Mismatches between birds' spatial and temporal dynamics reflect their delayed response to global changes

Global changes alter the dynamics of biodiversity, and are forecasted to continue or worsen in the decades to come. Modelling approaches used to anticipate these impacts are mainly based on the equivalence between spatial and temporal response to environmental forcings, generally called space-for-time substitution. However, several processes are known to generate deviations between spatial and temporal responses, potentially undermining the prediction based on space-for-time substitution. We here used high-resolution data from the french breeding bird survey to quantify and map the deviation between spatial and temporal patterns of bird abundances resulting from the dynamics of 124 species monitored in 2133 sites between 2001 and 2012. Using independent empirical data, we then tested specific predictions linked to the determinants (anthropogenic activities) and processes (lagged responses to environmental changes) potentially generating these deviations. We found that deviations between spatial and temporal patterns of abundances were particularly structured in space for bird communities. Following our predictions, these space–time deviations were positively correlated with the human influence on ecosystems, and linked with colonization–extinction ratios and community completeness, two markers of ongoing delayed responses to environmental changes. Our results suggest that the deviations between spatial and temporal patterns are related to recent anthropogenic environmental changes and disequilibrium responses to these changes. Investigating deviations between spatial and temporal patterns of biodiversity might open promising perspectives for a formal quantification of disequilibrium state of biodiversity at large spatial scale.     

Greater Abundance of <Emphasis Type="Italic">Betula nana</Emphasis> and Early Onset of the Growing Season Increase Ecosystem CO<Subscript>2</Subscript> Uptake in West Greenland

Expansion of deciduous shrubs is a common observation throughout the Arctic, with implications for carbon (C) cycling. Shrubs may increase net ecosystem C uptake through greater leaf area and gross ecosystem photosynthesis (GEP), and/or through cooler summer soils and reduced ecosystem respiration (ER). We used a space-for-time substitution combined with experimental warming at a Low Arctic site in West Greenland to examine the biophysical effects of increased temperature and Betula nana abundance on ecosystem CO₂ exchange. Communities dominated by Betula were much stronger C sinks than graminoid communities due to greater GEP and lower ER. The warming treatment had little effect on GEP, ER, or net ecosystem CO₂ exchange (NEE). The start of the growing season has been advancing at our study site, as indicated by long-term observations of plant phenology. In a retrospective analysis, we estimate that earlier onset of the growing season has increased the strength of the ecosystem C sink at rates of 1.3 and 2.1 g C m^?2 y^?1 in Betula and graminoid tundra, respectively, since 2002. However, earlier, and presumably longer, growing seasons may be associated with greater potential for drought stress. Our data suggest that mid-summer drought-induced GEP declines may partially offset C gains associated with an earlier start to the growing season. Our results suggest greater deciduous shrub abundance and longer growing seasons will likely lead to greater net C uptake in our study area, while highlighting important complexities associated with drought and plant community composition.     

Matching the forecast horizon with the relevant spatial and temporal processes and data sources

Most phenomenological, statistical models used to generate ecological forecasts take either a time-series approach, based on long-term data from one location, or a space-for-time approach, based on data describing spatial patterns across environmental gradients. However, the magnitude and even the sign of environment–response relationships detected using these two approaches often differs, leading to contrasting predictions about responses to future environmental change. Here we consider how the forecast horizon determines whether more accurate predictions come from the time-series approach, the space-for-time approach or a combination of the two. As proof of concept, we use simulated case studies to show that forecasts for short and long forecast horizons need to focus on different ecological processes, which are reflected in different kinds of data. First, we simulated population or community dynamics under stationary temperature using two simple, mechanistic models. Second, we fit statistical models to the simulated data using a time-series approach, a space-for-time approach or a weighted average. We then forecast the response to a temperature increase using the statistical models, and compared these forecasts to temperature effects simulated by the mechanistic models. We found that the time-series approach made accurate short-term predictions because it captured initial conditions and effects of fast processes such as birth and death. The space-for-time approach made more accurate long-term predictions because it better captured the influence of slower processes such as evolutionary and ecological selection. The weighted average made accurate predictions at all time scales, including intermediate time-scales where the other two approaches performed poorly. A weighted average of time-series and space-for-time approaches shows promise, but making this weighted model operational will require new research to predict the rate at which slow processes begin to influence dynamics.     

