Predicted Effects Of Climate Change Research Articles

On their best behavior: how animal behavior can help determine the combined effects of species interactions and climate change

The increasingly appreciated link between climate change and species interactions has the potential to help us understand and predict how organisms respond to a changing environment. As this connection grows, it becomes even more important to appreciate the mechanisms that create and control the combined effect of these factors. However, we believe one such important set of mechanisms comes from species' behavior and the subsequent trait-mediated interactions, as opposed to the more often studied density-mediated effects. Behavioral mechanisms are already well appreciated for mitigating the separate effects of the environment and species interactions. Thus, they could be at the forefront for understanding the combined effects. In this review, we (1) show some of the known behaviors that influence the individual and combined effects of climate change and species interactions; (2) conceptualize general ways behavior may mediate these combined effects; and (3) illustrate the potential importance of including behavior in our current tools for predicting climate change effects. In doing so, we hope to promote more research on behavior and other mechanistic factors that may increase our ability to accurately predict climate change effects.

Potential climate change effects on groundwater recharge in the High Plains Aquifer, USA

Considering that past climate changes have significantly impacted groundwater resources, quantitative predictions of climate change effects on groundwater recharge may be valuable for effective management of future water resources. This study used 16 global climate models (GCMs) and three global warming scenarios to investigate changes in groundwater recharge rates for a 2050 climate relative to a 1990 climate in the U.S. High Plains region. Groundwater recharge was modeled using the Soil‐Vegetation‐Atmosphere‐Transfer model WAVES for a variety of soil and vegetation types representative of the High Plains. The median projection under a 2050 climate includes increased recharge in the Northern High Plains (+8%), a slight decrease in the Central High Plains (−3%), and a larger decrease in the Southern High Plains (−10%), amplifying the current spatial trend in recharge from north to south. There is considerable uncertainty in both the magnitude and direction of these changes in recharge projections. Predicted changes in recharge between dry and wet future climate scenarios encompass both an increase and decrease in recharge rates, with the magnitude of this range greater than 50% of current recharge. On a proportional basis, sensitivity of recharge to changes in rainfall indicates that areas with high current recharge rates are least sensitive to change in rainfall and vice versa. Sensitivity analyses indicate an amplification of change in recharge compared to change in rainfall, and this amplification is in the range of 1–6 with an average of 2.5–3.5 depending upon the global warming scenario.

Predicted responses of invasive mammal communities to climate‐related changes in mast frequency in forest ecosystems

Predicting the dynamics and impacts of multiple invasive species can be complex because ecological relationships, which occur among several trophic levels, are often incompletely understood. Further, the complexity of these trophic relationships exacerbates our inability to predict climate change effects on invaded ecosystems. We explore the hypothesis that interactions between two global change drivers, invasive vertebrates and climate change, will potentially make matters worse for native biodiversity. In New Zealand beech (Nothofagus spp.) forests, a highly irruptive invasive mammal community is driven by multi-annual resource pulses of beech seed (masting). Because mast frequency is predicted to increase with climate change, we use this as a model system to explore the extent to which such effects may influence invasive vertebrate communities, and the implications of such interactions for native biodiversity and its management. We build on an established model of trophic interactions in the system, combining it with a logistic probability mast function, the parameters of which were altered to simulate either contemporary conditions or conditions of more or less frequent masting. The model predicts that increased mast frequency will lead to populations of a top predator (the stoat) and a mesopredator (the ship rat) becoming less irruptive and being maintained at appreciably higher average abundances in this forest type. In addition, the ability of both current and in-development management approaches to suppress invasive mammals is predicted to be compromised. Because invasive mammals are key drivers of native fauna extinction in New Zealand, with the additional loss of associated functions such as pollination and seed dispersal, these predictions imply potentially serious adverse impacts of climate change for the conservation of biodiversity and ecosystem function. Our study also highlights the importance of long-term monitoring data for assessing and managing future impacts of global change drivers.

