A simple non-separable,non-stationary spatiotemporal model for ozone

The past two decades have witnessed an increasing interest in the use of space-time models for a wide range of environmental problems. The fundamental tool used to embody both the temporal and spatial components of the phenomenon in question is the covariance model. The empirical estimation of space-time covariance models can prove highly complex if simplifying assumptions are not employed. For this reason, many studies assume both spatiotemporal stationarity, and the separability of spatial and temporal components. This second assumption is often unrealistic from the empirical point of view. This paper proposes the use of a model in which non-separability arises from temporal non-stationarity. The model is used to analyze tropospheric ozone data from the Emilia-Romagna Region of Italy.     

Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act

In 2014, the Fish and Wildlife Service (FWS) and National Marine Fisheries Service announced a new policy interpretation for the U.S. Endangered Species Act (ESA). According to the act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range (SPR). The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals’ “removal would cause the entire species to become endangered or threatened.” We reviewed 20 quantitative techniques used to assess whether a portion of a species’ range is significant according to the new guidance. Our assessments are based on the 3R criteria—redundancy (i.e., buffering from catastrophe), resiliency (i.e., ability to withstand stochasticity), and representation (i.e., ability to evolve)—that the FWS uses to determine if a species merits listing. We identified data needs for each quantitative technique and considered which methods could be implemented given the data limitations typical of rare species. We also identified proxies for the 3Rs that may be used with limited data. To assess potential data availability, we evaluated 7 example species by accessing data in their species status assessments, which document all the information used during a listing decision. In all species, an SPR could be evaluated with at least one metric for each of the 3Rs robustly or with substantial assumptions. Resiliency assessments appeared most constrained by limited data, and many species lacked information on connectivity between subpopulations, genetic variation, and spatial variability in vital rates. These data gaps will likely make SPR assessments for species with complex life histories or that cross national boundaries difficult. Although we reviewed techniques for the ESA, other countries require identification of significant areas and could benefit from this research.     

Spatiotemporal variation in survival rates: implications for population dynamics of yellow-bellied marmots

Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.     

The promise of Beijing: Evaluating the impact of the 2008 Olympic Games on air quality

To prepare for the 2008 Olympic Games, China adopted a number of radical measures to improve air quality. Using the officially reported air pollution index (API) from 2000 to 2009, we show that these measures improved the API of Beijing during and a little after the Games, but a significant proportion of the effect faded away by October 2009. For comparison, we also analyze an objective and indirect measure of air quality at a high spatial resolution – aerosol optimal depth (AOD), derived using the data from NASA satellites. The AOD analysis confirms the real but temporary improvement in air quality, it also shows a significant correlation between air quality improvement and the timing and location of plant closure and traffic control. These results suggest that it is possible to achieve real environmental improvement via stringent policy interventions, but for how long the effects of these interventions will last will largely depend on the continuation of the interventions.     

厦门市PM10浓度空间与时间差异分析

在厦门市环境大气污染物中,PM10是其首要的大气污染物。厦门市大气中的PM10浓度受天气和气候以及土地利用类型、交通排放、工业状况等诸多自然因素和人为因素的共同影响而呈现出一定的时空变化规律,文章对厦门市2001年至2002年PM10浓度的空间变化和时间变化特点进行了分析,揭示了影响厦门市环境大气中PM10浓度空间变化和不同尺度的时间变化的影响因素。     

Modelling the spatial structure of forest stands by multivariate point processes with hierarchical interactions

A stochastic model is applied to describe the spatial structure of a forest stand. We aim at quantifying the strength of the competition process between the trees in terms of interaction within and between different size classes of trees using multivariate Gibbs point processes with hierarchical interactions introduced in [Högmander, H., Särkkä, A., 1999. Multitype spatial point patterns with hierarchical interactions. Biometrics 55, 1051–1058]. The new model overcomes the main limitation of the traditional use of the Gibbs models allowing to describe systems with non-symmetric interactions between different objects. When analyzing interactions between neighbouring trees it is natural to assume that the size of a tree determines its hierarchical level: the largest trees are not influenced by any other trees than the trees in the same size class, while trees in the other size classes are influenced by the other trees in the same class as well as by all larger trees. In this paper, we describe a wide range of Gibbs models with both hierarchical and non-hierarchical interactions as well as a simulation algorithm and a parameter estimation procedure for the hierarchical models. We apply the hierarchical interaction model to the analysis of forest data consisting of locations and diameters of tree stems.     

Temporal, spatial, and between-host comparisons of patterns of parasitism in lake zooplankton

In nature, multiple parasite species infect multiple host species and are influenced by processes operating across different spatial and temporal scales. Data sets incorporating these complexities offer exciting opportunities to examine factors that shape epidemics. We present a method using generalized linear mixed models in a multilevel modeling framework to analyze patterns of variances and correlations in binomially distributed prevalence data. We then apply it to a multi-lake, multiyear data set involving two Daphnia host species and nine microparasite species. We found that the largest source of variation in parasite prevalence was the species identities of host-parasite pairs, indicating strong host-parasite specificity. Within host-parasite combinations, spatial variation (among lakes) exceeded interannual variation. This suggests that factors promoting differences among lakes (e.g., habitat characteristics and species interactions) better explain variation in peak infection prevalence in our data set than factors driving differences among years (e.g., climate). Prevalences of parasites in D. dentifera were more positively correlated than those for D. pulicaria, suggesting that similar factors influenced epidemic size among parasites in D. dentifera. Overall, this study demonstrates a method for parsing patterns of variation and covariation in infection prevalence data, providing greater insight into the relative importance of different underlying drivers of parasitism.     

近10年中国大陆MODlS遥感气溶胶光学厚度特征

应用2001-2010年MODIS大气气溶胶光学厚度（AOD）资料,分析中国550nmAOD年和季节平均分布。还选取了10个代表性区域,分析AOD变化特征。这些分析建立起了近10年来中国气溶胶光学厚度的气候学特征：中国年平均AOD空间区域分布中心大体呈现两低两高。两低中心位于植被覆盖度高和人烟稀少的（1）黑龙江和内蒙古东北高纬度地区（－0．2）;（2）川、滇与青藏高原交界的西南高海拔地区（0．1-0．2）。一个AOD低值带（0．2－0．3）连接这两个低中心,呈东北西南走向跨过中国大陆。在此低值带两侧,各有一片AOD高值中心（－0．8）：（1）人口密集和工业化发展带来的大量人为气溶胶形成了一个覆盖了华北、长江流域（从四川盆地,两湖地区到长三角）到华南珠江三角洲相联的大片高AOD中心区域;（2）以沙尘为主的自然气气溶胶造就了西北塔克拉玛干沙漠及周边高AOD区。中国AOD这一两低两高区域分布特征基本保持四季不变,但其中心强度呈现各自区域性季节变化。中国春季AOD高值区的面积最大,其次是夏季,然后是秋季,面积最小的是冬季。南方AOD月变化规律多为双峰型,即3－5和8－9月出现2次高峰,5－7月从南向北先后出现波谷,变化规律与季风响应。北方为单峰型,6－7月为高峰,11到来年2月为低谷。用弱季风年（2002）和强季风年（2003）季风影响区域气象条件和气溶胶数据对比分析表明,大陆AOD的月空间分布和变化与季风气候,以及风速、风向、降水、温度和湿度等的变化有关。     

Spatial anatomy of species survival: effects of predation and climate-driven environmental variability

The majority of survival analyses focus on temporal scales. Consequently, there is a limited understanding of how species survival varies over space and, ultimately, how spatial variability in the environment affects the temporal dynamics of species abundance. Using data from the Barents Sea, we study the spatiotemporal variability of the juvenile Atlantic cod (Gadus morhua) survival. We develop an index of spatial survival based on changes of juvenile cod distribution through their first winter of life (from age-0 to age-1) and study its variability in relation to biotic and abiotic factors. Over the 25 years analyzed (1980-2004), we found that, once the effect of passive drift due to dominant currents is accounted for, the area where age-0 cod survival was lowest coincided with the area of highest abundance of older cod. Within this critical region, the survival of age-0 cod was negatively affected by its own abundance, by that of older cod, and by bottom depth. Furthermore, during cold years, age-0 cod survival increased in the eastern and coldest portion of the examined area, which was typically avoided by older conspecifics. Based on these results we propose that within the examined area top-down mechanisms and predation-driven density dependence can strongly affect the spatial pattern of age-0 cod survival. Climate-related variables can also influence the spatial survival of age-0 cod by affecting their distribution and that of their predators. Results from these and similar studies, focusing on the spatial variability of survival rates, can be used to characterize species habitat quality of marine renewable resources.     

近10年中国大陆MODIS遥感气溶胶光学厚度特征

应用2001—2010年MODIS大气气溶胶光学厚度(AOD)资料,分析中国550 nm AOD年和季节平均分布。还选取了10个代表性区域,分析AOD变化特征。这些分析建立起了近10年来中国气溶胶光学厚度的气候学特征:中国年平均AOD空间区域分布中心大体呈现两低两高。两低中心位于植被覆盖度高和人烟稀少的(1)黑龙江和内蒙古东北高纬度地区(～0.2);(2)川、滇与青藏高原交界的西南高海拔地区(0.1～0.2)。一个AOD低值带(0.2～0.3)连接这两个低中心,呈东北西南走向跨过中国大陆。在此低值带两侧,各有一片AOD高值中心(～0.8):(1)人口密集和工业化发展带来的大量人为气溶胶形成了一个覆盖了华北、长江流域(从四川盆地,两湖地区到长三角)到华南珠江三角洲相联的大片高AOD中心区域;(2)以沙尘为主的自然气气溶胶造就了西北塔克拉玛干沙漠及周边高AOD区。中国AOD这一两低两高区域分布特征基本保持四季不变,但其中心强度呈现各自区域性季节变化。中国春季AOD高值区的面积最大,其次是夏季,然后是秋季,面积最小的是冬季。南方AOD月变化规律多为双峰型,即3—5和8—9月出现2次高峰,5—7月从南向北先后出现波谷,变化规律与季风响应。北方为单峰型,6—7月为高峰,11到来年2月为低谷。用弱季风年(2002)和强季风年(2003)季风影响区域气象条件和气溶胶数据对比分析表明,大陆AOD的月空间分布和变化与季风气候,以及风速、风向、降水、温度和湿度等的变化有关。     

Importance of timely metadata curation to the global surveillance of genetic diversity

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.     

Sampling variability and estimates of density dependence: a composite-likelihood approach

It is well known that sampling variability, if not properly taken into account, affects various ecologically important analyses. Statistical inference for stochastic population dynamics models is difficult when, in addition to the process error, there is also sampling error. The standard maximum-likelihood approach suffers from large computational burden. In this paper, I discuss an application of the composite-likelihood method for estimation of the parameters of the Gompertz model in the presence of sampling variability. The main advantage of the method of composite likelihood is that it reduces the computational burden substantially with little loss of statistical efficiency. Missing observations are a common problem with many ecological time series. The method of composite likelihood can accommodate missing observations in a straightforward fashion. Environmental conditions also affect the parameters of stochastic population dynamics models. This method is shown to handle such nonstationary population dynamics processes as well. Many ecological time series are short, and statistical inferences based on such short time series tend to be less precise. However, spatial replications of short time series provide an opportunity to increase the effective sample size. Application of likelihood-based methods for spatial time-series data for population dynamics models is computationally prohibitive. The method of composite likelihood is shown to have significantly less computational burden, making it possible to analyze large spatial time-series data. After discussing the methodology in general terms, I illustrate its use by analyzing a time series of counts of American Redstart (Setophaga ruticilla) from the Breeding Bird Survey data, San Joaquin kit fox (Vulpes macrotis mutica) population abundance data, and spatial time series of Bull trout (Salvelinus confluentus) redds count data.     

Determinants of male spacing behavior in microtines: an experimental manipulation of female spatial distribution and density

Theory on microtine mating systems predicts that male spacing behavior will be related to female spatial and temporal distribution. However, data from a natural population of field voles, Microtus agrestis, indicated a potential influence of female density on the spacing behavior of males. Therefore, I experimentally investigated the relative importance of female density and female spatial distribution for the spacing behavior of males in M. agrestis. Males were radio-tracked in enclosed natural habitats in which females at different densities were placed in two different spatial arrangements: clumped versus even distribution. Female density was the main factor determining male spacing behavior. At the high female density males had smaller home ranges and moved shorter distances between radio-tracking recordings. Also, home ranges were more exclusive at high female density. However, since there was a significant positive correlation between home range size and range overlap, range exclusiveness seemed to be influenced by female density indirectly through the effect of range size. Female spatial distribution, on the other hand, had no influence on male home range exclusiveness.     

Climate and predation dominate juvenile and adult recruitment in a turtle with temperature-dependent sex determination

Conditions experienced early in life can influence phenotypes in ecologically important ways, as exemplified by organisms with environmental sex determination. For organisms with temperature-dependent sex determination (TSD), variation in nest temperatures induces phenotypic variation that could impact population growth rates. In environments that vary over space and time, how does this variation influence key demographic parameters (cohort sex ratio and hatchling recruitment) in early life stages of populations exhibiting TSD? We leverage a 17-year data set on a population of painted turtles, Chrysemys picta, to investigate how spatial variation in nest vegetation cover and temporal variation in climate influence early life-history demography. We found that spatial variation in nest cover strongly influenced nest temperature and sex ratio, but was not correlated with clutch size, nest predation, total nest failure, or hatching success. Temporal variation in climate influenced percentage of total nest failure and cohort sex ratio, but not depredation rate, mean clutch size, or mean hatching success. Total hatchling recruitment in a year was influenced primarily by temporal variation in climate-independent factors, number of nests constructed, and depredation rate. Recruitment of female hatchlings was determined by stochastic variation in nest depredation and annual climate and also by the total nest production. Overall population demography depends more strongly on annual variation in climate and predation than it does on the intricacies of nest-specific biology. Finally, we demonstrate that recruitment of female hatchlings translates into recruitment of breeding females into the population, thus linking climate (and other) effects on early life stages to adult demographics.     

Inferring evolutionary signals from ecological data in a plant-pathogen metapopulation

We followed the dynamics of local epidemics in three populations of a natural plant-pathogen system for four sequential years. We characterize the overwintering process with spatial statistics and use a stochastic, spatially explicit, modeling approach with Bayesian parameter estimation to study the spread of the infection during the growing season. Our modeling approach allows us to infer coevolutionary signals from spatiotemporal data on pathogen prevalence. Most importantly, we are able to assess the distribution of resistant hosts within the distribution of all host plants. We show that resistant hosts occur in areas with high pathogen encounter rates, and that the occurrence of resistance correlates with overwintering probability of the pathogen. The estimates for essentially all model parameters are characterized by a large amount of variation over the years and the populations. While the variation in the fraction of resistant hosts and in the force of infection is to a large extent explained by the population, the other model parameters (two parameters describing the shape of the dispersal kernel) vary essentially in an unpredictable manner, suggesting that much of the variation may occur at very fine spatial and temporal scales.     

Ecological sexual segregation in fallow deer (Dama dama): a multispatial and multitemporal approach

We questioned the different interpretations of ecological sexual segregation from a novel perspective, i.e., by carrying out diverse temporal and spatial scale analyses within a long-term study (1984–2003). Thus we combined spatial (small/large) and temporal (small/large) scale analyses to identify the factors generating sexual segregation in fallow deer in San Rossore, Italy. The study site was divided into an eastern sector characterized by human disturbance (DS) and a western undisturbed sector (US). According to census data, human presence increased in DS from 1984, and while females gradually abandoned it, males remained—thus supporting the predation risk hypothesis (large spatial and temporal scale)—and actually increased their presence in DS, where they seemingly benefited from a lower female density. This supported the indirect competition hypothesis. The analysis of data on a large temporal and small spatial scale confirmed that intersexual competition, in particular for grass, was higher in a crowded pasture in US. Observations by means of radio-telemetry of 23 adult females and 25 adult males (1997–2001, reduced temporal and large spatial scale) showed that large scale segregation was relevant during the day and disappeared at night, when disturbance was absent and also the females reached DS. This also supported the predation risk hypothesis. Moreover, sexes showed different habitat choices inside DS at night, thus supporting the forage selection hypothesis (small spatial and temporal scale). In conclusion, failure to address the whole set of combinations of spatial and temporal scale analyses would have led to monocausal explanations of ecological sexual segregation.     

Changes in body size, abundance, and energy allocation in rockfish assemblages of the northeast Pacific.

Fish body size, a key driver of many aspects of fish population biology and ecology, is affected by fisheries that deplete the largest individuals. Rockfish (genus Sebastes) are a diverse group that has been heavily fished on the U.S. West Coast in recent decades. We examined trawl survey data from 1980 to 2001 to determine spatial and temporal trends in body size and density of 16 shelf rockfish species, including six that are considered overfished. Mean individual mass and maximum observed mass declined in the majority of species in one or more zoogeographic regions between central California and Washington. Density changes were far more variable in time and space, but in all regions, density declines were most often associated with large-bodied rockfish. We next estimated the impact of size and density changes on energy consumption and fecundity in a five-species rockfish assemblage that includes bocaccio (S. paucispinis), a large-bodied, overfished species. Indexes of both consumption and fecundity by the assemblage increased in the southern portion of the study area between 1980 and 2001 but decreased in the northern portion. Allocation of energy and reproductive potential within the assemblage shifted dramatically: relative to bocaccio, total energy consumption and fecundity indexes for the other four species increased by orders of magnitude from 1980 to 2001. These changes in community structure may affect the ability of bocaccio and other large rockfish species to recover from overfishing, especially in light of long-term declines in zooplankton production that may also be affecting rockfish size and production. Addressing these issues may require a regional, multispecies management approach.     

Untested assumptions about within-species sample size and missing data in interspecific studies

Phylogenetic comparative studies rely on species-specific data that often contain missing values and/or differ in sample size among species. These phenomena may violate statistical assumptions about the non-random variance component in sampling effort. A major reason why this assumption is often not fulfilled is because the probability of being sampled (i.e., being captured or observed) may depend on species-specific characteristics. Here, we test this assumption by using information on within-species sample sizes and missing data from five independent comparative datasets of European birds. First, we show that the two estimates of data availability (missing values and within-species sample size) are positively correlated and are associated with research effort in general (the number of papers published). Second, we demonstrate biologically meaningful relationships between data availability and phenotypic traits. For example, population size, risk-taking, and habitat specialization independently predicted within-species sample size. The key determinants of missing data were population size and distribution range. However, data availability was not structured by phylogenetic relationships. These results indicate that the accuracy of sampling is repeatable and distributed non-randomly among species, as several species-specific attributes determined the probability of observation. Therefore, data availability seems to be a species-specific trait that can be shaped by ecology, life history, and behavior. Such relationships raise issues about non-random sampling, which requires attention in comparative studies.     

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.