产业集聚对雾霾污染与生态效率的非线性影响及溢出效应

新常态背景下，"降霾增效"是促进城市协调可持续发展的重要保障。基于2008-2017年我国269个地级市面板数据，利用ArcGIS空间分析、EBM-DEA、空间杜宾等模型，探究雾霾污染与生态效率的时空演化格局及产业集聚对其非线性影响及空间溢出效应。结果显示：（1）我国城市雾霾污染具有"块状"与"集群分布"特征，并呈现以京津冀城市群为中心的"核心-边缘"扩散模式；城市生态效率呈东部 > 中部 > 西部依次递减态势，其H-H型城市主要分布在东部沿海地区；（2）产业集聚是"双刃剑"，其对雾霾污染与生态效率的影响存在显著的"U"型关系，即产业集聚每提升1%，雾霾污染和生态效率相应降低0.1388%和0.1409%，产业集聚平方项每提升1%则相应提升0.0188%和0.0113%；（3）产业集聚进一步提升对本地与邻近城市的雾霾污染具有较强的正向空间溢出效应，地方政府应采取联防联控的污染治理策略，构建长效环境治理合作机制；（4）产业集聚规模对雾霾污染和生态效率的影响表现出一定的区域异质性，应设计差异化的产业发展策略，为城市"降霾增效"提供支撑；通过重构权重矩阵、替换核心解释变量与设置滞后变量，证明了上述主要结论的稳健性。当前我国正处于工业文明向生态文明转换的关键阶段，期望本研究能为区域可持续发展提供参考。     

Identifying the spatial effects and driving factors of urban PM2.5 pollution in China

Exploring exactly where air pollution comes from, and identifying the key factors that influence it, can provide a scientific basis for the rational formulation and effective implementation of air pollution policies in China. Based on the data from 2001 to 2012 covering PM_2.5 concentrations in 285 Chinese cities, we use dynamic spatial panel models to empirically analyze the key driving factors of this air pollution. Results show that China’s urban smog demonstrates both obvious global spatial autocorrelation and local spatial agglomeration. There is a significant inverted “U-shaped” curve between economic development level and air pollution, and most cities are in the phase in which pollution is increasing in conjunction with improvements to the economy. Due to a rapid increase in population in built up areas, a high-proportion of secondary industry, a coal-dominated energy structure and increasing traffic intensity, China’s smog problem is becoming more and more serious. FDI probably will not play a future role in mitigating the air pollution. Central heating in winter in northern China further aggravates local smog to a certain extent. Because China’s haze pollution presents path-dependent characteristics and spatial spillover effects in the time dimension and in the space dimension respectively, so smog alleviation policies should be implemented based both on the strategies of maximizing effort and regional joint prevention and control.     

吉林省县域环境污染的时空演变特征与影响因素

基于2011年和2015年环境污染物排放和经济社会数据,选取4类污染物的工业源、农业源和城镇生活源排放总量指标,通过构建整体环境污染综合指数和分来源污染指数综合反映吉林省县域尺度单元污染状况,运用Moran I指数、时空跃迁分析和标准差椭圆分析定量研究吉林省环境污染的时空演变特征,并构建空间计量模型对环境污染的影响因素进行分析.结果表明:吉林省环境污染具有空间集聚特征,环境污染主要分布在长春、吉林等中部地区,分来源的环境污染空间分布存在明显的区域差异特征;吉林省县域单元整体环境污染和农业源污染均具有空间相关性,环境污染空间布局的关联结构稳定性高,环境污染具有路径锁定特征;环境污染的空间分布呈现西北-东南分布格局,且环境污染表现出由中心向四周扩散态势,环境污染的重心在43.65-43.66°N,125.83-125.84°E之间变动;地区经济发展水平、城市化水平和农业生产是吉林省县域环境污染和工业源污染的主要驱动因素,产业结构的调整优化改善了整体环境污染与工业源污染状况.化肥的过度使用增加了农业源污染,经济发展水平和城市化水平是城镇生活源污染排放的主要驱动因素.县域整体环境污染和农业源污染均具有空间扩散效应,各自污染状况分别与相邻地区整体环境污染和农业源污染状况密切相关.     

