Degree Of Environmental Change Research Articles

Coral recruits demonstrate thermal resilience

Marine heatwaves are becoming more frequent during summer and pose a significant threat to coral reef ecosystems. Restoration efforts have the potential to support native coral populations and guard them against some degree of environmental change, while global action against climate change takes place. Interspecific hybridization is one approach through which resilient coral stock could be generated for restoration. Here we compared the performance of Acropora kenti and A. loripes hybrid and purebred coral recruits under a simulated thermal stress event. A. kenti eggs were successfully fertilized by A. loripes sperm to produce ‘KL’ hybrids, but no ‘LK’ hybrids could be produced from A. loripes eggs and A. kenti sperm. Despite corals in the elevated treatment accruing thermal stress (>12 degree heating weeks over 2 months) known to result in mass bleaching, both purebred and hybrid recruits showed no signs of stress under the simulated temperature regime, based on the performance indicators survivorship, size, color (a proxy of bleaching), and photochemical efficiency of photosystem II. Comparisons between the hybrids and purebreds studied here must be interpreted with caution because hybrid sample sizes were small. The hybrids did not outperform both of their purebred counterparts for any metrics studied here, demonstrating that there are limitations to the extent to which interspecific hybridization may boost the performance of coral stock. In general, the purebred A. loripes recruits performed best under both ambient and elevated conditions. The performance of the KL hybrid corals was similar to the maternal parental species, A. kenti, or not significantly different to either parental purebred species. The Symbiodiniaceae communities of the KL hybrids were characteristic of their maternal counterparts and may have underpinned the performance differences between the A. kenti/KL hybrid and A. loripes recruits.

A Multi-Layered 3D NDT Scan-Matching Method for Robust Localization in Logistics Warehouse Environments

This paper proposed a multi-layered 3D NDT (normal distribution transform) scan-matching approach for robust localization even in the highly dynamic environment of warehouse logistics. Our approach partitioned a given 3D point-cloud map and the scan measurements into several layers regarding the degree of environmental changes in the height direction and computed the covariance estimates for each layer using 3D NDT scan-matching. Because the covariance determinant is the estimate's uncertainty, we can determine which layers are better to use in the localization in the warehouse. If the layer gets close to the warehouse's floor, the degree of environmental changes, such as the cluttered warehouse layout and position of boxes, would be significantly large, while it has many good features for scan-matching. If the observation at a specific layer is not explained well enough, then the layer for localization can be switched to other layers with lower uncertainties. Thus, the main novelty of this approach is that localization robustness can be improved even in very cluttered and dynamic environments. This study also provides the simulation-based validation using Nvidia's Omniverse Isaac sim and detailed mathematical descriptions for the proposed method. Moreover, the evaluated results of this study can be a good starting point for further mitigating the effects of occlusion in warehouse navigation of mobile robots.

Hitting reset: Industry evolution, generational technology cycles, and the dynamic value of firm experience

AbstractResearch SummaryWe study how the value of depth and breadth of experience shifts across generational technology cycles and industry evolution. Experience breadth builds organizational flexibility that is valuable during technology transitions and when the industry is younger, while experience depth builds domain‐specific resources that are important during periods of technology stability and later periods of industry evolution. We test our theory in the console game industry, where publishers face repeated periods of transition and stability across multiple console generations. We find support for most hypotheses, except that the value of breadth correlates with the magnitude of any transition instead of decreasing linearly over time. We contribute to research on the changing value of firm experience and to the understanding of generational technological change during industry evolution.Managerial AbstractMany industries face generational changes. How incumbent firms handle those transitions is important to firm survival and success. We study how the prior experience of video game publishers helps them navigate transitions. First, we find that firms with deep experience in a genre produce more successful games in that genre only during stable periods in the industry. Second, the benefits of deep experience increase over time as some of the experience‐built capabilities of the firm survive technological transitions. Third, broad and diversified firms perform best during generational transitions as they successfully enter new domains made popular by the generational shift. We suggest that the product strategies of video game firms should depend on the relevant experience they possess and the degree of environmental change.

Climate-induced species range shift and local adaptation strategies in a temperate marine protected area, Ashizuri-Uwakai National Park, Shikoku Island, western Japan

In temperate seas, expansion of reef-building coral distribution, decline of macroalgal beds, and changes in constituent species for coral communities and/or macroalgal beds mainly due to increase in sea surface temperature have been reported. Not only mitigation but also adaptive responses are important for the measures against climate change. Consideration of adaptive measures depends on local conditions such as the degree of environmental change and industrial structure is necessary when measures are implemented. This study focused on the marine protected area (Ashizuri-Uwakai National Park in Japan) and its surrounding area. This area is characterized by a very large north-south gradient in water temperature and the distribution of corals and macroalgae along it. The purpose of this study is to consider what adaptive measures are suitable for each region and industry in response to changes in coastal ecosystems (coral community and macroalgal bed). Future (assuming the end of this century under RCP2.6 and RCP8.5 scenarios) changes in the potential distribution area of coral, macroalgae, and their consumers were projected using simulated sea surface temperature with a high-spatial resolution. After projecting the coastal ecosystem changes and assessing the contemporary use of coastal ecosystem, we give examples of what specific adaptive measures should be taken in each area for three fields, i.e., biodiversity conservation, fisheries, and tourism. Assuming the 2090s, though drastic changes in coastal ecosystem are not projected compared to the present state under RCP2.6 scenario, as coral distribution shifts north, feeding damage by crown-of-thorn starfish is projected to become a problem. Therefore, expansion of protected areas and promotion of conservation activities are major challenges for coral ecosystem conservation. On the other hand, under RCP8.5 scenario, it is important to take appropriate conservation measures for macroalgae since coral growth becomes difficult to achieve and grazing pressure on macroalgae increases due to extreme elevated water temperature. Moreover, creation of alternate or new tourism resources will be needed. This research represents projected scenarios of coastal ecosystem changes with a high spatial resolution and adaptation measures based on the changes for each municipality.

Evaluating the Near and Mid Infrared Bi-Spectral Space for Assessing Fire Severity and Comparison with the Differenced Normalized Burn Ratio

Fire severity, defined as the degree of environmental change caused by a fire, is a critical fire regime attribute of interest to fire emissions modelling and post-fire rehabilitation planning. Remotely sensed fire severity is traditionally assessed by the differenced normalized burn ratio (dNBR). This spectral index captures fire-induced reflectance changes in the near infrared (NIR) and short-wave infrared (SWIR) spectral regions. This study evaluates a spectral index based on a band combination including the NIR and mid infrared (MIR) spectral regions, the differenced normalized difference vegetation index with mid infrared (dNDVIMID), to assess fire severity. This evaluation capitalized upon the unique opportunity stemming from the pre- and post-fire airborne acquisitions over the Rim (2013) and King (2014) fires in California with the MODIS/ASTER Airborne Simulator (MASTER) instrument. The field data consist of 85 Geometrically structured Composite Burn Index (GeoCBI) plots. In addition, six different index combinations, respectively three with a NIR–SWIR combination and three with a NIR–MIR combination, were evaluated based on the optimality of fire-induced spectral displacements. The optimality statistic ranges between zero and one, with values of one representing pixel displacements that are unaffected by noise. The results show that the dNBR demonstrated a stronger relationship with GeoCBI field data when field measurements over the two fire scars were combined than the dNDVIMID approaches. The results yielded an R2 of 0.68 based on a saturated growth model for the best performing dNBR index, whereas the performance of the dNDVIMID indices was lower with an R2 = 0.61 for the best performing dNDVIMID index. The dNBR also outperformed the dNDVIMID in terms of spectral optimality across both fires. The best performing dNBR index yielded median optimality statistics of 0.56 over the Rim and 0.60 over the King fire. The best performing dNDVIMID index recorded optimality values of 0.49 over the Rim and 0.46 over the King fire. We also found that the dNBR approach led to considerable differences in the form of the relationship with the GeoCBI between the two fires, whereas the dNDVIMID approach yielded comparable relationships with the GeoCBI over the two fires. This suggests that the dNDVIMID approach, despite its slightly lower performance than the dNBR, may be a more robust method for estimating and comparing fire severity over large regions. This premise needs additional verification when more air- or spaceborne imagery with NIR and MIR bands will become available with a spatial resolution that allows ground truthing of fire severity.

A reinforcement learning approach for dynamic multi-objective optimization

Dynamic Multi-objective Optimization Problem (DMOP) is emerging in recent years as a major real-world optimization problem receiving considerable attention. Tracking the movement of Pareto front efficiently and effectively over time has been a central issue in solving DMOPs. In this paper, a reinforcement learning-based dynamic multi-objective evolutionary algorithm, called RL-DMOEA, which seamlessly integrates reinforcement learning framework and three change response mechanisms, is proposed for solving DMOPs. The proposed algorithm relocates the individuals based on the severity degree of environmental changes, which is estimated through the corresponding changes in the objective space of their decision variables. When identifying different severity degree of environmental changes, the proposed RL-DMOEA approach can learn better evolutionary behaviors from environment information, based on which apply the appropriate response mechanisms. Specifically, these change response mechanisms including the knee-based prediction, center-based prediction and indicator-based local search, are devised to promote both convergence and diversity of the algorithm under different severity of environmental changes. To verify this idea, the proposed RL-DMOEA is evaluated on CEC 2015 test problems involving various problem characteristics. Empirical studies on chosen state-of-the-art designs validate that the proposed RL-DMOEA is effective in addressing the DMOPs.

Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios.

Substantial environmental change can force a population onto a path towards extinction, but under some conditions, adaptation by natural selection can rescue the population and allow it to persist. This process, known as evolutionary rescue, is believed to be less likely to occur with greater magnitudes of random environmental fluctuations because environmental variation decreases expected population size, increases variance in population size and increases evolutionary lag. However, previous studies of evolutionary rescue in fluctuating environments have only considered scenarios in which evolutionary rescue was likely to occur. We extend these studies to assess how baseline extinction risk (which we manipulated via changes in the initial population size, degree of environmental change or mutation rate) influences the effects of environmental variation on evolutionary rescue following an abrupt environmental change. Using a combination of analytical models and stochastic simulations, we show that autocorrelated environmental variation hinders evolutionary rescue in low-extinction-risk scenarios but facilitates rescue in high-risk scenarios. In these high-risk cases, the chance of a run of good years counteracts the otherwise negative effects of environmental variation on evolutionary demography. These findings can inform the development of effective conservation practices that consider evolutionary responses to abrupt environmental changes.

Impact assessment of treating wastewater on the physiochemical variables of environment: a case of Kermanshah wastewater treatment plant in Iran

BackgroundThe most critical step to control sewage pollution and recycle of wastewater is to establish sewage treatment plants and to monitor their performance. This research aims to assess the environmental impacts of effluent waters, treated by Kermanshah wastewater treatment plant (KWTP), on some physicochemical variables of the adjacent river named as Qarasou River, northwestern Iran. Several water samples were collected from different locations into KWTP and along the Qarasou River in different time intervals of April and July 2017 to assess the effect of treated waters on the environment water quality. As well, an integrated environmental change index (ΔYi) was defined to assess the degree of changes and impacts in the current status.ResultsThe analyses indicated that the values of total suspended solids (TSS), nitrate (NO3), phosphorous (P), biological oxygen demand (BOD), and chemical oxygen demand (COD) overall decreased by treatment process at effluent water compared with raw sewage amounts. Contrarily, amounts of acidity and dissolved oxygen (DO) slightly increased in effluent water due to the aeration processes during the treatment process. The environmental change index (ΔYi) was estimated between 0.04 and 0.88 with an average of 0.28 for all variables in different time intervals, indicating the lowest degree of environmental changes and higher efficiency of treating wastewater in KWTP.ConclusionsThe results concluded the efficiency for the removal TSS, NO3, BOD, and COD is estimated 80–92% during the water purification process in KWTP as an acceptable efficiency. Finally, it can be mentioned that the activated sludge process of KWTP has not any risky impacts on Qarasou River and the whole environment.

Ecological drivers of Hepacivirus infection in a neotropical rodent inhabiting landscapes with various degrees of human environmental change.

Anthropogenic environmental change can impact community and population traits such as species diversity and population densities, which have been shown to influence the prevalence of viruses in wildlife reservoirs. In particular, host species resilient to changes in their natural habitat may increase in numbers, which in turn can affect the prevalence of directly transmitted viruses. We have carried out a survey of small mammal communities in three tropical landscapes differing in their degree of environmental change in Central Panama and investigated the effects of community changes on Hepacivirus prevalence. The modification of continuous habitat into partly connected or isolated habitat patches during the past century was linked to changes in species diversity and species assemblages, which was further associated with shifts in the abundance of generalist marsupial (Didelphis marsupialis, Philander opossum) and rodent (Proechimys semispinosus) species. The latter has become dominant in isolated habitat patches and was the only identified Hepacivirus host in our study system. Our analyses suggest that, in addition to the effects of host age and sex, host population density in interaction with sex ratio is a crucial predictor of infection probability. Although we found no significant relationships between species diversity per se and infection probability, the lowest prevalence detected in the landscape with the highest species diversity indicates that shifts in species assemblages (e.g. changes in the presence and abundance of marsupial predators) impact the host's intraspecific contact rates, the probability of virus transmission and, thus, the virus prevalence. Our study additionally provides important data on the influence of human-induced landscape changes on infection probability and, therefore, on virus prevalence in wildlife and emphasizes the importance of a landscape-scale approach with concomitant consideration of the complex interactions between ecological factors.

Effects of pasture conversion to sugarcane for biofuel production on stream fish assemblages in tropical agroecosystems

Abstract One of the main causes of biodiversity loss in aquatic ecosystems is instream habitat change associated with land‐use change in the drainage basin. Biofuel crop production is an increasingly important driver of land‐use change in existing agricultural drainage basins. Conceptually, biofuels such as sugarcane (Saccharum spp.: Poaceea) can provide a sustainable alternative to fossil fuels, but little is known about the consequences of biofuel crop production for biodiversity. Thus, our aim was to investigate if and how the degree of further environmental changes at regional and local scales can influence taxonomic and functional structure of fish assemblages in agroecosystem streams. We quantified drainage basin land use, instream and riparian habitat, and fish assemblages in 38 agroecosystem streams in Brazil with drainage basins experiencing rapid expansion of sugarcane production, and calculated degree of environmental change and corresponding response in taxonomic and functional structure of stream fish assemblages. Procrustes and redundancy analyses tested for correlation between land use and instream habitat and environmental factors correlated with fish assemblage structure, respectively. Previous studies demonstrated relationships between land‐use change, instream habitat change and taxonomic and functional structure of stream fish assemblages. Therefore, we used regression to test the hypothesis that degree of environmental change is positively correlated with magnitude of change in taxonomic and functional structure of fish assemblages. Primary gradients of environmental change included conversion of pasture to sugarcane and reduction of stream width, depth and volume. Although drainage basin and instream attributes were not correlated within a year, we detected a legacy effect of land use on instream habitat. The degree of environmental change was not significantly correlated with taxonomic or functional changes in stream fish assemblages in most cases. However, abundances of resistant taxa increased, whereas nektonic functional groups decreased, and the biological response also presented evidence of a legacy effect. Our findings demonstrate that instream habitat and aquatic biodiversity in streams with agricultural drainage basins undergoing rapid conversion to biofuel production likely will not experience the full magnitude of responses in the short term. Therefore, repeated sampling of sufficient duration to account for legacy effects or time lags is needed to test for effects of biofuel expansion on biodiversity, and similarly to assess whether management practices such as riparian zone preservation can benefit biodiversity in agroecosystems.

Fish community dynamics (1985–2010) in multiple reaches of a large river subjected to flow restoration and other environmental changes

Summary To assess how climate warming, flow regulation and flow restoration affect community dynamics, we analysed long‐term (15–25 years) series of fish community data from four restored and two unrestored reaches of the Rhône River. Environmental variables (low and high flow hydraulics, temperature, sediment flushing operations) were measured in all reaches. Five of the reaches were bypassed by artificial channels, downstream from diversion dams whose construction finished in 1984. Minimum flows in four of these reaches were restored (i.e. increased by factors up to 10) between 2000 and 2006. We examined hypotheses concerning the inter‐annual response of fish community guilds and size structure to flow restoration, climate warming and dam completions. We also performed a principal component analysis (PCA) to explore observed community changes at the river scale (all reaches pooled). We used mixed‐effects linear models to infer potential environmental effects not included in our hypotheses. Our results indicated an inter‐annual effect of flow restoration in the two reaches where minimum flows were most modified (higher percentages of ‘midstream’ species preferring deep and fast water). They also revealed effects of climate warming in the two warmed reaches (higher percentages of southern and small individuals and higher total density). These effects were consistent with our hypotheses. In contrast, dam construction had no consistent effects across reaches. The first PCA axis indicated that the longitudinal organisation of fish communities at the river scale was unchanged, but independent inter‐annual effects of flow restoration and climate change were apparent along the second and third axes. Observed annual variations within sites were weakly related to annual variation in environmental variables. This may be due to the presence of long‐term or time‐lagged environmental effects and the difficulty of estimating community structure of large river fishes accurately enough for this kind of analysis. Fish community responses to flow restoration and other environmental changes may be consistent across multiple reaches when the degree of environmental change is taken into account. Our results support the effectiveness of flow restoration on communities of large rivers subjected to multiple environmental changes.

