Climatic regime shifts and decadal-scale variability in calanoid copepod populations off southern California

Decadal‐scale climatic regimes and the shifts between them have important impacts on marine ecosystems. Climatic regime shifts have been observed or hypothesized in the North Pacific basin in 1976–77 and 1989. This paper examines long‐term (1951–99) trends in calanoid copepod populations off southern California, and the evidence for responses to regime shifts. Most of the species of calanoid copepod that were analysed underwent one or more step changes during the 49 years covered by the study. All but one of these changes occurred in five periods: the late 1950s, late 1960s, mid‐1970s, early 1980s and around 1990. The late 1960s changes are considered to be artifacts of an increase in sampling depth. Strong El Niño conditions affected California waters during the late 1950s and early 1980s. The step changes of the mid‐1970s and late 1980s to early 1990s may have been responses to regime shifts or other climatic events. 28% of the species and subspecies responded to the 1976–77 event, all increasing in abundance. Another 28% of the copepod categories underwent step changes around 1990, most decreasing. Evidence for regime shifts in the hydrographic variables that were examined is mixed. The 10‐m temperature increased in the mid‐1970s. Abrupt changes in variables around 1990 were short‐lived. However, the population responses around 1990 and to the El Niños of the late 1950s and early 1980s indicate that some species of calanoid copepods may respond on longer time scales to environmental conditions that persist only a few years.     

Synchronous marine pelagic regime shifts in the Northern Hemisphere

Regime shifts are characterized by sudden, substantial and temporally persistent changes in the state of an ecosystem. They involve major biological modifications and often have important implications for exploited living resources. In this study, we examine whether regime shifts observed in 11 marine systems from two oceans and three regional seas in the Northern Hemisphere (NH) are synchronous, applying the same methodology to all. We primarily infer marine pelagic regime shifts from abrupt shifts in zooplankton assemblages, with the exception of the East Pacific where ecosystem changes are inferred from fish. Our analyses provide evidence for quasi-synchronicity of marine pelagic regime shifts both within and between ocean basins, although these shifts lie embedded within considerable regional variability at both year-to-year and lower-frequency time scales. In particular, a regime shift was detected in the late 1980s in many studied marine regions, although the exact year of the observed shift varied somewhat from one basin to another. Another regime shift was also identified in the mid- to late 1970s but concerned less marine regions. We subsequently analyse the main biological signals in relation to changes in NH temperature and pressure anomalies. The results suggest that the main factor synchronizing regime shifts on large scales is NH temperature; however, changes in atmospheric circulation also appear important. We propose that this quasi-synchronous shift could represent the variably lagged biological response in each ecosystem to a large-scale, NH change of the climatic system, involving both an increase in NH temperature and a strongly positive phase of the Arctic Oscillation. Further investigation is needed to determine the relative roles of changes in temperature and atmospheric pressure patterns and their resultant teleconnections in synchronizing regime shifts at large scales.     

Robustness of early warning signals of regime shifts in time-delayed ecological models

Various ecological and other complex dynamical systems may exhibit abrupt regime shifts or critical transitions, wherein they reorganize from one stable state to another over relatively short time scales. Because of potential losses to ecosystem services, forecasting such unexpected shifts would be valuable. Using mathematical models of regime shifts, ecologists have proposed various early warning signals of imminent shifts. However, their generality and applicability to real ecosystems remain unclear because these mathematical models are considered too simplistic. Here, we investigate the robustness of recently proposed early warning signals of regime shifts in two well-studied ecological models, but with the inclusion of time-delayed processes. We find that the average variance may either increase or decrease prior to a regime shift and, thus, may not be a robust leading indicator in time-delayed ecological systems. In contrast, changing average skewness, increasing autocorrelation at short time lags, and reddening power spectra of time series of the ecological state variable all show trends consistent with those of models with no time delays. Our results provide insights into the robustness of early warning signals of regime shifts in a broader class of ecological systems.     

Region‐wide changes in marine ecosystem dynamics: state‐space models to distinguish trends from step changes

Regime shifts are sudden changes in ecosystem structure that can be detected across several ecosystem components. The concept that regime shifts are common in marine ecosystems has gained popularity in recent years. Many studies have searched for the step‐like changes in ecosystem state expected under a simple interpretation of this idea. However, other kinds of change, such as pervasive trends, have often been ignored. We assembled over 300 ecological time series from seven UK marine regions, covering two to three decades. We developed state‐space models for the first principal component of the time series in each region, a common measure of ecosystem state. Our models allowed both trends and step changes, possibly in combination. We found trends in three of seven regions and step changes in two of seven regions. Gradual and sudden changes are therefore important trajectories to consider in marine ecosystems.     