Climate Change Vulnerability of Native and Alien Freshwater Fishes of California: A Systematic Assessment Approach

Freshwater fishes are highly vulnerable to human-caused climate change. Because quantitative data on status and trends are unavailable for most fish species, a systematic assessment approach that incorporates expert knowledge was developed to determine status and future vulnerability to climate change of freshwater fishes in California, USA. The method uses expert knowledge, supported by literature reviews of status and biology of the fishes, to score ten metrics for both (1) current status of each species (baseline vulnerability to extinction) and (2) likely future impacts of climate change (vulnerability to extinction). Baseline and climate change vulnerability scores were derived for 121 native and 43 alien fish species. The two scores were highly correlated and were concordant among different scorers. Native species had both greater baseline and greater climate change vulnerability than did alien species. Fifty percent of California’s native fish fauna was assessed as having critical or high baseline vulnerability to extinction whereas all alien species were classified as being less or least vulnerable. For vulnerability to climate change, 82% of native species were classified as highly vulnerable, compared with only 19% for aliens. Predicted climate change effects on freshwater environments will dramatically change the fish fauna of California. Most native fishes will suffer population declines and become more restricted in their distributions; some will likely be driven to extinction. Fishes requiring cold water (<22°C) are particularly likely to go extinct. In contrast, most alien fishes will thrive, with some species increasing in abundance and range. However, a few alien species will likewise be negatively affected through loss of aquatic habitats during severe droughts and physiologically stressful conditions present in most waterways during summer. Our method has high utility for predicting vulnerability to climate change of diverse fish species. It should be useful for setting conservation priorities in many different regions.

Building blocks of economic resilience to climate change: a south east Australian fisheries example

Climate change will impact on ecological, social, and economic elements of fisheries; however, the three are seldom considered in an integrated fashion. We develop a fishery-level assessment of economic resilience to climate change for the Tasmanian rock lobster fishery, a linked social–ecological system. We outline the main climate change forcing influences that link climate change to the fishery via changes in lobster abundance, distribution, and phenology. Using a bottom-up approach, we identify twelve economic attributes strongly related to the fisheries’ economic resilience to climate change. Resilience attributes are grouped according to the level of the economic domain (business, sectoral, and governance). Attributes are then evaluated to determine the overall economic resilience of the rock lobster fishery in the context of the specific nature of predicted climate change effects. We identify areas of low resilience in the economic sub-system for this fishery. Evaluating the economic resilience of regional fisheries using this integrated, interdisciplinary framework provides a practical, parsimonious, and conceptually sound basis for undertaking comprehensive and contextually tailored assessments of climate change impacts and economic vulnerability. The framework can be extended to include a broader range of climate change impacts and the social domain of the human sub-system.

Anticipating Stream Ecosystem Responses to Climate Change: Toward Predictions that Incorporate Effects Via Land–Water Linkages

Climate change (CC) is projected to increase the frequency and severity of natural disturbances (wildfires, insect outbreaks, and debris flows) and shift distributions of terrestrial ecosystems on a global basis. Although such terrestrial changes may affect stream ecosystems, they have not been incorporated into predictions of stream responses to CC. Here, we introduce a conceptual framework to evaluate to what extent responses of streams to CC will be driven by not only changes in thermal and hydrologic regimes, but also alterations of terrestrial processes. We focused on forested watersheds of western North America because this region is projected to experience CC-induced alteration of terrestrial processes. This provided a backdrop for investigating interactive effects of climate and terrestrial responses on streams. Because stream responses to terrestrial processes have been well-studied in contexts largely independent of CC research, we synthesized this knowledge to demonstrate how CC-induced alterations of terrestrial ecosystems may affect streams. Our synthesis indicated that altered terrestrial processes will change terrestrial–aquatic linkages and autotrophic production, potentially yielding greater sensitivity of streams to CC than would be expected based on shifts in temperature and precipitation regime alone. Despite uncertainties that currently constrain predictions regarding stream responses to these additional pathways of change, this synthesis highlighted broader effects of CC that require additional research. Based on widespread evidence that CC is linked to changing terrestrial processes, we conclude that accurate predictions of CC effects on streams may be coupled to the accuracy of predictions for long-term changes in terrestrial ecosystems.

Relations entre le niveau de risque psychosocial et le niveau de stress professionnel perçu chez les collaborateurs des agences commerciales d’un groupe industriel de fabrication de matériel électrique en France

Barrier islands shrub thickets, the dominant woody community of many Atlantic coast barrier islands, are very sensitive to changes in the freshwater lens and thus, constitute a strong indicator of summer drought. NDVI was computed from airborne images and multispectral images on Hog Island (VA, USA) to evaluate summer growing season changes in woody communities for better predictions of climate change effects. Patterns of NDVI were compared year to year and monthly relative to precipitation and water table depth at the appropriate temporal scale. The highest absolute values of NDVI as well as the larger surface covered by woody vegetation (NDVI > 0.5) occurred in the wet year (2004) with a bimodal distribution of NDVI values (around 0.65 and 0.9) while both dry years (2007 and 2008) showed similar values in maximum, mean and standard deviation and unimodal distributions (around 0.75) of NDVI values. Positive linear adjustments were obtained between maximum (r2 > 0.9) and mean NDVI (r2 > 0.87) and the accumulated rainfall in the hydrological year and the mean water table depth from the last rainfall event till the date of the image acquisition. The spatial variations revealed that water table depth behaved different in wet and dry years. In dry years there was a remarkable increase in mean and maximum values linearly related to water table depth. The highest slope of the adjustment in 2007 indicated a sharp response of vegetation in the driest year. Monthly series of NDVI showed the major role of lack of precipitation through July and August in 2007 with missing classes of NDVI above 0.8 and unimodal distributions in mid-late summer. Best linear fits (r2 close to 1) were obtained with rainfall at different temporal scales: accumulated rainfall in the hydrological year 2004 and accumulated rainfall in the last month previous to the date of 2007 image. Thus, in dry years productivity is closely related to water available from recent past as opposed to over the year for wet years. Good fits (r2 values higher than 0.88) were obtained between monthly decrease in water table depth and NDVI variables just in the dry year. These results demonstrate the important feedback between woody vegetation response to changes in the freshwater lens using empirical data and could apply to other systems with strong directional gradients in resources.

Compiling geophysical and geological information into a 3-D model of the glacially-affected island of Föhr

Abstract. Within the scope of climatic change and associated sea level rise, coastal aquifers are endangered and are becoming more a focus of research to ensure the future water supply in coastal areas. For groundwater modelling a good understanding of the geological/hydrogeological situation and the aquifer behavior is necessary. In preparation of groundwater modelling and assessment of climate change impacts on coastal water resources, we setup a geological/hydrogeological model for the North Sea Island of Föhr. Data from different geophysical methods applied from the air, the surface and in boreholes contribute to the 3-D model, e.g. airborne electromagnetics (SkyTEM) for spatial mapping the resistivity of the entire island, seismic reflections for detailed cross-sections in the groundwater catchment area, and geophysical borehole logging for calibration of these measurements. An iterative and integrated evaluation of the results from the different geophysical methods contributes to reliable data as input for the 3-D model covering the whole island and not just the well fields. The complex subsurface structure of the island is revealed. The local waterworks use a freshwater body embedded in saline groundwater. Several glaciations reordered the youngest Tertiary and Quaternary sediments by glaciotectonic thrust faulting, as well as incision and refill of glacial valleys. Both subsurface structures have a strong impact on the distribution of freshwater-bearing aquifers. A digital geological 3-D model reproduces the hydrogeological structure of the island as a base for a groundwater model. In the course of the data interpretation, we deliver a basis for rock identification. We demonstrate that geophysical investigation provide petrophysical parameters and improve the understanding of the subsurface and the groundwater system. The main benefit of our work is that the successful combination of electromagnetic, seismic and borehole data reveals the complex geology of a glacially-affected island. A sound understanding of the subsurface structure and the compilation of a 3-D model is imperative and the basis for a groundwater flow model to predict climate change effects on future water resources.

Climate change impacts on natural toxins in food production systems, exemplified by deoxynivalenol in wheat and diarrhetic shellfish toxins

Climate change is expected to affect food and feed safety, including the occurrence of natural toxins in primary crop and seafood production; however, to date, quantitative estimates are scarce. This study aimed to estimate the impact of climate change effects on mycotoxin contamination of cereal grains cultivated in the terrestrial area of north west Europe, and on the frequency of harmful algal blooms and contamination of shellfish with marine biotoxins in the North Sea coastal zone. The study focused on contamination of wheat with deoxynivalenol, and on abundance of Dinophysis spp. and the possible relationship with diarrhetic shellfish toxins. The study used currently available data and models. Global and regional climate models were combined with models of crop phenology, mycotoxin prediction models, hydrodynamic models and ecological models, with the output of one model being used as input for the other. In addition, statistical data analyses using existing national datasets from the study area were performed to obtain information on the relationships between Dinophysis spp. cell counts and contamination of shellfish with diarrhetic shellfish toxins as well as on frequency of cereal cropping. In this paper, a summary of the study is presented, and overall conclusions and recommendations are given. Climate change projections for the years 2031–2050 were used as the starting point of the analyses relative to a preceding 20-year baseline period from which the climate change signal was calculated. Results showed that, in general, climate change effects lead to advanced flowering and harvest of wheat, and increased risk of contamination of wheat with deoxynivalenol. Blooms of dinoflagellates were estimated to occur more often. If the group of Dinophysis spp. behaves similarly to other flagellates in the future then frequency of harmful algal blooms of Dinophysis spp. may also increase, but consequences for contamination of shellfish with diarrhetic shellfish toxins are uncertain. Climate change will also have indirect effects on toxin contamination, which may be equally important. For example, the frequency of cropping of wheat and maize in north Europe was projected to increase under climate change, which will also increase the risk of contamination of the grains with deoxynivalenol. Risk managers are encouraged to consider the entire range of the predictions of climate change effects on food safety hazards, rather than median or average values only. Furthermore, it is recommended to closely monitor levels of mycotoxins and marine biotoxins in the future, in particular related to risky situations associated with favourable climatic conditions for toxin producing organisms. In particular, it is important to pay attention to the continuity of collecting the right data, and the availability and accessibility of databases. On a European level, it is important to stress the need for harmonisation of terminology and data collection.

Predicting climate change effects on agriculture from ecological niche modeling: who profits, who loses?

The susceptibility of agriculture to changing environmental conditions is arguably the most dangerous short-term consequence of climate change, and predictions on the geography of changes will be useful for implementing mitigation strategies. Ecological niche modeling (ENM) is a technique used to relate presence records of species to environmental variables. By extrapolation, ENM maps the suitability of a landscape for the species in question. Recently, ENM was successfully applied to predict the geographic distribution of agriculture. Using climate and soil conditions as predictor variables, agricultural suitability was mapped across the Old World. Here, I present analogous ENM-based maps of the suitability for agriculture under climate change scenarios for the year 2050. Deviations of predicted scenarios from a current conditions model were analyzed by (1) comparing relative average change across regions, and (2) by relating country-wide changes to the data indicative of the wealth of nations. The findings indicate that different regions vary considerably in whether they win or lose in agricultural suitability, even if average change across the entire study region is small. A positive relationship between the wealth of nations and change in agriculture conditions was found, but variability around this trend was high. Parts of Africa, Europe and southern and eastern Asia were predicted to be particularly negatively affected, while north-eastern Europe, among other regions, can expect more favorable conditions for agriculture. The results are presented as an independent “second opinion” to previously published, more complex forecasts on agricultural productivity and food supply variability due to climatic change, which were based on fitting environmental variables to yield statistics.

NDVI as an indicator for changes in water availability to woody vegetation

Barrier islands shrub thickets, the dominant woody community of many Atlantic coast barrier islands, are very sensitive to changes in the freshwater lens and thus, constitute a strong indicator of summer drought. NDVI was computed from airborne images and multispectral images on Hog Island (VA, USA) to evaluate summer growing season changes in woody communities for better predictions of climate change effects. Patterns of NDVI were compared year to year and monthly relative to precipitation and water table depth at the appropriate temporal scale. The highest absolute values of NDVI as well as the larger surface covered by woody vegetation (NDVI>0.5) occurred in the wet year (2004) with a bimodal distribution of NDVI values (around 0.65 and 0.9) while both dry years (2007 and 2008) showed similar values in maximum, mean and standard deviation and unimodal distributions (around 0.75) of NDVI values. Positive linear adjustments were obtained between maximum (r2>0.9) and mean NDVI (r2>0.87) and the accumulated rainfall in the hydrological year and the mean water table depth from the last rainfall event till the date of the image acquisition. The spatial variations revealed that water table depth behaved different in wet and dry years. In dry years there was a remarkable increase in mean and maximum values linearly related to water table depth. The highest slope of the adjustment in 2007 indicated a sharp response of vegetation in the driest year. Monthly series of NDVI showed the major role of lack of precipitation through July and August in 2007 with missing classes of NDVI above 0.8 and unimodal distributions in mid-late summer. Best linear fits (r2 close to 1) were obtained with rainfall at different temporal scales: accumulated rainfall in the hydrological year 2004 and accumulated rainfall in the last month previous to the date of 2007 image. Thus, in dry years productivity is closely related to water available from recent past as opposed to over the year for wet years. Good fits (r2 values higher than 0.88) were obtained between monthly decrease in water table depth and NDVI variables just in the dry year. These results demonstrate the important feedback between woody vegetation response to changes in the freshwater lens using empirical data and could apply to other systems with strong directional gradients in resources.

A single climate driver has direct and indirect effects on insect population dynamics

Weather drives population dynamics directly, through effects on vital rates, or indirectly, through effects on the population's competitors, predators or prey and thence on vital rates. Indirect effects may include non-additive interactions with density dependence. Detection of climate drivers is critical to predicting climate change effects, but identification of potential drivers may depend on knowing the underlying mechanisms. For the butterfly Speyeria mormonia, one climate driver, snow melt date, has multiple effects on population growth. Snow melt date in year t has density-dependent indirect effects. Through frost effects, early snow melt decreases floral resources, thence per-capita nectar availability, which determines fecundity in the lab. Snow melt date in year t + 1 has density-independent direct effects. These effects explain 84% of the variation in population growth rate. One climate parameter thus has multiple effects on the dynamics of a species with non-overlapping generations, with one effect not detectable without understanding the underlying mechanism.

Demographic response by a small epiphytic orchid

Biotic changes are an inevitable consequence of climate change. Epiphytes may be more susceptible to changes in climate variation, but data regarding responses to climate variability under field conditions are limited. We evaluated whether the abundance of demographic stages in the epiphytic orchid Lepanthes rupestris at the Luquillo Experimental Forest in Puerto Rico was associated with short-term changes in climate variation over an 8-yr period. We used cross-correlation analyses to evaluate associations between the abundance of seedlings, juveniles, adults, and fruits per subpopulation, population growth, colonization and extinction rates in L. rupestris with variables related to precipitation and temperature, with and without lag- responses. We detected significant negative correlations between the average number of seedlings and the number of dry days, between the average number of fruits and minimum average temperature with a 6-mo response lag, and between the average number of adults and the maximum temperature with a 1-yr response lag. Neither population growth rate nor probability of colonization and extinction were directly related to climatic variation between 2000 and 2007. Associations between climatic variables and demographic stages could have negative implications for this orchid within the context of expected drying trends in the Caribbean. Results argue for the establishment of long-term monitoring studies of orchid populations, because only long-term studies would provide the appropriate temporal scale to detect and predict climate change effects and adaptive management of orchid populations.

Identifying the contribution of physical and chemical stressors to the daily number of hospital admissions implementing an artificial neural network model

The relative contribution of chemical (air pollution) and physical (temperature and humidity) health stressors to urban hospitalization rates is the objective of the current study. The data used in the study included the daily number of hospital admissions due to cardiorespiratory diseases, hourly mean concentrations of CO, NO2, SO2, O3, and black smoke in several monitoring stations, as well as meteorological data (temperature, relative humidity, wind speed/direction) in Athens, Greece. The relations among the data above were studied using Generalized Linear Models (GLMs) and Artificial Neural Networks (ANNs). Elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg/m3 leads to an increase of 8.6% in hospital admissions), followed by O3 and the other atmospheric pollutants (CO, NO2, and SO2). Meteorological parameters also play a decisive role in the formation of air-pollutant levels affecting public health. Both models performed adequately, however the ANN adaptation in complicate environmental issues results in improved modeling outcomes compared to the GLMs. The major finding of the study lies on the flexibility and the adaptation of the methodological approach for assessing non-linear problems and specifically the effect of non-linear parameters, such as the temperature. Moreover, the importance of temperature is established even when the whole dataset is modeled, reflecting the dual mode effect of temperature on cardiorespiratory admissions. Considering the urgent challenge to predict climate change effects on public health, a mathematical tool that successfully captures the direct impact of the affecting meteorological parameters (temperature and humidity) to health outcomes is of high added value.

Impacts of climate change on Swiss biodiversity: An indicator taxa approach

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of ‘greenhouse’ gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.

Predicting climate change effects on wildfires requires linking processes across scales

AbstractAccurate process‐based prediction of climate change effects on wildfires requires coupling processes across orders of magnitude of time and space scales, because climate dynamic processes operate at relatively large scales (e.g., hemispherical and centennial), but fire behavior processes operate at relatively small scales (e.g., molecules and microseconds). In this review, we outline some of the current understanding of the processes by which climate/meteorology controls wildfire behavior by focusing on four critical stages of wildfire development: (1) fuel drying, (2) ignition, (3) spread, and (4) extinction. We identify some key mechanisms that are required for predicting climate change effects on fires, as well as gaps in our understanding of the processes linking climate and fires. It is currently not possible to make accurate predictions of climate change effects on wildfires due to the limited understanding of the linkage between general circulation model outputs and the local‐scale meteorology to which fire behavior processes respond. WIREs Clim Change 2011 2 99–112 DOI: 10.1002/wcc.92This article is categorized under: Paleoclimates and Current Trends &gt; Earth System Behavior

The importance of terrestrial resource subsidies for shredders in open-canopy streams revealed by stable isotope analysis

Many streams run through naturally-unforested, agricultural, and residential landscapes and thus do not have closed riparian canopies. Little is known of food web dynamics and ecosystem function in such open-canopy streams. Similarly, our knowledge of ecosystem processes in intermittent streams and effects of drought on stream ecosystem function are limited, despite that predictions of climate change effects include increased frequency and duration of droughts in freshwaters. The aim of my thesis was to increase our knowledge of invertebrate shredder assemblages and ecosystem function in open-canopy intermittent streams and to reveal the role of terrestrial organic matter in open-canopy streams. Invertebrate shredders, as primary consumers of detritus, significantly contribute to the ecosystem function decomposition of organic matter. Thereby, shredders are important vectors for transferring detrital energy into stream food webs. I found high-density and species-rich shredder assemblages in three open-canopy intermittent streams on the island of Oland in the southern Baltic Sea, Sweden. My results showed that terrestrially derived organic matter was the shredder’s main food source and the amount of high-quality CPOM potentially limited shredder production. However, through supplementing their feeding with algae, a high shredder production, similar to production estimates in forested permanent streams, could be maintained in these open-canopy intermittent streams. Instead, my results indicate that the primary physical factor constraining shredder production in intermittent streams is the length of the summer drought period. Furthermore, drying simulated as decreasing water levels in an experiment, decreased invertebrate shredder feeding activity and consequently, the breakdown rate of organic matter. Drying also altered a caddisfly shredders’ life cycle phenology and such evident induction of earlier pupation due to drying has not been shown for aquatic insects earlier. Food webs and ecosystem function and processes in open-canopy and intermittent streams deserve further attention, especially as these types of streams are very common worldwide. My findings indicate that the energy base in open-canopy streams may be terrestrially derived organic matter, as in forested streams, but constraints imposed by habitat traits and differences in organic matter input size may have significant consequences on stream productivity. My results may be important for increased understanding of potential effects of land use changes (i.e. forestry, agriculture, urbanization) and environmental changes (i.e. climate change) on stream ecosystems.