长江中游城市群生态文明水平测度及时空演变

长江中游城市群在我国区域发展格局中占有重要地位,必须以生态文明为理念进行城市群的建设。使用熵权TOPSIS综合评价法测度长江中游城市群2009至2013年的生态文明水平;利用环境库兹涅茨曲线理论和障碍度模型解析城市群生态文明差异化格局的成因和重要影响因子;运用空间全局自相关方法分析城市群整体生态文明水平的空间聚集程度;借助Jenks自然最佳断裂点法对各地区生态文明状况进行聚类可视化分析。研究表现:(1)人均国内生产总值、人均居民社会消费品零售额、服务业增加值占GDP比重、人均水资源总量、城镇居民年人均可支配收入为5大影响长江中游城市群生态文明水平的重要因素。(2)武汉城市圈中武汉市生态文明水平颇佳,周边城市围绕武汉市呈圈层低值分布,"中心-外围"模式明显;环长株潭城市群展现长沙、株洲双核模式,一定程度上带动临近城市进行生态文明建设,但与相隔较远城市极化现象严重;环鄱阳湖城市群各地市间生态文明差异较小,5年来生态文明水平进步明显。(3)2009至2013年长江中游城市群生态文明聚类特征由微弱的负相关向微弱的正相关演变,并于2012年呈现出较强的集聚倾向。(4)襄阳市、宜昌市生态文明水平逐年下降,由生态文明库兹涅茨曲线的上方跌落至曲线下方,经济刺激对生态文明贡献偏低,九江市生态文明水平的保持与连续性较弱,波动性较大。     

城市化与生态系统服务的空间交互关系研究——以长株潭城市群为例

探索生态系统服务与城市化的空间交互关系为城市发展和保护提供新的视角。以长株潭城市群为例,以其2015年的土地利用、经济社会等数据为基础,利用格网分析和空间自相关模型解析城市化与生态系统服务的空间交互规律。结果表明:(1)长株潭城市群城市化水平空间分布区域差异性显著,城市化水平由高到低依次为城市化地区、正在城市化地区和生态绿心保护区,表现出从城市化地区向周边地区依次递减的态势。(2)受城市化水平和土地利用变化等影响,生态系统服务空间分布具有明显的差异性,并呈现出"中心-外围"逐步升高的趋势。(3)长株潭城市群城市化与各项生态系统服务之间呈显著负相关,由于驱动机制的不同,城市化地区、正在城市化地区和生态绿心保护区的城市化对生态系统服务的影响存在显著差异。(4)长株潭城市群的各项生态系统服务与城市化之间存在四种空间相关类型。高高集聚区和低低集聚区零散分布在整个研究区域,面积较小;高低集聚区分布在湘潭县西南部、株洲县东南部,面积较大;低高集聚区分布集中在城市化地区,呈现块状分布,面积较大。     

京津冀城市群地区影响城镇化的关键要素识别及其交互作用

中国的城镇化率随经济快速发展而迅速提高,由此导致的生态环境问题不断涌现,城镇化对区域生态环境的胁迫作用日益增加,城市可持续发展受到严峻挑战。目前城镇化和生态环境交互关系的关键影响因子仍不明确,而基于关键影响因子描述城镇化与生态环境要素交互胁迫作用的研究也较少。以京津冀城市群为研究区,使用城镇化率描述城镇化发展过程,使用相关分析初步总结了生态环境要素与城镇化过程的相关性,基于灰色关联分析方法求取了生态环境要素与不同城市城镇化率的关联度,使用方差分析法得到影响城镇化与生态环境交互胁迫的关键要素,最后明确了城市和生态环境要素交互胁迫作用的显著性。结果表明,水资源要素和生态要素与城镇化率相关性较弱;居民用电与城镇化过程的关联度最大、生活用水关联度最小;方差稳定性排名显示建成区面积关联度在各城市间最稳定,常住人口最不稳定;同类别要素间关联度差异不明显,可以将10要素合并为6要素;关联度的稳定性对识别关键要素有重要作用;城市和生态环境要素同时对要素关联度分布具有影响,二者存在显著的交互作用。本研究对明确生态环境对城镇化过程的影响模式,分析生态环境对城市群发展的限制或支撑作用提供参考。     