Early warning signals of demographic regime shifts in invading populations

The Allee effect can cause alternative stable states in population abundance of invasive species. Sudden eruption of invading populations from low to high abundance may be viewed as a regime shift from one alternative state to another. Previous research proposed several types of early warning signals to predict regime shifts in ecological systems such as polluted lakes and semiarid grasslands. This paper explores theoretically the potential of such indicators in predicting demographic regime shifts of invading populations. I analyzed a stochastic differential equation model for the population dynamics of an invasive species subject to Allee effects and propagule pressure. Diffusion approximation to the stochastic model suggests that persistent propagule pressure makes demographic regime shifts inevitable, but Allee effects can lengthen the mean time until regime shifts virtually indefinitely. To compare the potential of indicators, I examined standard deviation, skewness, and estimated return rates of longitudinal population abundance. I found that standard deviation showed a distinct increase as regime shifts became more likely, but skewness and return rates showed no clear trends. This result suggests that standard deviation might be a useful warning signal for forecasting an impending demographic regime shift of invading populations during the period when their abundance is still low.     

Potential impacts of climate change on stable flies, investigated along an altitudinal gradient

Adult populations of stable flies were sampled along an altitudinal transect in Reunion Island to determine whether higher temperatures were associated with: (a) higher numbers of flies; (b) a longer season of infestation, and/or (c) different responses to warming in the cosmopolitan Stomoxys calcitrans (L) and the tropical Stomoxys niger niger Macquart (Diptera: Muscidae). Flies of both species were trapped at seven farms situated at four altitudes (100-1600 m a.s.l.) over a 90-week period. For both species, there were no relationships between the maximum or mean fly abundance and altitude. Only minimum abundance in winter was significantly higher at lower altitudes. Maximum and mean abundances differed significantly between nearby farms under similar climatic conditions. Seasonal fluctuations in fly abundance changed along the gradient. At lower altitudes, population growth started earlier after the winter but abundance declined earlier in summer, which resulted in a shift of the season of infestation. Seasonal fluctuations of both species were strongly related to climate variables at high altitude, mainly temperature. However, climate variables explained a decreasing proportion of the variations in abundance at lower altitudes. Stomoxys calcitrans was the most abundant species overall, but the proportion of S. n. niger increased significantly at lower altitudes and this species became predominant at 100 m a.s.l. It is concluded that stable fly infestations are unlikely to worsen in response to global warming. Maximum abundance is limited by local factors, possibly larval resources, which suggests that adequate husbandry practices could override the impact of climate change. Because S. n. niger tends to be the predominant pest at elevated temperatures, it is recommended that this species should not be introduced in areas where climate is changing.     

Identification of regime shifts in time series using neighborhood statistics

Sudden and significant changes in biotic and abiotic variables have been observed across a variety of systems. The identification of such regime shifts in time series includes both model-fitting and statistical approaches. We introduce two methods that use state- or measurement-space neighborhood statistics to pick out regime shifts. Analysis of simulated and real data sets shows that these methods can be an effective means of identifying regime shifts for single variable as well as multivariable time series. In addition, these methods can be used on systems with non-equilibrium steady states. However, care must be taken in interpreting results as these methods do respond to changes in time series that are not consistent with the regime shift concept.     

Conditional heteroscedasticity as a leading indicator of ecological regime shifts

Regime shifts are massive, often irreversible, rearrangements of nonlinear ecological processes that occur when systems pass critical transition points. Ecological regime shifts sometimes have severe consequences for human well-being, including eutrophication in lakes, desertification, and species extinctions. Theoretical and laboratory evidence suggests that statistical anomalies may be detectable leading indicators of regime shifts in ecological time series, making it possible to foresee and potentially avert incipient regime shifts. Conditional heteroscedasticity is persistent variance characteristic of time series with clustered volatility. Here, we analyze conditional heteroscedasticity as a potential leading indicator of regime shifts in ecological time series. We evaluate conditional heteroscedasticity by using ecological models with and without four types of critical transition. On approaching transition points, all time series contain significant conditional heteroscedasticity. This signal is detected hundreds of time steps in advance of the regime shift. Time series without regime shifts do not have significant conditional heteroscedasticity. Because probability values are easily associated with tests for conditional heteroscedasticity, detection of false positives in time series without regime shifts is minimized. This property reduces the need for a reference system to compare with the perturbed system.     