Forest Remnants Along Urban-Rural Gradients: Examining Their Potential for Global Change Research

Over the next century, ecosystems throughout the world will be responding to rapid changes in climate and rising levels of carbon dioxide, inorganic N and ozone. Because people depend on biological systems for water, food and other ecosystem services, predicting the range of responses to global change for various ecosystem types in different geographic locations is a high priority. Modeling exercises and manipulative experimentation have been the principle approaches used to place upper and lower bounds on community and ecosystem responses. However, each of these approaches has recognized limitations. Manipulative experiments cannot vary all the relevant factors and are often performed at small spatio-temporal scales. Modeling is limited by data availability and by our knowledge of how current observations translate into future conditions. These weaknesses would improve if we could observe ecosystems that have already responded to global change factors and thus presage shifts in ecosystem structure and function. Here we consider whether urban forest remnants might offer this ability. As urban forests have been exposed to elevated temperature, carbon dioxide, nitrogen deposition and ozone for many decades, they may be ahead of the global change “response curve” for forests in their region. Therefore, not only might forests along urbanization gradients provide us with natural experiments for studying current responses to global change factors, but their legacy of response to past urbanization may also constitute space-for-time substitution experiments for predicting likely regional forest responses to continued environmental change. For this approach to be successful, appropriate criteria must be developed for selecting forest remnants and plots that would optimize our ability to detect incipient forest responses to spatial variation in global change factors along urbanization gradients, while minimizing artifacts associated with remnant size and factors other than those that simulate global change. Studying forests that meet such criteria along urban-to-rural gradients could become an informative part of a mixed strategy of approaches for improving forecasts of forest ecosystem change at the regional scale.     

Responses of competitive understorey species to spatial environmental gradients inaccurately explain temporal changes

Understorey plant communities play a key role in the functioning of forest ecosystems. Under favourable environmental conditions, competitive understorey species may develop high abundances and influence important ecosystem processes such as tree regeneration. Thus, understanding and predicting the response of competitive understorey species as a function of changing environmental conditions is important for forest managers. In the absence of sufficient temporal data to quantify actual vegetation changes, space-for-time (SFT) substitution is often used, i.e. studies that use environmental gradients across space to infer vegetation responses to environmental change over time. Here we assess the validity of such SFT approaches and analysed 36 resurvey studies from ancient forests with low levels of recent disturbances across temperate Europe to assess how six competitive understorey plant species respond to gradients of overstorey cover, soil conditions, atmospheric N deposition and climatic conditions over space and time. The combination of historical and contemporary surveys allows (i) to test if observed contemporary patterns across space are consistent at the time of the historical survey, and, crucially, (ii) to assess whether changes in abundance over time given recorded environmental change match expectations from patterns recorded along environmental gradients in space. We found consistent spatial relationships at the two periods: local variation in soil variables and overstorey cover were the best predictors of individual species’ cover while interregional variation in coarse-scale variables, i.e. N deposition and climate, was less important. However, we found that our SFT approach could not accurately explain the large variation in abundance changes over time. We thus recommend to be cautious when using SFT substitution to infer species responses to temporal changes.     

