Empirical models of rain-spells characteristics – A case study of a Mediterranean-arid climatic transect

Environmental (geomorphological, hydrological and ecological) processes are controlled by rainfall, particularly in the Mediterranean, semi-arid and arid regions. Rainfall was analyzed using the concept of rain-spells, i.e., a period of successive rain days preceded and followed by at least one day without rainfall. Daily data from 13 stations along a climatic transect extending from the Judean Mountains with a Mediterranean climate to the Dead Sea arid region in Israel were studied. Rain-spell characteristics (number, yield and duration), based on these data, are presented for different rainfall thresholds, which might be used for different environmental processes such as rock weathering, soil organic matter dynamics, landslides, overland flow and floods and soil erosion. Three estimation models have been developed in order to predict the mean annual Number of Rain-Spells (NRS), mean Rain-Spell Yield (RSY), and mean Rain-Spell Duration (RSD) for the mean annual rainfall and for any given rainfall threshold. These models can be used for current climatic conditions and for scenarios in which the rainfall total changes.     

Benefits of mycorrhizal inoculation in reintroduction of endangered plant species under drought conditions

Numerous human activities constitute threats to biodiversity. The effects of climate change, including increasing drought in already arid lands, pose an additional layer of uncertainty in the fate of rare species. In the case of plants, reintroduction is becoming an important active management practice in species conservation. We hypothesized that even under extreme drought inoculation with mycorrhizal fungi would increase growth rates of an endangered plant in experimental reintroduction. We selected a plant species, Abronia macrocarpa, and conducted the experiment in Texas while the area was experiencing mild and extreme drought intensities. Treatment plots were planted with seed inoculated with arbuscular mycorrhizal fungi and control plots were planted with seed coated with autoclaved inoculant. We analyzed measurements of growth and development of germinated plants. Mean number of leaves was greater in treatment plants (P = 0.005) and mean aerial diameter was larger in treatment plants (P = 0.02) than in control plants. Significantly improved growth suggests that inoculation is a viable technique to increase reintroduction success in plant species especially during periods of drought.     

Predictive mapping of soil total nitrogen at a regional scale: A comparison between geographically weighted regression and cokriging

Accurately mapping the spatial distribution of soil total nitrogen is important to precision agriculture and environmental management. Geostatistical methods have been frequently used for predictive mapping of soil properties. Recently, a local regression method, geographically weighted regression (GWR), got the attention of environmentalists as an alternative in spatial modeling of environmental attributes, due to its capability of incorporating various auxiliary variables with spatially varied correlation coefficients. The objective of this study is to compare GWR and ordinary cokriging (OCK) in predictive mapping of soil total nitrogen (TN) using multiple environmental variables. 353 soil Samples within the surface horizon of 0–20 cm in a study area were collected, and their TN contents were measured for calibrating and validating the GWR and OCK interpolations. The environmental variables finally chosen as auxiliary data include elevation, land use types, and soil types. Results indicate that, although OCK is slightly better than GWR in global accuracy of soil TN prediction (the adjusted R² for GWR and OCK are 0.5746 and 0.6858, respectively), the soil TN map interpolated by GWR shows many details reflecting the spatial variations of major auxiliary variables while OCK smoothes out almost all local details. Geographically weighted regression could account for both the spatial trend and local variations, whilst OCK had difficulties to capture local variations. It is concluded that GWR is a more promising spatial interpolation method compared to OCK in predicting soil TN and potentially other soil properties, if a suitable set of auxiliary variables are available and selected.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city,China

Land price plays an important role in guiding land resource allocation for urban planning and development, particularly in big cities of fast developing countries where infrastructures and populations change frequently. Therefore, detecting spatially implicit information in the spatial pattern of relationships between land price and related impact factors is critical. Geographically weighted regression (GWR) analysis was conducted in this study for the purpose in Wuhan, China, by using a 10-year panel data set of residential land price. Based on twelve factors in three aspects (land attributes, location factors and neighborhood attributes), an evaluation index system of resident land price was established. The spatial distributions of estimated coefficients and pseudo t-values of three major explanatory variables (floor area ratio, distance to nearest center business district (CBD) and distance to nearest lake), obtained from GWR analysis, indicated that their relationships of the impact factors with land price are spatially non-stationary. The positive impact of floor area ratio on land price is more significant in highly developed areas than in less developed areas. Conversely, the negative impact of distance to nearest CBD on land price is larger in highly developed areas than in less developed areas. Moreover, wealthier dwellers may be willing to pay a higher price for a good lake view (especially views of small lakes), but infrastructure barriers (near some large lakes) cause negative effect. The outputs of this study, which provide detailed information on the relationships between land price and impact factors in local areas, are promising for urban planners to scientifically evaluate land price and make area-specific strategies.     

Lessons learned from the 2013 Calgary flood: Assessing risk of drinking water well contamination

A devastating flood occurred in southern Alberta on June 19, 2013, from greater than normal snowfalls in the Rocky Mountains and excess precipitation during the early spring that left soils saturated and unable to absorb any additional precipitation. This flood was Canada's most costly natural disaster, with five to six billion Canadian dollars in damages. The first objective of this study was to determine if the flood caused an increase in private drinking water well contamination in the Calgary Health Zone by comparing contamination rates to previous years. The second objective was to determine which environmental factors were associated with contamination during this flood event. Test results of total coliforms (TC) and Escherichia coli (EC) of private water wells were used to determine contamination. A geographically weighted Poisson regression analysis suggested that TC contamination was not associated with this flood. The EC contamination is positively associated with floodways, flood fringe, farms, and negatively associated with intermittent water (sloughs). These results suggest that for the 2013 flood, individual well characteristics are more important than surrounding geographic features. Thus, it is recommended that homeowners who live in a high-risk area ensure their wells are properly maintained to reduce risk of water well contamination.     

A spatio-temporal analysis of academic performance at the Basic Education Certificate Examination in Ghana

Over the last decade, Ghana has more than tripled investment in its basic education system. Consequently, the country has made huge educational gains, primarily in providing universal access to basic education. However, many stakeholders are worried that academic performance is lagging because of disproportional attention to accessing basic education. Discussion of these concerns is hampered by ongoing disagreement about the true trajectory of academic performance at the basic education level and the widespread nature of students' lagging academic performance. In part, this disagreement stems from the failure of empirical studies to comprehensively examine trends in academic performance standards at the basic education level by concurrently considering a geographical and longitudinal perspective. Thus, this study examines the spatio-temporal trends of academic performance at the junior high school level since 2009 by using multilevel growth curve modeling, spatial statistics, and district-level longitudinal data. Results reveal 3 statistically distinct trajectories of academic performance: erratic, accelerating, and decelerating changes. Results also show that rural–urban gaps explain 31% of the performance trajectories, a trend which is expected to persist in the long term. In addition, we find extreme variations in academic performance within rural areas. Given the varying trajectories and geographical variability in academic performance, we suggest a localized approach to addressing challenges of low academic achievement at the basic education level in Ghana.     

Variation in low food access areas due to data source inaccuracies

Several spatial measures of community food access identifying so called “food deserts” have been developed based on geospatial information and commercially-available, secondary data listings of food retail outlets. It is not known how data inaccuracies influence the designation of Census tracts as areas of low access. This study replicated the U.S. Department of Agriculture Economic Research Service (USDA ERS) food desert measure and the Centers for Disease Control and Prevention (CDC) non-healthier food retail tract measure in two secondary data sources (InfoUSA and Dun & Bradstreet) and reference data from an eight-county field census covering 169 Census tracts in South Carolina. For the USDA ERS food deserts measure accuracy statistics for secondary data sources were 94% concordance, 50–65% sensitivity, and 60–64% positive predictive value (PPV). Based on the CDC non-healthier food retail tracts both secondary data demonstrated 88–91% concordance, 80–86% sensitivity and 78–82% PPV. While inaccuracies in secondary data sources used to identify low food access areas may be acceptable for large-scale surveillance, verification with field work is advisable for local community efforts aimed at identifying and improving food access.     

Soil seed bank longevity of the exotic annual grass Bromus rubens in the Mojave Desert,USA

Although arid environments are often considered among the least invaded terrestrial biomes, the impacts of exotic plant species can be severe and long lasting. Bromus rubens (red brome) is an exotic annual grass species in the Mojave Desert known to outcompete native plant species, alter habitat, and promote accumulation of fuel that contributes to increasing fire frequency and severity. We assessed longevity of the exotic B. rubens seeds in the soil by burying seeds at four depths (0, 2, 5, and 10 cm) and recovering seeds 6, 12, 18, and 24 months after burial. Seed viability was reduced with greater burial depth and greater time since burial. A relatively small proportion of seeds retained viability for two years, suggesting that while the B. rubens seed bank can be large, it is relatively short-lived. Although B. rubens apparently relies more on the annual production, dispersal, and germination of seeds than on a long-lived seed bank for its annual recruitment, the numerous seeds produced by individual plants indicate that even a small proportion of seeds remaining viable for more than a year can aid recruitment from the seed bank and is an important factor in understanding population dynamics.     

Modelling collective Yawuru values along the foreshore of Roebuck Bay,Western Australia using fuzzy logic

The cadastral model has played a key role in Indigenous dispossession in settler states. Yet, the recognition of Indigenous land rights, which has increased globally since the 1960s, frequently requires Indigenous communities to directly engage with this spatial model. In Australia, native title claimants must use entity-based models of space to delineate their traditional territories during the claim process. They must also engage with planning and development documents which use the cadastral model of space to assert and defend their rights following native title recognition. This is often problematic as Indigenous spatial ontologies emphasise complexity and continuity which is inimical to the ‘crisp’ representations of cadastral space.This study explores the potential of a fuzzy index modelling approach to represent cultural values using a case study from Broome, Western Australia. Sketch mapping, fuzzy index modelling and combinatory techniques were used to produce a model of several cultural values held by the Yawuru community for the in-town foreshore of Roebuck Bay. This model was overlaid on local planning documents to provide the Yawuru community with strategic intelligence for post native title governance. The experience of co-producing this model suggests that such techniques may assist Indigenous communities to engage with settler structures. This implies that policies which fail to extend analytical capacity to interested native title groups as part of programmes of spatial enablement continue to perpetuate historical processes of colonial domination.     

Boundary-based analysis for the assessment of coastal dune landscape integrity over time

Coastal dunes are transitional systems which offer manifold ecosystem services, including material and intangible benefits, whose relevance for human society has been little investigated to date. In order to plan a sustainable use of these threatened ecosystems, proper indicators to quantify ecological services and functions over time should be provided. Since the functionality of coastal dunes is affected by the specific contiguity among different dune habitat patches, in this paper we propose the use of landscape integrity, expressed by the number and length of boundary types among the aforementioned habitats, as an ecosystem functionality indicator. In particular, we aim at properly expressing the trend of coastal dune mosaic integrity in two Italian LTER sites over the last sixty years by applying a generalized diversity function on the number and length of boundary types. Such functions, unlike a traditional diversity index, allow a complete summarization of landscape diversity and structure. The proposed method has proved to be effective in the considered context, because it has adequately underlined the different landscape integrity trend recorded in the two sites. In particular, generalized diversity functions showed to efficiently express both rough and moderate anthropogenic transformations, which affected spatial heterogeneity and functionality of the considered coastal dune mosaic. Further applications at different scales and across different ecosystems are encouraged.     

A comparison of techniques for generating forest ownership spatial products

To fully understand forest resources, it is imperative to understand the social context in which the forests exist. A pivotal part of that context is the forest ownership. It is the owners, operating within biophysical and social constraints, who ultimately decide if the land will remain forested, how the resources will be used, and by whom. Forest ownership patterns vary substantially across the United States. These distributions are traditionally represented with tabular statistics that fail to capture the spatial patterns of ownership. Existing spatial products are not sufficient for many strategic-level planning needs because they are not electronically available for large areas (e.g., parcels maps) or do not provide detailed ownership categories (e.g., only depict private versus public ownership). Thiessen polygon, multinomial logit, and classification tree methods were tested for producing a forest ownership spatial dataset across four states with divergent ownership patterns: Alabama, Arizona, Michigan, and Oregon. Over 17,000 sample points with classified forest ownership, collected as part of the USDA Forest Service, Forest Inventory and Analysis (FIA) program, were divided into two datasets, one used as the dependent variable across all of the models and 10 percent of the points were retained for validation across the models. Additional model inputs included a polygon coverage of public lands from the Conservation Biology Institute’s Protected Areas Database (PAD) and data representing human population pressures, road densities, forest characteristics, land cover, and other attributes. The Thiessen polygon approach predicted ownership patterns based on proximity to the sample points in the model dataset and subsequent combining with the PAD ownership data layer. The multinomial logit and classification tree approaches predicted the ownership at the validation points based on the PAD ownership information and data representing human population, road, forest, land cover, and other attributes. The percentage of validation points across the four states correctly predicted ranged from 76.3 to 78.9 among the methods with corresponding weighted kappa values ranging from 0.73 to 0.76. Different methods performed slightly, but statistically significantly, better in different states Overall, the Thiessen polygon method was deemed preferable because: it has a lower bias towards dominant ownership categories; requires fewer inputs; and is simpler to implement.     

Photosynthetic characteristics of sinking microalgae under the sea ice

The photosynthetic characteristics of sinking a microalgal community were studied to compare with the ice algal community in the sea ice and the phytoplankton community in the water column under the sea ice at the beginning of the light season in the first-year sea ice ecosystem on the Mackenzie Shelf, in the western Canadian Arctic. The phytoplankton community was collected using a water bottle, whereas the sinking algal community was collected using particle collectors, and the ice algal community was obtained by using an ice-core sampler from the bottom portion of ice core. Photosynthesis versus irradiance (P-E) incubation experiments were conducted on deck to obtain the initial slope (α^B) and the maximum photosynthetic rate (P_m^B) of the three algal communities. The α^B and the P_m^B of the light saturation curve, and chlorophyll a (Chl a) specific absorption coefficient (ā_ph*) between the sinking microalgal community and the ice algal community were similar and were distinctly different from the phytoplankton community. The significant linear relationship between α^B and P_m^B, which was obtained among the three groups, may suggest that a photo-acclimation strategy is common for all algal communities under the low light regime of the early season. Although the sinking algal community could be held for the entire duration of deployment at maximum, this community remained photosynthetically active once exposed to light. This response suggests that sinking algal communities can be the seed population, which results in a subsequent phytoplankton bloom under the sea ice or in a surface layer, as well as representing food for the higher trophic level consumers in the Arctic Ocean even before the receding of the sea ice.     

Climate change in the Arctic: current and future vulnerability in two Inuit communities in Canada

Climate change is already occurring in the Arctic and the Arctic Climate Impact Assessment recently concluded that future climate change could be devastating for Inuit. This paper characterises vulnerability to climate change in two Inuit communities in the Canadian territory of Nunavut, focusing on the resource harvesting sector. In both communities, Inuit have demonstrated significant adaptability in the face of current changes in climatic conditions. This adaptability is facilitated by traditional Inuit knowledge, strong social networks, flexibility in resource use, and institutional support. Changing Inuit livelihoods, however, have undermined certain aspects of adaptive capacity and have resulted in emerging vulnerabilities. Global and regional climate projections indicate that climatic conditions which currently pose risks are expected to be negatively affected by future climate change. These projections are not without precedent and analysis of current vulnerability and identification of adaptation constraints by Inuit in the two communities indicate the continued importance of traditional coping mechanisms. The ability to draw on these coping mechanisms in light of future climate change, however, will be unequal and the research indicates that young Inuit and those without access to economic resources, in particular, are vulnerable.     

Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem

Climate and land-use changes are projected to threaten biodiversity over this century. However, few studies have considered the spatial and temporal overlap of these threats to evaluate how ongoing land-use change could affect species ranges projected to shift outside conservation areas. We evaluated climate change and urban development effects on vegetation distribution in the Southwest ecoregion, California Floristic Province, USA. We also evaluated how well a conservation network protects suitable habitat for rare plant species under these change projections and identified primary sources of uncertainty. We used consensus-based maps from three species distribution models (SDMs) to project current and future suitable habitat for 19 species representing different functional types (defined by fire-response – obligate seeders, resprouting shrubs – and life forms – herbs, subshrubs), and range sizes (large/common, small/rare). We used one spatially explicit urban growth projection; two climate models, emission scenarios, and probability thresholds applied to SDMs; and high-resolution (90 m) environmental data. We projected that suitable habitat could disappear for 4 species and decrease for 15 by 2080. Averaged centroids of suitable habitat (all species) were projected to shift tens (up to hundreds) of kilometers. Herbs showed a small-projected response to climate change, while obligate seeders could suffer the greatest losses. Several rare species could lose suitable habitat inside conservation areas while increasing area outside. We concluded that (i) climate change is more important than urban development for vegetation habitat loss in this ecoregion through 2080 due to diminishing amounts of undeveloped private land in this region; (ii) the existing conservation plan, while extensive, may be inadequate to protect plant diversity under projected patterns of climate change and urban development, (iii) regional assessments of the dynamics of the drivers of biodiversity change based on high-resolution environmental data and consensus predictive mapping, such as this study, are necessary to identify the species expected to be the most vulnerable and to meaningfully inform regional-scale conservation.     

全球平均气温未来情景的降尺度分析

如何提高全球气候模拟数据的分辨率,以满足全球、区域乃至局地陆地生态系统全球变化响应的定量分析,是当今全球气候变化研究的核心内容之一。在全球尺度上,本文利用全球气象观测站点的气候数据和DEM 数据,对全球年平均气温与纬度和海拔高程之间相关性进行回归分析,建立全球气候降尺度空间模拟的统计转移函数,并与高精度曲面建模(HASM)方法进行集成,从而实现IPCC GCM HadCM3 的模拟数据从3.75° × 2.5°到 0.125° × 0.125°的降尺度处理。研究结果表明,在3 种气候情景的T1-T4 时段内,格陵兰岛平均气温在0℃以下的区域和南极洲平均气温在-35℃以下的区域均呈逐渐缩减趋势,赤道至南北回归线之间的平均气温大于40℃以上的区域呈逐渐增加趋势。其中,A1Fi 情景的平均气温上升速度最快,A2 情景次之,B2 情景的平均气温上升速度最慢。构建降尺度方法有效地将IPCC GCMs的粗分辨率的气候情景数据降尺度转换成高分辨率的气候数据,并克服和弥补了目前IPCC GCMs的模拟数据因分辨率低而不能对区域乃至局地气候变化的细节及趋势进行刻画的缺陷。     

柴达木盆地近50年来年气温、降水的小波分析

采用墨西哥帽小波函数,对柴达木盆地1954-2003年近50年年气温和年降水变化时间序列进行了小波分析,揭示了柴达木盆地气温、降水变化的多时间尺度的复杂结构,分析了不同时间尺度下气温、降水序列变化的周期和突变点,并根据主周期对未来温度、降水变化进行了预测。研究表明盆地年气温变化以12年周期振荡最强,年降水变化以9年周期振荡最强。在不同时间尺度上,年气温、年降水变化具有不同的对应关系,时间尺度越小,位相差异越小。     