Clinical symptoms, treatment and outcome of highlands malaria in Eldoret (2420 m a.s.l.) and comparison to malaria in hyper-immune population in endemic region of Southern Sudan

Malaria should not be present in altitudes more than 1,800 m a.s.l. However due to global warming, highlands malaria (HM) occurs up to 2,000 m. The purpose of this study is comparison of clinical picture and prognosis of HM and compare it to malaria in endemic region of southern Sudan (endemic malaria - EM) among hyper-immune population.     

Architecture of collapse: regime shift and recovery in an hierarchically structured marine ecosystem

By the late 20th century, a series of events or ‘natural experiments’, for example the depletion of apex predators, extreme eutrophication and blooms of invasive species, had suggested that the Black Sea could be considered as a large ecosystem ‘laboratory’. The events resulted in regime shifts cascading through all trophic levels, disturbing ecosystem functioning and damaging the water environment. Causal pathways by which the external (hydroclimate, overfishing) and internal (food web interactions) drivers provoke regime shifts are investigated. Statistical data analyses supported by an interpretative framework based on hierarchical ecosystem theory revealed mechanisms of hierarchical incorporation of environmental factors into the ecosystem. Evidence links Atlantic teleconnections to Black Sea hydroclimate, which together with fishing shapes variability in fish stocks. The hydroclimatic signal is conveyed through the food web via changes in productivity at all levels, to planktivorous fish. Fluctuating fish abundance is believed to induce a lagged change in competitor jelly plankton that cascades down to phytoplankton and influences water quality. Deprived of the stabilising role of apex predators, the Black Sea's hierarchical ecosystem organisation is susceptible to both environmental and anthropogenic stresses, and increased fishing makes fish stock collapses highly probable. When declining stocks are confronted with burgeoning fishing effort associated with the inability of fishery managers and decision‐makers to adapt rapidly to changes in fish abundance, there is overfishing and stock collapse. Management procedures are ineffective at handling complex phenomena such as ecosystem regime shifts because of the shortage of suitable explanatory models. The proposed concepts and models reported here relate the hydroclimate, overfishing and invasive species to shifts in ecosystem functioning and water quality, unravelling issues such as the causality of ecosystem interactions and mechanisms and offering potential for finding ways to reverse regime shifts. We advocate a management approach aiming at restoring ecosystem hierarchy that might mitigate the costly consequences of regime shifts.     

Incidence of malaria among children living near dams in northern Ethiopia: community based incidence survey

ObjectiveTo assess the impact of construction of microdams on the incidence of malaria in nearby communities in terms of possibly increasing peak incidence and prolonging transmission.DesignFour quarterly cycles of malaria incidence surveys, each taking 30 days, undertaken in eight at risk communities close to dams paired with eight control villages at similar altitudes but beyond flight range of mosquitoes.SettingTigray region in northern Ethiopia at altitudes of 1800 to 2225 m.SubjectsAbout 7000 children under 10 years living in villages within 3 km of microdams and in control villages 8-10 km distant.ResultsOverall incidence of malaria for the villages close to dams was 14.0 episodes/1000 child months at risk compared with 1.9 in the control villages—a sevenfold ratio. Incidence was significantly higher in both communities at altitudes below 1900 m.ConclusionsThere is a need for attention to be given to health issues in the implementation of ecological and environmental development programmes, specifically for appropriate malaria control measures to counteract the increased risks near these dams.

Key messages

• Environmental development may have important effects on the epidemiology of vector borne diseases such as malaria
• This may be particularly important where disease transmission is unstable—for example, in highland areas
• Children in villages near recently constructed microdams in northern Ethiopia had a significantly increased risk of malaria
• It seems that this irrigation development programme is leading to increased malaria transmission across a range of altitudes and seasons
• Intersectoral collaboration is necessary in development projects that may affect communities both positively and negatively

     

Clinical Malaria Transmission Trends and Its Association with Climatic Variables in Tubu Village,Botswana: A Retrospective Analysis