Formal Comparison of Dual-Parameter Temporal Discounting Models in Controls and Pathological Gamblers

Temporal or delay discounting refers to the phenomenon that the value of a reward is discounted as a function of time to delivery. A range of models have been proposed that approximate the shape of the discount curve describing the relationship between subjective value and time. Recent evidence suggests that more than one free parameter may be required to accurately model human temporal discounting data. Nonetheless, many temporal discounting studies in psychiatry, psychology and neuroeconomics still apply single-parameter models, despite their oftentimes poor fit to single-subject data. Previous comparisons of temporal discounting models have either not taken model complexity into account, or have overlooked particular models. Here we apply model comparison techniques in a large sample of temporal discounting datasets using several discounting models employed in the past. Among the models examined, an exponential-power model from behavioural economics (CS model, Ebert & Prelec 2007) provided the best fit to human laboratory discounting data. Inter-parameter correlations for the winning model were moderate, whereas they were substantial for other dual-parameter models examined. Analyses of previous group and context effects on temporal discounting with the winning model provided additional theoretical insights. The CS model may be a useful tool in future psychiatry, psychology and neuroscience work on inter-temporal choice.     

The Influence of Climate, Soils, Weather, and Land Use on Primary Production and Biomass Seasonality in the US Great Plains

Identifying the conditions and mechanisms that control ecosystem processes, such as net primary production, is a central goal of ecosystem ecology. Ideas have ranged from single limiting-resource theories to colimitation by nutrients and climate, to simulation models with edaphic, climatic, and competitive controls. Although some investigators have begun to consider the influence of land-use practices, especially cropping, few studies have quantified the impact of cropping at large scales relative to other known controls over ecosystem processes. We used a 9-year record of productivity, biomass seasonality, climate, weather, soil conditions, and cropping in the US Great Plains to quantify the controls over spatial and temporal patterns of net primary production and to estimate sensitivity to specific driving variables. We considered climate, soil conditions, and long-term average cropping as controls over spatial patterns, while weather and interannual cropping variations were used as controls over temporal variability. We found that variation in primary production is primarily spatial, whereas variation in seasonality is more evenly split between spatial and temporal components. Our statistical (multiple linear regression) models explained more of the variation in the amount of primary production than in its seasonality, and more of the spatial than the temporal patterns. Our results indicate that although climate is the most important variable for explaining spatial patterns, cropping explains a substantial amount of the residual variability. Soil texture and depth contributed very little to our models of spatial variability. Weather and cropping deviation both made modest contributions to the models of temporal variability. These results suggest that the controls over seasonality and temporal variation are not well understood. Our sensitivity analysis indicates that production is more sensitive to climate than to weather and that it is very sensitive to cropping intensity. In addition to identifying potential gaps in out knowledge, these results provide insight into the probable long- and short-term ecosystem response to changes in climate, weather, and cropping.     

植物对气候变化生理生态响应的不确定性分析

生态系统对全球气候变化的响应模式有利于人类预测与适应未来生态环境变化,植物作为陆地生态系统的重要组成部分,对全球气候变化的响应具有重要作用.本文通过对近年来植物对气候变化的生理生态响应研究中(包括定点控制实验,空间代替时间样带),植物响应模式的复杂性、多样性及可变性等诸多不确定性进行分析.以探讨预测未来气候情景下植物的动态变化及生理生态响应过程.分析结果认为.造成这些不确定性的主要原因包括:(1)利用空间代替时间的样带研究中,往往忽略了植物的非线性响应,存在明显的阈值;(2)样带及定点研究中,由于各种气候因子的耦合.很难确定各种气候因子对植物生理生态学特性影响的权重;(3)定点控制实验中往往忽略了植物对气候变化的适应性,使实验结果很难代表更长时间尺度上的反映模式;(4)在相同的气候变化条件下,不同植物的响应有可能存在明显差异.提出了今后植物对气候变化生理生态响应研究的建议.     