华北平原土地利用/覆盖对CO空间分布的调控作用

CO不仅是中国主要的空气污染物之一，还是温室效应的贡献者。农业用地每年消耗了大量的CO通量，土地利用/覆盖格局对于调控CO空间分布发挥了较大的作用。针对土地利用/覆盖调控CO空间分布开展研究，以华北平原为例揭示人类活动对CO空间异质性的影响。研究发现2010至2020年华北平原CO排放量由4964×10⁴ t降低至2683×10⁴ t,大部分耕地CO浓度由90 t/km²下降至45 t/km²以下。CO浓度空间集聚程度呈现先降低后升高趋势，Moran′s I指数由0.25增加至0.41。经济发展迅速的地区CO污染较为严重，北京和周边城市形成了CO污染高-高集聚区，周口和淮北等城市则形成了低-低集聚区。总体来看，CO浓度呈低-低集聚分布的区域不断扩大，反映出CO减排措施已经初见效果。研究表明土地利用/覆盖在类型与结构方面的差异影响了CO的排放、扩散以及氧化消耗，增加了大气CO收支的不确定性，对CO空间分布具有一定的调控作用。通过分析土地利用/覆盖与CO空间分布的关联性，探究土地利用/覆盖及景观格局对区...     

Intrinsic and extrinsic causes of spatial variability across scales in a metacommunity

The relative importance of extrinsic and intrinsic causes of variability is among the oldest unresolved problems in ecology. However, the interaction between large-scale intrinsic variability in species abundance and environmental heterogeneity is still unknown. We use a metacommunity model with disturbance-recovery dynamics to resolve the interaction between scales of environmental heterogeneity, biotic processes and of intrinsic variability. We explain how population density increases with environmental variability only when its scale matches that of intrinsic patterns of abundance, through their ability to develop in heterogeneous environments. Succession dynamics reveals how the strength of local species interactions, through its control of intrinsic variability, can in turn control the scale of metapopulation response to environmental scales. Our results show that the environment and species density might fail to show any correlation despite their strong causal association. They more generally suggest that the spatial scale of ecological processes might not be sufficient to build a predictive framework for spatially heterogeneous habitats, including marine reserve networks.     

“世博”背景下上海经济与环境的耦合演化

综合运用社会经济统计与环境监测数据,揭示了"世博"背景下,上海城市内部经济发展和环境保护关系的耦合演化特征。结果发现,2002-2010年各区县经济差异明显扩大。在总体差异中,主要表现为主城区内部和郊区内部差异,主城区和郊区间的差异较小;2006年后,主城区内部差异贡献进一步增加,郊区内部差异贡献开始下降,但各区环境质量有明显改善。2006年和2010年经济环境耦合关系都满足环境库兹涅兹曲线规律,但2010年拐点处的经济水平与环境质量都明显优于2006年,各区县分布格局差异较大。研究揭示了经济结构调整与全球化、多层次城市规划体系以及世博会影响是区域经济差异及环境库兹涅茨曲线演化的主要驱动因素。建议快速发展的城市应该加速产业转型升级、发挥产业布局与城市规划作用、抓住举办城市重大活动机遇,优化经济环境耦合关系,实现城市的可持续发展。     

Spatial flow analysis of water pollution in eco-natural systems

The disjunction of ecological and socioeconomic sciences is one of the main obstructions in current human–natural integrated systems research. Therefore, gridded GIS technology is introduced in an attempt to achieve the spatial flow analysis of water pollution in eco-natural systems. With this unified GIS platform, an input–output table and one-dimensional water quality model are chosen to manifest the spatial economic flows and spatial natural flows of water pollution separately. Finally, the comprehensive effect of the spatial circulation of water pollution in eco-natural systems is assessed. A case study of the framework is carried out in the Changzhou District of Taihu Lake, China, and the main results show the following: (1) COD (chemical oxygen demand) direct emissions represent the characteristics of high intensity and clustering in industrial regions; control unit 8 is the largest secondary emissions unit, representing up to 41.79% of the total, whereas the emissions of the primary industry tend to be low intensity and widespread. (2) The gray virtual water flow from the primary industry to other heavy industries (except the chemical industry) is the main flow type; the transfer amount adds up to 2512 t, and the inter-units with the largest occupation of water environment capacity (WEC) upstream to downstream are 8–9, nearly up to 1548 t. (3) Under the interaction of positive and negative functions of economic flows and natural flows, the final effect of pollution transfer may be offset, environmental degradation or environmental improvement. This study could provide a basis for ecological compensation, environmental exteriority and optimization of industrial structure layouts.     

成渝城市群城镇化与生态环境耦合协调及交互影响

以成都-重庆(简称成渝)城市群为研究对象,从经济、社会、生态和城乡协调4个子系统构建城镇化综合评价指标体系,将生态环境承载力和生态弹性结合构建生态环境综合评价指标体系,应用耦合协调度模型测度2005—2018年成渝城市群各地级市城镇化与生态环境的耦合协调度,借助GIS空间分析法、象限分析法和Tapio模型,分析成渝城市群各地级市城镇化与生态环境交互作用的类型、演化路径及其解耦路径。结果表明: 研究期间,成渝城市群的城镇化质量呈现波动上升趋势,以成都、重庆为高值区呈“双核”向四周辐射;生态环境质量缓慢提升,呈四周高、中部低,开口向北的“U”型空间格局。城镇化系统和生态环境系统耦合协调水平较高,总体呈上升的趋势,协调类型由以濒临失调和勉强协调为主逐渐向以中度协调为主演变,呈现中部低、东西高的空间格局。城镇化与生态环境交互作用的演化路径呈现稳定型和变化型2个大类。稳定型包括5个亚类20个城市,成都、德阳、绵阳等城市始终是良好协调型;变化型包括9个亚类16个城市,重庆主城区、铜梁等多数城市的协调度提升,呈“上升式”发展;合川、自贡等少数城市呈“下沉式”发展。生态环境增长率和城镇化增长率均为正,城镇化与生态环境的解耦路径以弱脱钩和扩张连接为主。     

Examining determinants of geographic variation in colorectal cancer mortality in North Carolina: A spatial analysis approach

PurposeA recent study using national data from 2000 to 2009 identified colorectal cancer (CRC) mortality “hotspots” in 11 counties of North Carolina (NC). In this study, we used more recent, state-specific data to investigate the county-level determinants of geographic variation in NC through a geospatial analytic approach.MethodUsing NC CRC mortality data from 2003 to 2013, we first conducted clustering analysis to confirm spatial dependence. Spatial economic models were then used to incorporate spatial structure to estimate the association between determinants and CRC mortality. We included county-level data on socio-demographic characteristics, access and quality of healthcare, behavioral risk factors (CRC screening, obesity, and cigarette smoking), and urbanicity. Due to correlation among screening, obesity and quality of healthcare, we combined these factors to form a cumulative risk group variable in the analysis.ResultsWe confirmed the existence of spatial dependence and identified clusters of elevated CRC mortality rates in NC counties. Using a spatial lag model, we found significant interaction effect between CRC risk groups and socioeconomic deprivation. Higher CRC mortality rates were also associated with rural counties with large towns compared to urban counties.ConclusionOur findings depicted a spatial diffusion process of CRC mortality rates across NC counties, demonstrated intertwined effects between SES deprivation and behavioral risks in shaping CRC mortality at area-level, and identified counties with high CRC mortality that were also deprived in multiple factors. These results suggest interventions to reduce geographic variation in CRC mortality should develop multifaceted strategies and work through shared resources in neighboring areas.     

京津冀城市群人-地、人-水与人-碳交互胁迫关系及其叠加效应

随着社会、经济效益的不断增加及国际影响力的不断增大，京津冀正在向世界级城市群迈进。而快速的城市增长与资源环境的交互胁迫效应严重制约了京津冀地区的可持续发展，因此，明确城市增长与不同资源环境要素的相互作用机制并采用有效的措施，是实现京津冀地区发展和保护共生的关键。目前针对城镇化与单一种资源环境要素交互作用的研究较多，但对城镇化与不同资源环境要素相互作用的叠加效应的关注很少。针对土地、水资源与能源这三种明显限制京津冀地区发展的资源要素，综合考虑了供给侧与需求侧特征，分析了人-地、人-水与人-碳的相互作用关系，解析了京津冀地区城镇发展与不同资源环境要素交互胁迫作用及其叠加效应。结果表明：2002-2017年，1、城市群整体水平上，人-地、人-水和人-碳关系总体上均呈"强协调"或"弱协调"交替变化的状态；2、城市尺度上，不同城市的人-地、人-水和人-碳交互关系存在明显时空分异。多数城市都曾面临土地、水资源或能源的胁迫影响，尤其是河北的一些城市（石家庄、邯郸、承德、衡水、邢台、唐山及保定等）在有些年份面临土地、水资源或能源的"强胁迫"影响；3、从京津冀地区整体水平上看，不存在多种资源要素的叠加胁迫影响，但是，城市群内部多数城市在有的年份同时面临土地、水资源或能源两种以上资源要素的叠加胁迫影响。因此，要协同改善京津冀地区资源环境的胁迫，需要全面考虑不同空间尺度之间，不同城市之间，以及不同资源要素之间的叠加影响机制，有针对性的提出政策与措施。     

长三角城市群城市空间形态与碳收支时空耦合关系

区域碳收支动态监测与评估是推动城市群低碳发展和碳达峰的关键基础问题。设计和分析了长三角城市群区域碳收支与城市空间形态的时空耦合关系。基于2001、2005和2010年碳排放、净初级生产力、土地利用和土壤等数据构建了长三角城市群区域碳收支的时空分布估算模型,接着利用地理加权回归模型分析了城市空间形态景观格局指数与碳收支的相关性,最后结合地理探测器定量分析了景观格局指数因子对碳收支的影响及其交互作用。研究结果表明：（1）长三角城市群碳收支存在明显的空间异质性,总体呈现南部高,北部次之,东部低的特征;（2）同时,长三角城市群碳收支具有明显时间异质性,2001、2005和2010年呈现减少的趋势,其中2001-2005年下降幅度较大;（3）斑块类型面积、城市斑块数量、最大斑块指数、景观形状指数与碳收支具有负相关性;边缘密度、城市建成区斑块密度与碳收支具有显著正相关性;（4）2001年、2005年和2010年的建成区总面积是碳收支空间异质性的主要驱动因素;斑块类型面积与其他因子的交互作用对碳收支空间异质性影响贡献程度比其他因子间交互作用较强。一定程度揭示了城市空间形态景观格局与碳收支时空分布的相关性,可为碳达峰/碳中和、城市形态优化等提供科学参考。     

Synchrony of spatial populations: heterogeneous population dynamics and reddened environmental noise

Many species exhibit widespread spatial synchrony in population fluctuations. This pattern is of great ecological interest and can be a source of concern when a species is rare or endangered. Moran’s theorem suggests that if two (or more) populations sharing a common linear density-dependence in the renewal process are disturbed with correlated noise, they will become synchronized with correlation matching the noise correlation. In this report, correlation of nonidentical populations that are described by linear and stationary autoregressive processes is analyzed. We show that the expected spatial synchrony between two populations can be decomposed into two multiplicative components. One is the demographic component related to the values of the autoregressive coefficients and the noise color. The other is the spatial correlation of the environmental colored noise. The main results are consistent with the predictions of previous experiments and simulations, and the importance of this report is to provide theoretical support.     

Forest age correlates with fine-scale spatial structure of Matsutake mycorrhizas

Examining the fine-scale spatial structure of fungal populations can tell us much about how individual species reproduce and disperse throughout natural landscapes. Here we study the fine-scale genetic structure of Tricholoma matsutake, a prized edible and medicinal mushroom, by systematic sampling of mycorrhizas within fairy rings in 50-y-old and old-growth forests in two villages. Using single nucleotide polymorphism DNA markers we show that mycorrhizas in both forest age classes in both villages showed high levels of genotypic diversity, consistent with a reproductive life history predominated by outcrossing via basidiospore dispersal. Both the percentage of polymorphic loci within fairy rings, as well as genotype diversity were higher in old-growth compared to 50-y-old forests. Fifty-year-old forests showed significant spatial autocorrelation between pairs of mycorrhizas up to 42 m, and a pattern consistent isolation-by-distance structure. Spatial patterns in old-growth forests were random. Furthermore, AMOVA analysis indicates that 11 % of molecular variance in 50-y-old forests is partitioned between villages, whereas no significant variance is partitioned between villages in old-growth forests. We conclude that populations of T. matsutake in 50-y-old forests are the result of a founder effect maintained by local inoculation sources. This pattern attenuates as forests age and accumulate inocula from more distance sources. We speculate on how genetic mosaicism within T. matsutake fairy rings may structure populations within a chronosequence. Finally, we discuss how population spatial dynamics and dispersal strategy in T. matsutake contrast with other ectomycorrhizal species.     

京津冀城市群空间扩张及其经济溢出效应

随着我国城市化的快速发展,区域城市之间的联系逐渐加强,不同的扩张模式对城市间经济增长溢出效应会产生不同的影响。基于Capello模型,计算了京津冀城市群地区13个城市扩张带来的经济增长溢出效应,通过比较扇状扩张城市和轴向扩张城市得到和给出的城市增长溢出效应,研究了不同扩张类型城市溢出效应的差异,以及京津冀地区经济增长溢出效应的空间分布特征。结果表明,京津冀城市群地区城市间经济增长溢出效应明显,北京和天津给出的溢出效应远高于其他城市,扇状扩张城市比轴向扩张城市更有利于城市之间的增长效益溢出。京津冀地区已经形成了以北京、天津、廊坊和唐山为中心的核心区,石家庄、保定为核心的次级核心区,位于城市群边缘的城市与核心城市联系较弱,在未来的城市群发展中,可通过政策和规划优化城市形态,使城市空间形态更有利于城市经济发展。     

城市群地区城市高质量发展与生态环境的交互协同作用——以成渝城市群为例

高质量发展与生态环境交互作用的研究是实现可持续发展和建设美丽中国的关键议题。选取成渝地区36个市县为研究单元，以2005年、2010年、2015年和2018年为主要研究时间节点。基于可持续发展和美丽中国理念构建成渝城市群高质量发展评价指标体系，借鉴压力-状态-响应模型构建生态环境质量评价指标体系，应用熵权法测度城市高质量发展水平和生态环境质量水平；运用耦合协调度模型测度二者的耦合协调关系；利用地理探测器和社会网络分析法分析各因子交互作用类型及强度。结果表明：（1）成渝城市群城市高质量发展与生态环境耦合度高，交互影响作用显著；耦合协调水平较低，以低水平耦合协调为主，呈现明显的双核心空间结构。（2）城镇化与生态环境两系统间的因子交互作用强于各系统内部因子交互作用，系统间的因子交互作用呈现显著的非线性增强，系统内因子以双因子增强为主，系统间存在较强交互协同效应，各子系统交互作用存在明显的"涌现现象"和"蝴蝶效应"。（3）生态环境系统在与城镇系统的交互作用中发挥主导作用，生态环境水平、生态环境压力为关键交互因子；资源禀赋、生态保护、资源消耗、环境水平、创新力量、文化传承等为主要子因子。研究深刻解析成渝城市群城镇化与生态环境的交互协同模式，以期为成渝城市群的高质量发展提供科学参考。     

Spatial metrics as indicators of biodegradation benefits from bacterial dispersal networks

Ecological dynamics often show intricate variations in response to different spatial configurations of environmental conditions. For instance, efficient turnover of natural or anthropogenic compounds in soils strongly depends on the bioavailability of these compounds to metabolically active bacteria. Experimental and modelling studies have highlighted that fungal networks may considerably enhance bioavailability by facilitating bacterial dispersal. Therefore, such dispersal networks may play a key role in many soil processes, for example, in contaminant degradation. Particularly, simulation studies revealed that the spatial configurations of networks may be a crucial factor determining the bacterial access to contaminants. Since these spatial configurations are typically complex and not precisely known, suitable metrics describing them in an aggregated manner are required for assessing expected biodegradation benefits from different bacterial dispersal networks. Using a spatially explicit microbial model we randomly created various dispersal network configurations and simulated the resulting bacterial degradation of organic compounds. We investigated numerous spatial metrics for characterizing the manifold network configurations, and identified appropriate metrics based on nonparametric correlation measures. Our results show that single metrics can approximately indicate biodegradation performance, and that well-chosen combinations of two metrics offer very good assessments. Thus, our analysis provides characteristics to focus on when dealing with real fungal networks in future practical applications in environmental management. Moreover, the protocol we employed for deriving the appropriate metrics is suited to be adapted to other ecological studies of functional responses to spatial environmental characteristics, for instance, changes in ecosystem services or biodiversity aspects due to habitat loss and fragmentation.     

Do migratory or demographic disruptions rule the population impact of pollution in spatial networks?

Ecotoxicology supplies environmental quality criteria mainly based on the potential effects of contaminants on demographic rates of natural populations. Possible impacts through pollutant-induced disruptions of spatial behaviors are totally neglected. Should it be significant to take into account this "second way"? We developed the example of a hypothetical brown trout population living in a river network. We analyzed how behaviors of toxic avoidance or attraction during the spawning migration alter the impact of pollution. Attraction behaviors basically enhanced the bad effect of pollution. More interesting, avoidance behaviors can weakly lift the asymptotic population growth rate, while if there is density-dependent effects on recruitment, pollutant avoidance can actually lead to a substantial drop in equilibrium size. Our model allowed comparing the relative significance of migratory and demographic disruptions for explaining the population impacts of pollution; we thus stress on the need of increasing efforts to develop knowledge relative to toxicant-induced spatial behaviors and to integrate such effects in the definition of environmental quality criteria.