Good knowledge on the interactions between climatic variables and malaria can be very useful for predicting outbreaks and preparedness interventions. We investigated clinical malaria transmission patterns and its temporal relationship with climatic variables in Tubu village, Botswana. A 5-year retrospective time series data analysis was conducted to determine the transmission patterns of clinical malaria cases at Tubu Health Post and its relationship with rainfall, flood discharge, flood extent, mean minimum, maximum and average temperatures. Data was obtained from clinical records and respective institutions for the period July 2005 to June 2010, presented graphically and analysed using the Univariate ANOVA and Pearson cross-correlation coefficient tests. Peak malaria season occurred between October and May with the highest cumulative incidence of clinical malaria cases being recorded in February. Most of the cases were individuals aged >5 years. Associations between the incidence of clinical malaria cases and several factors were strong at lag periods of 1 month; rainfall (r = 0.417), mean minimum temperature (r = 0.537), mean average temperature (r = 0.493); and at lag period of 6 months for flood extent (r = 0.467) and zero month for flood discharge (r = 0.497). The effect of mean maximum temperature was strongest at 2-month lag period (r = 0.328). Although malaria transmission patterns varied from year to year the trends were similar to those observed in sub-Saharan Africa. Age group >5 years experienced the greatest burden of clinical malaria probably due to the effects of the national malaria elimination programme. Rainfall, flood discharge and extent, mean minimum and mean average temperatures showed some correlation with the incidence of clinical malaria cases.     

荒漠人工固沙植被区土壤水分的时空变异性

表层土壤水分具有高度的时间和空间变异性.研究的目的:(1)揭示沙坡头人工固沙植被区浅层土壤水分的时空变异性特征;(2)确定驱动土壤水分变异的主要环境因子.在人工固沙植被区内一个4500m2的网格样地上每隔10m设置取样点,在连续7个月的时间内 (2005年4～10月),每隔15d用时域反射仪测量各样点表层以下15cm和30cm深度的土壤容积含水量.结果表明,该区网格尺度上浅层土壤水分的分布具有明显的空间变异性,其变异性随着土壤水分含量的降低而减小;相对海拔是驱动土壤水分空间变异的主要环境因子,其作用在降雨后尤为显著,且其对土壤下层的影响比上层更明显;植被和土壤水分含量的相关性时间序列与相对海拔一致--降雨使其相关性增加;土壤质地(土壤粒径分布)和土壤水分含量的相关性时间序列特征与植被和相对海拔相反,且其对土壤上层的影响比下层更明显.因此,在沙坡头荒漠人工固沙植被区,降雨后的短暂湿润期,地形和植被是驱动浅层土壤水分变异的主要影响因子,而随着降雨之后土壤逐渐变干,土壤质地的影响变得更加明显.     

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal‐scale biological variability

In areas of the North Pacific that are largely free of overfishing, climate regime shifts – abrupt changes in modes of low‐frequency climate variability – are seen as the dominant drivers of decadal‐scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific‐North American Pattern (PNA), North Pacific Index (NPI), El Niño‐Southern Oscillation (ENSO)] to explain decadal‐scale (1965–2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1–2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1–2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1–2 satisfied assumptions of independent residuals and out‐performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1–2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations.     

Epidemic and Endemic Malaria Transmission Related to Fish Farming Ponds in the Amazon Frontier

Fish farming in the Amazon has been stimulated as a solution to increase economic development. However, poorly managed fish ponds have been sometimes associated with the presence of Anopheles spp. and consequently, with malaria transmission. In this study, we analyzed the spatial and temporal dynamics of malaria in the state of Acre (and more closely within a single county) to investigate the potential links between aquaculture and malaria transmission in this region. At the state level, we classified the 22 counties into three malaria endemicity patterns, based on the correlation between notification time series. Furthermore, the study period (2003–2013) was divided into two phases (epidemic and post-epidemic). Higher fish pond construction coincided both spatially and temporally with increased rate of malaria notification. Within one malaria endemic county, we investigated the relationship between the geolocation of malaria cases (2011–2012) and their distance to fish ponds. Entomological surveys carried out in these ponds provided measurements of anopheline abundance that were significantly associated with the abundance of malaria cases within 100 m of the ponds (P < 0.005; r = 0.39). These results taken together suggest that fish farming contributes to the maintenance of high transmission levels of malaria in this region.     