Identification of a biomanipulation‐driven regime shift in Lake Vesijärvi: implications for lake management

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Tree ring δ<Superscript>15</Superscript>N as validation of space-for-time substitution in disturbance studies of forest nitrogen status

Forest ecosystem nitrogen (N) response to disturbance has often been examined by space-for-time substitution, but there are few objective tests of the possible variation in disturbance type and intensity across chronosequence sites. We hypothesized that tree ring δ¹⁵N, as a record of ecosystem N status, could validate chronosequence assumptions and provide isotopic evidence to corroborate N trends. To test this we measured soil N availability, soil δ¹⁵N, and foliar N attributes of overstory Douglas-fir (Pseudotsuga menziesii) and understory western hemlock (Tsuga heterophylla) across three old-growth stands and nine second-growth plantations on southeast Vancouver Island, British Columbia (Canada). Increment cores for wood δ¹⁵N were retrieved from three co-dominant Douglas-fir per plot. Bulk soil δ¹⁵N was well aligned with both foliar and recent wood δ¹⁵N, demonstrating the utility of wood δ¹⁵N in monitoring ecosystem N status. Strongly contrasting trends in tree ring δ¹⁵N were evident among second-growth stands, with most trees from plantations older than 50 years exhibiting steep declines (3–4‰) in δ¹⁵N but with no temporal trends detected for younger plantations. The discrepancy in tree ring δ¹⁵N suggests disturbance history varied considerably among second-growth sites, likely because of greater slash loads and hotter broadcast burns on older cutblocks. As a consequence, the pattern of increased soil N availability and foliar N concentration with time since disturbance derived from the chronosequence could not be validated. Tree ring δ¹⁵N may provide insights into disturbance intensity, especially fire, and correlations with foliar N concentration could inform the extent of changes in stand nutrition.     

A Space-For-Time (SFT) Substitution Approach to Studying Historical Phenological Changes in Urban Environment

Plant phenological records are crucial for predicting plant responses to global warming. However, many historical records are either short or replete with data gaps, which pose limitations and may lead to erroneous conclusions about the direction and magnitude of change. In addition to uninterrupted monitoring, missing observations may be substituted via modeling, experimentation, or gradient analysis. Here we have developed a space-for-time (SFT) substitution method that uses spatial phenology and temperature data to fill gaps in historical records. To do this, we combined historical data for several tree species from a single location with spatial data for the same species and used linear regression and Analysis of Covariance (ANCOVA) to build complementary spring phenology models and assess improvements achieved by the approach. SFT substitution allowed increasing the sample size and developing more robust phenology models for some of the species studied. Testing models with reduced historical data size revealed thresholds at which SFT improved historical trend estimation. We conclude that under certain circumstances both the robustness of models and accuracy of phenological trends can be enhanced although some limitations and assumptions still need to be resolved. There is considerable potential for exploring SFT analyses in phenology studies, especially those conducted in urban environments and those dealing with non-linearities in phenology modeling.     

Quantitatively Evaluating Restoration Experiments: Research Design, Statistical Analysis, and Data Management Considerations

Conceptual and logistical challenges associated with the design and analysis of ecological restoration experiments are often viewed as being insurmountable, thereby limiting the potential value of restoration experiments as tests of ecological theory. Such research constraints are, however, not unique within the environmental sciences. Numerous natural and anthropogenic disturbances represent unplanned, uncontrollable events that cannot be replicated or studied using traditional experimental approaches and statistical analyses. A broad mix of appropriate research approaches (e.g., long-term studies, large-scale comparative studies, space-for-time substitution, modeling, and focused experimentation) and analytical tools (e.g., observational, spatial, and temporal statistics) are available and required to advance restoration ecology as a scientific discipline. In this article, research design and analytical options are described and assessed in relation to their applicability to restoration ecology. Significant research benefits may be derived from explicitly defining conceptual models and presuppositions, developing multiple working hypotheses, and developing and archiving high-quality data and metadata. Flexibility in research approaches and statistical analyses, high-quality databases, and new sampling approaches that support research at broader spatial and temporal scales are critical for enhancing ecological understanding and supporting further development of restoration ecology as a scientific discipline.     

Ecosystem Functions across Trophic Levels Are Linked to Functional and Phylogenetic Diversity

In experimental systems, it has been shown that biodiversity indices based on traits or phylogeny can outperform species richness as predictors of plant ecosystem function. However, it is unclear whether this pattern extends to the function of food webs in natural ecosystems. Here we tested whether zooplankton functional and phylogenetic diversity explains the functioning of 23 natural pond communities. We used two measures of ecosystem function: (1) zooplankton community biomass and (2) phytoplankton abundance (Chl a). We tested for diversity-ecosystem function relationships within and across trophic levels. We found a strong correlation between zooplankton diversity and ecosystem function, whereas local environmental conditions were less important. Further, the positive diversity-ecosystem function relationships were more pronounced for measures of functional and phylogenetic diversity than for species richness. Zooplankton and phytoplankton biomass were best predicted by different indices, suggesting that the two functions are dependent upon different aspects of diversity. Zooplankton community biomass was best predicted by zooplankton trait-based functional richness, while phytoplankton abundance was best predicted by zooplankton phylogenetic diversity. Our results suggest that the positive relationship between diversity and ecosystem function can extend across trophic levels in natural environments, and that greater insight into variation in ecosystem function can be gained by combining functional and phylogenetic diversity measures.     

Pairing automated mark–recapture and social network models to explore the effects of landscape configuration on hummingbird foraging patterns

Landscape changes can alter pollinator movement and foraging patterns which can in turn influence the demographic processes of plant populations. We leveraged social network models and four fixed arrays of five hummingbird feeders equipped with radio frequency identification (RFID) data loggers to study rufous hummingbird (Selasphorus rufus) foraging patterns in a heterogeneous landscape. Using a space-for-time approach, we asked whether forest encroachment on alpine meadows could restrict hummingbird foraging movements and impede resource discovery. We fit social network models to data on 2221 movements between feeders made by 29 hummingbirds. Movements were made primarily by females, likely due to male territoriality and early migration dates. Distance was the driving factor in determining the rate of movements among feeders. The posterior mean effects of forest landscape variables (local canopy cover and intervening forest cover) were negative, but with considerable uncertainty. Finally, we found strong reciprocity in hummingbird movements, indicative of frequent out and back movements between resources. Together, these findings suggest that reciprocal movements by female hummingbirds could help maintain bidirectional gene flow among nearby subpopulations of ornithophilous plants; however, if the distance among meadows increases with further forest encroachment, this may limit foraging among progressively isolated meadows.     

Global‐change drivers of ecosystem functioning modulated by natural variability and saturating responses

Humans are altering global environment at an unprecedented rate through changes in biodiversity, climate, nitrogen cycle, and land use. To address their effects on ecosystem functioning, experiments most frequently explore one driver at a time and control as many confounding factors as possible. Yet, which driver exerts the largest influence on ecosystem functioning and whether their relative importance changes among systems remain unclear. We analyzed experiments in the Patagonian steppe that evaluated the aboveground net primary production (ANPP) response to manipulated gradients of species richness, precipitation, temperature, nitrogen fertilization (N), and grazing intensity. We compared the effect on ANPP relative to ambient conditions considering intensity and direction of manipulations for each driver. The ranking of responses to drivers with comparable manipulation intensity was as follows: biodiversity>grazing>precipitation>N. For a similar intensity of manipulation, the effect of biodiversity loss was 4.0, 3.6, and 1.5, times larger than N deposition, decreased precipitation, and increased grazing intensity. We interpreted our results considering two hypotheses. First, the response of ANPP to changes in precipitation and biodiversity is saturating, so we expected larger effects when the driver was reduced, relative to ambient conditions, than when it was increased. Experimental manipulations that reduced ambient levels had larger effects than those that increased them. Second, the sensitivity of ANPP to each driver is inversely related to the natural variability of the driver. In Patagonia, the ranking of natural variability of drivers is as follows: precipitation>grazing>temperature>biodiversity>N. So, in general, the ecosystem was most sensitive to drivers that varied the least. Comparable results from Cedar Creek (MN) support both hypotheses and suggest that sensitivity to drivers varies among ecosystem types. Given the importance of understanding ecosystem sensitivity to predict global‐change impacts, it is necessary to design new experiments located in regions with contrasting natural variability and that include the full range of drivers.     

Predicting the likely response of data‐poor ecosystems to climate change using space‐for‐time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data‐poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data‐poor ecosystems based on a space‐for‐time substitution, using distant, well‐studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate‐ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains – to investigate ecological response to climate change – allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long‐term predictions will be of significant value to natural resource practitioners attempting to manage data‐poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.     

Environmental Drivers of Benthic Flux Variation and Ecosystem Functioning in Salish Sea and Northeast Pacific Sediments

The upwelling of deep waters from the oxygen minimum zone in the Northeast Pacific from the continental slope to the shelf and into the Salish Sea during spring and summer offers a unique opportunity to study ecosystem functioning in the form of benthic fluxes along natural gradients. Using the ROV ROPOS we collected sediment cores from 10 sites in May and July 2011, and September 2013 to perform shipboard incubations and flux measurements. Specifically, we measured benthic fluxes of oxygen and nutrients to evaluate potential environmental drivers of benthic flux variation and ecosystem functioning along natural gradients of temperature and bottom water dissolved oxygen concentrations. The range of temperature and dissolved oxygen encountered across our study sites allowed us to apply a suite of multivariate analyses rarely used in flux studies to identify bottom water temperature as the primary environmental driver of benthic flux variation and organic matter remineralization. Redundancy analysis revealed that bottom water characteristics (temperature and dissolved oxygen), quality of organic matter (chl a:phaeo and C:N ratios) and sediment characteristics (mean grain size and porosity) explained 51.5% of benthic flux variation. Multivariate analyses identified significant spatial and temporal variation in benthic fluxes, demonstrating key differences between the Northeast Pacific and Salish Sea. Moreover, Northeast Pacific slope fluxes were generally lower than shelf fluxes. Spatial and temporal variation in benthic fluxes in the Salish Sea were driven primarily by differences in temperature and quality of organic matter on the seafloor following phytoplankton blooms. These results demonstrate the utility of multivariate approaches in differentiating among potential drivers of seafloor ecosystem functioning, and indicate that current and future predictive models of organic matter remineralization and ecosystem functioning of soft-muddy shelf and slope seafloor habitats should consider bottom water temperature variation. Bottom temperature has important implications for estimates of seasonal and spatial benthic flux variation, benthic–pelagic coupling, and impacts of predicted ocean warming at high latitudes.     

Isolation and cultivation of microalgae select for low growth rate and tolerance to high pH

Harmful microalgal blooms or red tides are often associated with high levels of pH. Similarly, species and strains of microalgae cultivated in the laboratory with enriched media experience recurrent events of high pH between dilutions with fresh medium. To study the potential for laboratory selection by high pH, we compared, under identical experimental conditions the upper pH tolerance limits for growth in addition to growth and production rates of 23 strains of the common bloom-forming dinoflagellate Heterocapsa triquetra. The strains had been cultivated in official culture centres from ca. 1 to 51 years (corresponding to 200–10,000 generations). Strains cultivated for less than 10 years had significantly lower mean and median upper pH tolerance limits for growth, and higher growth and production rates compared to strains cultivated for more than 20 years. The range and variation of upper pH tolerance limits were higher in the younger (<10 years) than in the older strains (>20 years). These results suggest selection of strains best adapted to tolerate or postpone/avoid events of high pH in the laboratory. Our data have implications for experimental studies of pH response and reaction norms in general of microalgae and the inclusion of species-specific data into ecosystem models.