Assessing fire severity using imaging spectroscopy data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and comparison with multispectral capabilities

Fire severity, the degree of environmental change caused by a fire, is traditionally assessed by broadband spectral indices, such as the differenced Normalized Burn Ratio (dNBR) from Landsat imagery. Here, we used an alternative indicator, the burned fraction derived from spectral mixture analysis (SMA), to evaluate and compare the performance for assessing fire severity of broadband and narrowband imaging spectroscopy (IS) data in the visible to shortwave infrared (VSWIR, 0.35–2.5μm). We used the band specifications of the broadband Operational Land Imager (OLI) and the narrowband Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). We integrated two techniques to account for endmember variability in the unmixing process, spectral weighting and iterative unmixing, in a model referred to as weighted multiple endmember SMA (wMESMA). Based on a separability index, we evaluated the separability between the different ground components, or endmembers, that comprise post-fire environments (char, green vegetation (GV), non-photosynthetic vegetation (NPV) and substrate). We found that the near infrared region (0.7–1.3μm) had the highest discriminatory power, followed by the shortwave infrared 2 (SWIR2, 2–2.4μm), SWIR1 (1.5–1.7μm) and visible (0.35–0.7μm) regions. Individual narrowbands did not substantially outperform individual broadbands, however, the higher data dimensionality of IS resulted in significantly improved post-fire fractional cover and burned fraction estimates compared to multispectral data. Multispectral data captured a fair amount of the variability in fire severity conditions as represented by the different fractional cover estimates of the endmembers in both a multispectral narrow- and broadband scenario, however, fractional cover estimates derived from IS data using all viable bands were significantly better. This demonstrated the benefits of IS over traditional multispectral data to assess fire severity and also showed that the additional information gain was the result of higher data dimensionality and not because of certain narrowbands capturing narrow spectral features. In addition, we found that the burned fraction derived from all viable AVIRIS bands over a fire in California, USA, was highly correlated with two field measures of fire severity (Geo Composite Burn Index: R2=0.86, and the percentage black trees and shrubs: R2=0.65). Formal quantification of potential improvements of IS over multispectral methods is important with the advent of upcoming spaceborne IS missions (e.g. the Environmental Mapping and Analysis Program and Hyperspectral Infrared Imager). Our analysis showed that IS data when combined with advanced analysis techniques significantly improved fire severity assessments. The improvements of using IS data require higher computational cost and advanced processing, thus multispectral data might still suit the needs of certain applications such as rapid fire damage assessments and global analysis of spatio-temporal fire severity patterns.

Smaller, Scale-Free Gene Networks Increase Quantitative Trait Heritability and Result in Faster Population Recovery

One of the goals of biology is to bridge levels of organization. Recent technological advances are enabling us to span from genetic sequence to traits, and then from traits to ecological dynamics. The quantitative genetics parameter heritability describes how quickly a trait can evolve, and in turn describes how quickly a population can recover from an environmental change. Here I propose that we can link the details of the genetic architecture of a quantitative trait—i.e., the number of underlying genes and their relationships in a network—to population recovery rates by way of heritability. I test this hypothesis using a set of agent-based models in which individuals possess one of two network topologies or a linear genotype-phenotype map, 16–256 genes underlying the trait, and a variety of mutation and recombination rates and degrees of environmental change. I find that the network architectures introduce extensive directional epistasis that systematically hides and reveals additive genetic variance and affects heritability: network size, topology, and recombination explain 81% of the variance in average heritability in a stable environment. Network size and topology, the width of the fitness function, pre-change additive variance, and certain interactions account for ∼75% of the variance in population recovery times after a sudden environmental change. These results suggest that not only the amount of additive variance, but importantly the number of loci across which it is distributed, is important in regulating the rate at which a trait can evolve and populations can recover. Taken in conjunction with previous research focused on differences in degree of network connectivity, these results provide a set of theoretical expectations and testable hypotheses for biologists working to span levels of organization from the genotype to the phenotype, and from the phenotype to the environment.

The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: The case of the large 2007 Peloponnese wildfires in Greece

The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies was studied for the case of the large 2007 Peloponnese wildfires in Greece. Fire severity is defined as the degree of environmental change as measured immediately post-fire, whereas burn severity combines the direct fire impact and ecosystems responses. Geo Composite Burn Index (GeoCBI), two pre-/post-fire differenced Thematic Mapper (TM) dNBR assessments and a Moderate Resolution Imaging Spectroradiometer (MODIS) dNBR time series were used to analyze the temporal dimension. MODIS dNBR time series were calculated based on the difference between the NBR of the burned and control pixels, which were retrieved using time series similarity of a pre-fire year. The analysis incorporated the optimality statistic, which evaluates index performance based on displacements in the mid-infrared–near infrared bi-spectral space. Results showed a higher correlation between field and TM data early post-fire (R 2 = 0.72) than one-year post-fire (R 2 = 0.56). Additionally, mean dNBR (0.56 vs. 0.29), the dNBR standard deviation (0.29 vs. 0.19) and mean optimality (0.65 vs. 0.47) were clearly higher for the initial assessment than for the extended assessment. This is due to regenerative processes that obscured first-order fire effects impacting the suitability of the dNBR to assess burn severity in this case study. This demonstrates the importance of the lag timing, i.e. time since fire, of an assessment, especially in a quickly recovering Mediterranean ecosystem. The MODIS time series was used to study intra-annual changes in index performance. The seasonal timing of an assessment highly impacts what is actually measured. This seasonality affected both the greenness of herbaceous resprouters and the productivity of the control pixels, which is land cover specific. Appropriate seasonal timing of an assessment is therefore of paramount importance to anticipate false trends (e.g. caused by senescence). Although these findings are case study specific, it can be expected that similar temporal constraints affect assessments in other ecoregions. Therefore, within the limitations of available Landsat imagery, caution is recommended for the temporal dimension when assessing post-fire effects. This is crucial, especially for studies that aim to evaluate trends in fire/burn severity across space and time. Also, clarification in associated terminology is suggested.

Insect adaptations to cold and changing environments

AbstractA review of insect adaptations for resistance to cold and for life-cycle timing reveals the complexity of the adaptations and their relationships to features of the environment. Cold hardiness is a complex and dynamic state that differs widely among species. Surviving cold depends on habitat choice, relationships with ice and water, and synthesis of a variety of cryoprotectant molecules. Many aspects are time-dependent and are integrated with other factors such as taxonomic affinity, resource availability, natural enemies, and diapause. Timing adaptations reflect the fact that all environments change over many different time frames, from days to thousands of years. Environments differ in severity and in the extent, nature, variability, and predictability of change, as well as in how reliably cues indicate probable conditions in the future. These differences are reflected by a wide range of insect life-cycle systems, life-cycle delays, levels of responsiveness to various environmental signals, genetic systems, and circadian responses. In particular, the degree of environmental change, its predictability on different time frames, and whether it can be monitored effectively dictate the balance between fixed and flexible timing responses. These same environmental features have to be characterized to understand cold hardiness, but this has not yet been done. Therefore, the following key questions must be answered in order to put cold hardiness into the necessary ecological context: How much do conditions change? How consistent is the change? How reliable are environmental signals?

１．脳梗塞超急性期の病態

Through many experimental brain ischemia studies, it has been suggested that all of the cellular elements in the central nervous system show dynamic stress responses depending on the degree of environmental changes induced by ischemia and reperfusion. In this symposium, first I reviewed the pathogenic role of microvascular stasis (i. e., secondary ischemia) caused by the primary ischemic event and demonstrated the important role of cell adhesion molecules through the experiments using ICAM-1 knock-out mouse as a model of brain ischemia/reperfusion. Next, I discussed the ischemia-induced neuronal cell responses in relation to the apoptosis-like selective neuronal death and the induction of adopted stress responses including stress protein synthesis and 'ischemic tolerance' phenomenon. A variety of stress proteins induced by ischemic stress have been reviewed in relation to their pathophysiological roles in the ischemic brain. Finally, I reviewed the important pathogenic roles of endoplasmic reticulum (ER) stress as well as adaptive responses of ubiquitin-proteasome system in ischemia-induced neuronal cell death. For the development of a novel therapeutic agent against ischemic stroke, it is quite important to clarify both the negative and positive cellular responses induced by brain ischemia/reperfusion.

Comparison between Lamarckian and Darwinian Evolution on a Model Using Neural Networks and Genetic Algorithms

In this paper, we study the relationship between learning and evolution in a simple abstract model, where neural networks capable of learning are evolved using genetic algorithms (GAs). Each individual tries to acquire a proper behavior under a given environment through its lifetime learning, and the best individuals are selected to reproduce offspring, which then conduct lifetime learning in the succeeding generation. The connective weights of individuals' neural networks undergo modification, i.e., certain characters will be acquired, through their lifetime learning. By setting various rates for the heritability of acquired characters, which control the strength of ‘Lamarckian’ strategy, we observe adaptational processes of populations over successive generations. By taking the degree of environmental changes into consideration, we show the following results. Under static environments, populations with higher rates of heritability adapt themselves more quickly toward the environments, and thus perform well. On the other hand, under nonstationary environments, populations with lower rates of heritability not only show more stable behavior against environmental changes, but also maintain greater adaptability with respect to such changing environments. Consequently, the population with zero heritability, i.e., the Darwinian population, attains the highest level of adaptation towards dynamic environments.

Dynamic cellular response following brain ischemia and reperfusion

Since the first documentation of the induction of heat shock protein following transient cerebral ischemia, much experimental evidence suggested that all of the cellular elements in the central nervous system show dynamic stress responses depending on the degree of environmental changes induced by ischemia and reperfusion. In this review, first I focused on the importance of the usage of an appropriate experimental model for brain ischemia and reperfusion, and I presented our work on mouse models of transient global and focal ischemia. Next, I reviewed the pathogenic role of microvascular stasis (i.e., secondary ischemia) caused by the primary ischemic event and demonstrated the important role of cell adhesion molecules through the experiments using ICAM-1 knock-out mouse as a model of brain ischemia/reperfusion. Thirdly, I discussed the ischemia-induced neuronal cell responses in relation to the apoptosis-like selective neuronal death and the induction of adopted stress responses including stress protein synthesis and 'ischemic tolerance' phenomenon. A variety of stress proteins induced by ischemic stress have been reviewed and a pivotal role of tyrosine kinase system in selective neuronal death has been suggested in the gerbil model of transient forebrain ischemia. Finally, I showed the important pathophysiological roles of glial cells such as astrocytes and oligodendrocytes in the cellular cross-talk triggered by an ischemic event. For the development of a novel therapeutic agent against ischemic stroke, it is quite important to clarify both the negative and positive cellular responses induced by brain ischemia/reperfusion.

The ecophysiological complex of Bathyporeia pilosa and B. pelagica (Crustacea: Amphipoda). II. Effects of exposure

The resistance to high and low temperatures, starvation and desiccation effects in the sand dwelling amphipods Bathyporeia pilosaLindstrom and B. pelagica (Bate) have been tested. B. pilosa was the more tolerant species in all experiments. Gravid females showed a greater resistance to high temperatures than adult males in both species, and starvation tolerance was in the order gravid females>juvenile males> adult males. Time-temperature relationships, however, would seem to be of greater ecological significance than upper or lower lethal temperatures, and desiccation effects become obvious well within any limits set by starvation. Exposure would appear to be an important concept limiting the intertidal distribution of sand dwelling animals, particularly those confined to the surface layers of sediment. The amplitude, rate and degree of environmental change and its effect on feeding and reproduction offer severe limitations to the distribution of the two Bathyporeia species studied.

Peeping in chicks as a function of environmental change

Peeping was measured in 1-day-old and 4-day-old chicks in four different testing conditions. No differences were found between the two ages, but peeping increased markedly with the degree of environmental change. This latter variable may have been overlooked in past work because of the prevailing interest in changes of behavior as a function of disruption of social imprinting bonds.