The role of species’ ecological traits in climatically driven altitudinal range shifts of central European birds

Climate change is one of the most important recent forces modulating the structure of ecological communities worldwide. Although a number of studies have documented climatically induced altitudinal range shifts, with species move upwards with increasing temperature and tracking their climatic optima, an examination of interspecific variability in such altitudinal shifts remains unexplored. Using a unique dataset on the altitudinal distribution of birds in a central European mountain range, collected with constant effort and methodology over more than 20 years, we examined the effects of particular species’ ecological traits on interspecific variability in altitudinal range shifts. We predicted that shifts would be greater in species with narrower European climatic niches, breeding in open habitats, feeding on insects and originally breeding at lower altitudes. Patterns of the shifts differed within the time period studied. In the first decade, no climate change was observed and species did not show any direction in their altitudinal shifts. In the second decade, local spring temperatures increased and species moved to higher altitudes. These altitudinal shifts were related to species’ habitat preferences, with open habitat species shifting to higher altitudes than forest species. The effect of other predictors was relatively small. The habitat effects imply either stronger self‐regulation of the forest microclimate compared to open habitats, with forest species less forced to move upwards, or a delayed shift in the alpine timberline due to the slow growth of trees. In the latter case, forest species would face unfavourable climatic conditions and at the same time be constrained by the limited distribution of their habitat. Our study shows that species’ ecology can considerably alter the actual outcome of the impacts of ongoing climate change in mountain areas.     

The importance of within-system spatial variation in drivers of marine ecosystem regime shifts

Comparative analyses of the dynamics of exploited marine ecosystems have led to differing hypotheses regarding the primary causes of observed regime shifts, while many ecosystems have apparently not undergone regime shifts. These varied responses may be partly explained by the decade-old recognition that within-system spatial heterogeneity in key climate and anthropogenic drivers may be important, as recent theoretical examinations have concluded that spatial heterogeneity in environmental characteristics may diminish the tendency for regime shifts. Here, we synthesize recent, empirical within-system spatio-temporal analyses of some temperate and subarctic large marine ecosystems in which regime shifts have (and have not) occurred. Examples from the Baltic Sea, Black Sea, Bengula Current, North Sea, Barents Sea and Eastern Scotian Shelf reveal the largely neglected importance of considering spatial variability in key biotic and abiotic influences and species movements in the context of evaluating and predicting regime shifts. We highlight both the importance of understanding the scale-dependent spatial dynamics of climate influences and key predator–prey interactions to unravel the dynamics of regime shifts, and the utility of spatial downscaling of proposed mechanisms (as evident in the North Sea and Barents Sea) as a means of evaluating hypotheses originally derived from among-system comparisons.     

Rising variance: a leading indicator of ecological transition

Regime shifts are substantial, long-lasting reorganizations of complex systems, such as ecosystems. Large ecosystem changes such as eutrophication, shifts among vegetation types, degradation of coral reefs and regional climate change often come as surprises because we lack leading indicators for regime shifts. Increases in variability of ecosystems have been suggested to foreshadow ecological regime shifts. However, it may be difficult to discern variability due to impending regime shift from that of exogenous drivers that affect the ecosystem. We addressed this problem using a model of lake eutrophication. Lakes are subject to fluctuations in recycling associated with regime shifts, as well as fluctuating nutrient inputs. Despite the complications of noisy inputs, increasing variability of lake-water phosphorus was discernible prior to the shift to eutrophic conditions. Simulations show that rising standard deviation (SD) could signal impending shifts about a decade in advance. The rising SD was detected by studying variability around predictions of a simple time-series model, and did not depend on detailed knowledge of the actual ecosystem dynamics.     

Faunal change, environmental variability and late Pliocene hominin evolution

Global change during the late Pliocene was manifested in declining temperatures, increased amplitude of climate cycles, and shifts in the periodicity of orbital climate forcing. Linking these changes to the evolution of African continental faunas and to hominin evolution requires well-documented fossil evidence that can be examined through substantial periods of time. The Omo sequence of southern Ethiopia provides such a database, and we use it to analyze change in the abundances of mammal taxa at different levels of temporal and taxonomic resolution between 4 and 2 Ma. This study provides new evidence for shifts through time in the ecological dominance of suids, cercopithecids, and bovids, and for a trend from more forested to more open woodland habitats. Superimposed on these long-term trends are two episodes of faunal change, one involving a marked shift in the abundances of different taxa at about 2.8+/-0.1 Ma, and the second the transition at 2.5 Ma from a 200-ka interval of faunal stability to marked variability over intervals of about 100 ka. The first appearance of Homo, the earliest artefacts, and the extinction of non-robust Australopithecus in the Omo sequence coincide in time with the beginning of this period of high variability. We conclude that climate change caused significant shifts in vegetation in the Omo paleo-ecosystem and is a plausible explanation for the gradual ecological change from forest to open woodland between 3.4 and 2.0 Ma, the faunal shift at 2.8 +/-0.1 Ma, and the change in the tempo of faunal variability of 2.5 Ma. Climate forcing in the late Pliocene is more clearly indicated by population shifts within the Omo mammal community than by marked turnover at the species level.     

Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing.