi.We conducted a series of freezing experiments in an Alpine ice cave to test the conceptual model of CCCcoarse formation in freezing pools of water in perennial ice deposits. Our results document a number of features associated with the freezing of such confined water bodies, including ice bulging, cracking and episodic expulsion of water. These observations help explain the degassing of carbon dioxide required to maintain carbonate precipitation in these semi-closed pockets of slowly freezing water. Our experiments yielded a range of morphological types of cryogenic calcite crystals and aggregates comparable to those reported from CCCcoarse from currently ice-free caves elsewhere. The experimentally grown crystals also exhibit the same depleted O isotope composition characteristic of natural carbonates interpreted as being formed subaqueously in a semi-closed pools subject to freezing. The main difference to naturally formed CCCcoarse is their smaller crystal size, reflecting the comparably short freezing time of our experiments of less than two weeks.This study confirms the conceptual model explaining the formation of CCCcoarse in localized pools in ice and calls for a revision of the currently existing classification scheme for cryogenic cave carbonates.

A novel mutation in intron 1 of Wnt1 causes developmental loss of dopaminergic neurons in midbrain and ASD-like behaviors in rats

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with a strong genetic liability. Despite extensive studies, however, the underlying pathogenic mechanism still remains elusive. In the present study, we identified a homozygous mutation in the intron 1 of Wnt1 via large-scale screening of ASD risk/causative genes and verified that this mutation created a new splicing donor site in the intron 1, and consequently, a decrease of WNT1 expression. Interestingly, humanized rat models harboring this mutation exhibited robust ASD-like behaviors including impaired ultrasonic vocalization (USV), decreased social interactions, and restricted and repetitive behaviors. Moreover, in the substantia nigra compacta (SNpc) and the ventral tegmental area (VTA) of mutant rats, dopaminergic (DAergic) neurons were dramatically lost, together with a comparable decrease in striatal DAergic fibers. Furthermore, using single-cell RNA sequencing, we demonstrated that the decreased DAergic neurons in these midbrain areas might attribute to a shift of the boundary of the local pool of progenitor cells from the hypothalamic floor plate to the midbrain floor plate during the early embryonic stage. Moreover, treatments of mutant rats with levodopa could attenuate the impaired USV and social interactions almost completely, but not the restricted and repetitive behaviors. Our results for the first time documented that the developmental loss of DAergic neurons in the midbrain underlies the pathogenesis of ASD, and that the abnormal progenitor cell patterning is a cellular underpinning for this developmental DAergic neuronal loss. Importantly, the effective dopamine therapy suggests a translational significance in the treatment of ASD.

Is there a massive glacial-Holocene flora continuity in Central Europe?

The prevailing paradigm about the Quaternary ecological and evolutionary history of Central European ecosystems is that they were repeatedly impoverished by regional extinctions of most species during the glacial periods, followed by massive recolonizations from southern and eastern refugia during interglacial periods. Recent literature partially contradicts this view and provides evidence to re-evaluate this Postglacial Recolonization Hypothesis and develop an alternative one. We examined the long-term history of the flora of the Carpathian (Pannonian) Basin by synthesising recent advances in ecological, phylogeographical, palaeoecological and palaeoclimatological research, and analysing the cold tolerance of the native flora of a test area (Hungary, the central part of the Carpathian Basin). We found that (1) many species have likely occurred there continuously since before the Last Glacial Maximum (LGM); (2) most of the present-day native flora (1404 species, about 80%) can occur in climates as cold as or colder than the LGM (mean annual temperature ≤+3.5°C); and (3) grasslands and forests can be species-rich under an LGM-like cold climate. These arguments support an alternative hypothesis, which we call the Flora Continuity Hypothesis. It states that long-term continuity of much of the flora in the Carpathian Basin is more plausible than regional extinctions during the LGM followed by massive postglacial recolonizations. The long-term continuity of the region's flora may have fundamental implications not only for understanding local biogeography and ecology (e.g. the temporal scale of processes), but also for conservation strategies focusing on protecting ancient species-rich ecosystems and local gene pools.

Multi-host infection and phylogenetically diverse lineages shape the recombination and gene pool dynamics of Staphylococcus aureus.

Staphylococcus aureus can infect and adapt to multiple host species. However, our understanding of the genetic and evolutionary drivers of its generalist lifestyle remains inadequate. This is particularly important when considering local populations of S. aureus, where close physical proximity between bacterial lineages and between host species may facilitate frequent and repeated interactions between them. Here, we aim to elucidate the genomic differences between human- and animal-derived S. aureus from 437 isolates sampled from disease cases in the northeast region of the United States. Multi-locus sequence typing revealed the existence of 75 previously recognized sequence types (ST). Our population genomic analyses revealed heterogeneity in the accessory genome content of three dominant S. aureus lineages (ST5, ST8, ST30). Genes related to antimicrobial resistance, virulence, and plasmid types were differentially distributed among isolates according to host (human versus non-human) and among the three major STs. Across the entire population, we identified a total of 1,912 recombination events that occurred in 765 genes. The frequency and impact of homologous recombination were comparable between human- and animal-derived isolates. Low-frequency STs were major donors of recombined DNA, regardless of the identity of their host. The most frequently recombined genes (clfB, aroA, sraP) function in host infection and virulence, which were also frequently shared between the rare lineages. Taken together, these results show that frequent but variable patterns of recombination among co-circulating S. aureus lineages, including the low-frequency lineages, that traverse host barriers shape the structure of local gene pool and the reservoir of host-associated genetic variants. Our study provides important insights to the genetic and evolutionary factors that contribute to the ability of S. aureus to colonize and cause disease in multiple host species. Our study highlights the importance of continuous surveillance of S. aureus circulating in different ecological host niches and the need to systematically sample from them. These findings will inform development of effective measures to control S. aureus colonization, infection, and transmission across the One Health continuum.

Home-field advantage affects the local adaptive interaction between Andropogon gerardii ecotypes and root-associated bacterial communities.

Due to climate change, drought frequencies and severities are predicted to increase across the United States. Plant responses and adaptation to stresses depend on plant genetic and environmental factors. Understanding the effect of those factors on plant performance is required to predict species' responses to environmental change. We used reciprocal gardens planted with distinct regional ecotypes of the perennial grass Andropogon gerardii adapted to dry, mesic, and wet environments to characterize their rhizosphere communities using 16S rRNA metabarcode sequencing. Even though the local microbial pool was the main driver of these rhizosphere communities, the significant plant ecotypic effect highlighted active microbial recruitment in the rhizosphere, driven by ecotype or plant genetic background. Our data also suggest that ecotypes planted at their homesites were more successful in recruiting rhizosphere community members that were unique to the location. The link between the plants' homesite and the specific local microbes supported the "home field advantage" hypothesis. The unique homesite microbes may represent microbial specialists that are linked to plant stress responses. Furthermore, our data support ecotypic variation in the recruitment of congeneric but distinct bacterial variants, highlighting the nuanced plant ecotype effects on rhizosphere microbiome recruitment. These results improve our understanding of the complex plant host-soil microbe interactions and should facilitate further studies focused on exploring the functional potential of recruited microbes. Our study has the potential to aid in predicting grassland ecosystem responses to climate change and impact restoration management practices to promote grassland sustainability. IMPORTANCE In this study, we used reciprocal gardens located across a steep precipitation gradient to characterize rhizosphere communities of distinct dry, mesic, and wet regional ecotypes of the perennial grass Andropogon gerardii. We used 16S rRNA amplicon sequencing and focused oligotyping analysis and showed that even though location was the main driver of the microbial communities, ecotypes could potentially recruit distinct bacterial populations. We showed that different A. gerardii ecotypes were more successful in overall community recruitment and recruitment of microbes unique to the "home" environment, when growing at their "home site." We found evidence for "home-field advantage" interactions between the host and host-root-associated bacterial communities, and the capability of ecotypes to recruit specialized microbes that were potentially linked to plant stress responses. Our study aids in a better understanding of the factors that affect plant adaptation, improve management strategies, and predict grassland function under the changing climate.

Local labor market and the cross section of stock returns

Local labor market pooling is a crucial benefit in the economics of agglomeration (Marshall, 1890). To capture the pooling function, we employ segment information and occupation statistics to capture average pairwise labor force similarities for each focal firm. We find that firms in thicker local labor markets are underpriced and display significantly positive stock returns afterwards. The return predictability of local labor market measure is concentrated in non-mega cap firms; high-tech firms; younger firms; and firms with more high-skilled labor, less routine tasks, and lower labor intensity. Our results are robust to a battery of control variables and alternative measure specifications.

Consistent imprints of elevation, soil temperature and moisture on plant and arthropod communities across two subarctic landscapes

Abstract Factors shaping arthropod and plant community structure at fine spatial scales are poorly understood. This includes microclimate, which likely plays a large role in shaping local community patterns, especially in heterogeneous landscapes characterised by high microclimatic variability in space and in time. We explored differences in local microclimatic conditions and regional species pools in two subarctic regions: Kilpisjärvi in north‐west Finland and Varanger in north‐east Norway. We then investigated the relationship between fine‐scale climatic variation and local community characteristics (species richness and abundance) among plants and arthropods, differentiating the latter into two groups: flying and ground‐dwelling arthropods collected by Malaise and pitfall traps, respectively. Arthropod taxa were identified through DNA metabarcoding. Finally, we examined if plant richness can be used to predict patterns in arthropod communities. Variation in soil temperature, moisture and snow depth proved similar between regions, despite differences in absolute elevation. For each group of organisms, we found that about half of the species were shared between Kilpisjärvi and Varanger, with a quarter unique to each region. Plants and arthropods responded largely to the same drivers. The richness and abundance of both groups decreased as elevation increased and were positively correlated with higher soil moisture and temperature values. Plant species richness was a poor predictor of local arthropod richness, in particular for ground‐dwelling arthropods. Our results reveal how microclimatic variation within each region carves pronounced, yet consistent patterns in local community richness and abundance out of a joint species pool.

Local fishery, global commodity: the role of institutions in mediating intersectoral conflict, cooperation, and competition in a globalized fishery

Commons scholarship has improved our understanding of how to govern resources for sustainability. However, it has also been critiqued for its focus on traits (e.g. well-defined system boundaries) that are increasingly threatened by social and environmental trends. Fisheries are a key example of this challenge. While small-scale fisheries are critically important to the diets and livelihoods of millions, industrial fisheries from developed countries now dominate fishing around the world. While these two systems are governed separately, there is substantial overlap between them, conceptualized as the growing influence of globalization on local common pool resource (CPR) systems. One of the most impactful, but least understood consequences of this convergence are the emerging conflicts and competition between small-scale and industrial fisheries. In these systems, the interaction between small-scale CPRs and globalized commodity chains has meant the creation of a new, hybrid resource system, addressed by neither conventional industrial nor traditional small-scale governance approaches. We use empirical data from 396 cases of interactions at sea between globalized industrial and local small-scale fishers in Ghana from 1984 to 2013 to examine the conditions under which resource users conflict or cooperate, linking them to broader political and economic dynamics across scales. We consider the institutional factors that mediate these interactions, identifying policies to promote cooperative, and avert conflictual incidents. We further consider the long-term effects of these patterns of conflict and cooperation for the resilience or vulnerability of the resource base, the fishers, and the institutions governing the system. We suggest that specific governance arrangements that reduce disparities between groups, promote bridging social capital, and enhance hybrid and cross-scale institutions offer the best potential to govern resource systems where traditional CPRs and market-oriented industries converge.

Grasses exploit geometry to achieve improved guard cell dynamics.

Stomata are controllable micropores formed between two adjacent guard cells (GCs) that regulate gas flow across the plant surface.1 Grasses, among the most successful organisms on the planet and the main food crops for humanity, have GCs flanked by specialized lateral subsidiary cells (SCs).2,3,4 SCs improve performance by acting as a local pool of ions and metabolites to drive changes in turgor pressure within the GCs that open/close the stomatal pore.4,5,6,7,8 The 4-celled complex also involves distinctive changes in geometry, having dumbbell-shaped GCs compared with typical kidney-shaped stomata.2,4,9 However, the degree to which this distinctive geometry contributes to improved stomatal performance, and the underlying mechanism, remains unclear. To address this question, we created a finite element method (FEM) model of a grass stomatal complex that successfully captures experimentally observed pore opening/closure. Exploration of the model, including in silico and experimental mutant analyses, supports the importance of a reciprocal pressure system between GCs and SCs for effective stomatal function, with SCs functioning as springs to restrain lateral GC movement. Our results show that SCs are not essential but lead to a more responsive system. In addition, we show that GC wall anisotropy is not required for grass stomatal function (in contrast to kidney-shaped GCs10) but that a relatively thick GC rod region is needed to enhance pore opening. Our results demonstrate that a specific cellular geometry and associated mechanical properties are required for the effective functioning of grass stomata.

Local-to-global spatial learning for whole-slide image representation and classification.

Whole-slide image (WSI) provides an important reference for clinical diagnosis. Classification with only WSI-level labels can be recognized for multi-instance learning (MIL) tasks. However, most existing MIL-based WSI classification methods have moderate performance on correlation mining between instances limited by their instance- level classification strategy. Herein, we propose a novel local-to-global spatial learning method to mine global position and local morphological information by redefining the MIL-based WSI classification strategy, better at learning WSI-level representation, called Global-Local Attentional Multi-Instance Learning (GLAMIL). GLAMIL can focus on regional relationships rather than single instances. It first learns relationships between patches in the local pool to aggregate region correlation (tissue types of a WSI). These correlations then can be further mined to fulfill WSI-level representation, where position correlation between different regions can be modeled. Furthermore, Transformer layers are employed to model global and local spatial information rather than being simply used as feature extractors, and the corresponding structure improvements are present. In addition, we evaluate GIAMIL on three benchmarks considering various challenging factors and achieve satisfactory results. GLAMIL outperforms state-of-the-art methods and baselines by about 1 % and 10 %, respectively.

Anthropogenic hybridization of Populus × sibirica and Populus nigra in Siberia. Crossbreeding in ruderal (disturbed) habitats

Most of the known facts of anthropogenic hybridization of poplar with native taxa are observed in disturbed (ruderal) territories. In the Siberian region, their areas are steadily growing and, at the same time, they become centers of hybridization of the cultivar Populus × sibirica G.V. Krylov & G.V. Grig. ex A.K. Skvortsov with native P. nigra L., and pose a threat to local population gene pools. The purpose of this work is to consider the features of hybridization of Populus × sibirica with P. nigra in disturbed habitats. To achieve the goal set by the authors in 2020–2022, two populations of hybrids were studied in the vicinity of the city of Novokuznetsk (Kuzbass). Materials obtained earlier in the same area when studying the variability in plantations of P. nigra and P. × sibirica were used for comparative study and analysis. Hybrids, both in natural and disturbed habitats, inherit from the Siberian poplar the differentiation of crown shoots obtained by the latter from the ancestors of sections Tacamahaca Mill. In contrast to plantations in natural habitats, hybrids in disturbed areas showed variability in terms of the development of basal glands both at the endogenous and individual levels. Populations of hybrids under these conditions are characterized by a significantly higher phenotypic diversity due to the absence of stabilizing selection. Survival of “different-quality” hybrids under these conditions leads to the absence of prevailing phenotypes in the populations and the absence of asymmetry characteristic of hybridization

A study on the genetic diversity and subpopulation structure of three Bulgarian mountainous sheep breeds, based on genotyping of microsatellite markers

Traditional domestic breeds of domestic animals are part of the “living” wealth of the world, part of the disappearing biodiversity and a valuable local gene pool. Nowadays, they are increasingly included in the category of “rare and disappearing” breeds. Therefore, the purpose of this study was to reveal the genetic diversity and population structure of three Bulgarian mountainous sheep breeds (Rhodopean Tsigai, RT; Middle Rhodopean sheep, MRS; and Karakachan sheep, KS). A total of 113 unrelated individuals (two flocks of each breed) from different regions of the country were investigated based on 11 STR (short tandem repeat) markers. The obtained results showed a total of 116 alleles in the three sheep breeds. The mean number of alleles, effective number of alleles, and polymorphism information content (PIC) values per loci were 8.21, 4.72, and 0.79. The largest number of alleles were found in the population of MRS (9.18 ± 0.76), followed by RT (8.27 ± 0.64) and KS (7.18 ± 0.47). The largest polymorphism was found in INRA005 and INRA06 loci with 11 and 10 alleles, respectively, and the smallest polymorphic loci were noted for the locus McM042 and INRA172 with only 6 alleles. The observed heterozygosity showed the highest value in KS (0.79 ± 0.04), followed by RT (0.76 ± 0.02) and MRS (0.73 ± 0.04). The range of expected heterozygosity was from 0.77 ± 0.02 in MRS to 0.75 ± 0.03 in KS. The fixation index FST, estimated by analysis of molecular variance (AMOVA), was 0.2090, indicating moderate levels of genetic differentiation among the populations. The FST between the investigated breeds indicated a moderate value of 0.216, and the analysis of variance (ANOVA) data showed only 1% variation among the populations, whereas 99% was due to variation within breeds. The results by the STRUCTURE analysis revealed that all breeds were heterogeneous and formed three distinct clusters. The results of the genetic diversity and structure analysis of the investigated breeds provide useful information for assessing the genetic diversity of other Bulgarian autochthonous sheep breeds, serving as a cornerstone for designing effective conservation management strategies.

Document-Level Relation Extraction with Local Relation and Global Inference

The current popular approach to the extraction of document-level relations is mainly based on either a graph structure or serialization model method for the inference, but the graph structure method makes the model complicated, while the serialization model method decreases the extraction accuracy as the text length increases. To address such problems, the goal of this paper is to develop a new approach for document-level relationship extraction by applying a new idea through the consideration of so-called “Local Relationship and Global Inference” (in short, LRGI), which means that we first encode the text using the BERT pre-training model to obtain a local relationship vector first by considering a local context pooling and bilinear group algorithm and then establishing a global inference mechanism based on Floyd’s algorithm to achieve multi-path multi-hop inference and obtain the global inference vector, which allow us to extract multi-classified relationships with adaptive thresholding criteria. Taking the DocRED dataset as a testing set, the numerical results show that our proposed new approach (LRGI) in this paper achieves an accuracy of 0.73, and the value of F1 is 62.11, corresponding to 28% and 2% improvements by comparing with the classical document-level relationship extraction model (ATLOP), respectively.

Hydrochorous Seed Transport in the Lower Traisen River before and after Riverbed Restoration.

Hydrological restoration was carried out in a Lower Traisen, a small river within the floodplain of the Danube. The main goal was the reestablishment of typical riparian plant communities by using the potential of natural dispersal processes. We studied the transport of plant diaspores in the river water before and after the reconstruction of the riverbed. Aquatic seed traps were placed upstream and downstream of the restoration site. We identified the transported species and tested the viability of propagules. Functional species traits were analyzed to predict the probability of successful hydrochorous dispersal and changes in the transport pool due to the restoration. One-third of the local species pool was detected as being diaspores in the river. We observed a significant increase of ruderal species and neophytes, while the competitors and stress-tolerant competitors declined. Hydrochory is an important dispersal pathway for numerous plant species in the study area, including those without specific adaptations to this vector. Hydrochorous transport appears to be a sink for large-seeded species, primarily adapted to endozoochory. Follow-up management should be recommended to control the invasive species and to improve the structural and biological diversity of the Traisen Valley by supporting target species, which are also represented in the transport pool.

Using taxa-based approaches to delineate stream macroinvertebrate assemblage responses to stressor gradients in modified alluvial agroecosystems

Alluvial plain landscapes are some of the most agriculturally productive lands in the world but often have modified stream ecosystems due to cultivation history. This context requires consideration when establishing water quality management goals. We analyzed state water quality databases to demonstrate that Mississippi Alluvial Plain (MAP) ecoregion streams have elevated specific conductivity (SC) and nutrients and lower macroinvertebrate local and regional taxa pools compared to streams in other ecoregions, potentially reducing the efficacy of traditional biomonitoring approaches within the region. To overcome these challenges, we used threshold indicator taxa analysis (TITAN) to compare macroinvertebrate assemblage responses to water quality gradients among ecoregions in Mississippi. We identified individual taxa and assemblage-level responses to increasing water quality degradation in MAP streams. Observed responses occurred at higher concentrations for SC, total organic carbon (TOC) and total phosphorus (TP), but not total nitrogen (TN) relative to other ecoregions. These responses appeared to be driven by a large proportion of indicator taxa considered tolerant or unresponsive in other ecoregions, responding negatively to increasing water quality stressors in MAP streams. Our observed assemblage-level stressor responses to WQ gradients in MAP streams demonstrate shifting tolerance in highly altered ecosystems may require adjustments to recovery expectations but also provide useful measures for monitoring improvements in regional water quality. For example, our observed macroinvertebrate assemblage response to increasing TP identified a management goal similar to guidance based on distributional analysis of water quality data within the MAP ecoregion (0.11 vs 0.128 mg L−1) and thus provide some biological basis for previously identified nutrient goals for the region. Our approach can guide and monitor success of nutrient reduction efforts in MAP watersheds and other alluvial plain agroecosystems where reference conditions do not exist, and local and regional taxa pools are less diverse and may not support full recovery of ecological assemblages. While our results are promising, they should also be compared with more sensitive and less habitat-limited biological assemblages (e.g., algae or bacteria) to better understand complex ecological responses to best management practices designed to increase sustainability of high production agricultural regions.