气候变化下基于物种与植物耦联机制的小白额雁(Anser erythropus)潜在生境及适宜性研究--以长江流域中下游为例

气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。     

利用MaxEnt研究印度中部秃鹫栖息地适宜性及气候变化的影响

秃鹫提供了宝贵的生态系统服务,在生态系统平衡中发挥着重要作用,但印度本土秃鹫数量在过去几年有所下降。掌握秃鹫栖息地的分布现状对于管理和防止秃鹫数量继续下降至关重要。可以预见,目前的气候危机可能会进一步导致秃鹫生境适宜性的变化,并影响现存的秃鹫种群。因此,本研究利用物种分布模型,对印度中部一个秃鹫栖息地的短期和长期变化进行预测,并以统计和图形的方式呈现数据。选择MaxEnt软件进行预测,是因为它与其他模型相比具有一定的优势,如只使用现有数据,在数据不完整、样本量小、样本间隙小等情况下表现良好。采用全球气候模式集成学习算法(CCSM4、Had GEM2AO和MIROC5)以获得更好的预测结果。14个稳健模型(AUC 0.864–0.892)是利用7个秃鹫种群(长喙、白臀、红头、银灰色、埃及秃鹫、喜马拉雅和欧亚狮鹫)在两个季节共1000多个地点的数据建立的。选定的气候(温度和降水)和环境变量(NDVI、海拔和土地利用/土地覆盖)被用于预测当前栖息地,未来的预测只基于气候变量。影响秃鹫栖息地分布的最重要变量是降水量(bio 15,bio 18,bio19)和温度(bio 3,bio 5)。在目前的预测中,森林和水体是影响土地利用的主要因素。在较小尺度上,随着时间的推移,极端适宜的栖息地面积减少,高度适宜的栖息地面积增加,总适宜栖息地面积在2050年略有增加,但到2070年有所减少。在更大的尺度上考虑,2050年适宜栖息地的净损失为5%,2070年为7.17%(RCP4.5)。相似的,在RCP8.5下,2050年适宜栖息地的净损失为6%,2070年为7.3%。研究结果可用于制定秃鹫的保护规划和管理,从而保护其免受未来的气候变化等威胁。     

Relationships between Genetic Diversity of Vascular Plant Species and Climate Factors

Genetic diversity is crucial for plants to respond to global climate change, and exploring relationships between genetic diversity and climatic factors may help predict how global climate change will shape the genetic diversity of plants in the future. So far, however, the extent and magnitude of the impact of climatic factors on the genetic diversity of plants has not been clarified. We collected data from 68 published papers on two widely used measures of genetic diversity of populations (average expected heterozygosity (He) and average observed heterozygosity (Ho)) and on localities of populations of 79 vascular plants, and extracted data on 19 climatic factors from WorldClim. We then explored the relationships between measures of genetic diversity and climatic factors using linear regressions. He of plant populations was significantly correlated with climatic factors in 58.7% (44) of the 75 species that used He as a measure of genetic diversity, and Ho was correlated with climatic factors in 65.1% (41) of the 63 species that used this genetic diversity measure. In general, Mean Temperature of Wettest Quarter, Precipitation Seasonality, Precipitation of Driest Quarter and Temperature Seasonality played a vital role in shaping He, and Ho was mostly correlated with Precipitation of Warmest Quarter, Mean Temperature of Wettest Quarter, Precipitation of Driest Quarter and Precipitation of Driest Month. Also, the proportion of the significant correlations between genetic diversity of populations and climatic factors was higher for woody than for herbaceous species, and different climatic factors played different roles in shaping genetic diversity of these two growth forms. Our results suggest that climate may play an important role in shaping genetic diversity of plant populations, that climatic change in the future may alter genetic diversity of plants, and that genetic diversity of different plant forms may respond to climatic change differently.