Explaining regional variability in copepod recruitment: Implications for a changing climate

Characterizing environmental effects on copepod production and their ecological roles is complicated by multiple physical (e.g. temperature) and biological (e.g. food, predation) factors controlling multiple aspects of copepod physiology and demography. For example, data for two regions in eastern Canada (St. John’s, Newfoundland and Halifax, Nova Scotia) indicate that subtle differences in environmental conditions lead to significant differences in seasonal copepod ( Calanus finmarchicus) recruitment timing and magnitude. Here, we quantify how environmental variability influences C. finmarchicus physiology and demography leading to observed regional and seasonal variations in abundance off St. John’s and Halifax. We apply a stochastic individual-based model (IBM) for copepod population dynamics to simulate the seasonal variation in C. finmarchicus abundance of egg through copepodite 1 (C1) stages at the two sites using year-specific local forcing from multi-year data. The model includes individual variability in development, egg production and mortality rates with resulting seasonal C1 abundance averaged among years and compared to analogous observations. We find temperature has a dominant effect on both development and egg production rates while egg recruitment is affected by temperature and female abundance at both sites. We show that mortality rate characterization has a strong influence on modeled abundances, and site-specific environmentally dependent mortality rates are necessary to produce results consistent with observations (temperature vs. food vs. cannibalism via females). Results indicate that prediction of climate change effects on copepod abundance and their ecological roles requires consideration of biological (e.g. chlorophyll a, female abundance) as well as physical (e.g. temperature) factors. In particular, estimates of abundances during the onset of C1 recruitment (i.e. their arrival on the larval fish prey field) are improved by 67–94% when the influence of biological factors on mortality rates are considered.

Potential influence of climate change on vector-borne and zoonotic diseases: a review and proposed research plan.

BackgroundBecause of complex interactions of climate variables at the levels of the pathogen, vector, and host, the potential influence of climate change on vector-borne and zoonotic diseases (VBZDs) is poorly understood and difficult to predict. Climate effects on the nonvector-borne zoonotic diseases are especially obscure and have received scant treatment.ObjectiveWe described known and potential effects of climate change on VBZDs and proposed specific studies to increase our understanding of these effects. The nonvector-borne zoonotic diseases have received scant treatment and are emphasized in this paper.Data sources and synthesisWe used a review of the existing literature and extrapolations from observations of short-term climate variation to suggest potential impacts of climate change on VBZDs. Using public health priorities on climate change, published by the Centers for Disease Control and Prevention, we developed six specific goals for increasing understanding of the interaction between climate and VBZDs and for improving capacity for predicting climate change effects on incidence and distribution of VBZDs.ConclusionsClimate change may affect the incidence of VBZDs through its effect on four principal characteristics of host and vector populations that relate to pathogen transmission to humans: geographic distribution, population density, prevalence of infection by zoonotic pathogens, and the pathogen load in individual hosts and vectors. These mechanisms may interact with each other and with other factors such as anthropogenic disturbance to produce varying effects on pathogen transmission within host and vector populations and to humans. Because climate change effects on most VBZDs act through wildlife hosts and vectors, understanding these effects will require multidisciplinary teams to conduct and interpret ecosystem-based studies of VBZD pathogens in host and vector populations and to identify the hosts, vectors, and pathogens with the greatest potential to affect human populations under climate change scenarios.

Winter climate change in alpine tundra: plant responses to changes in snow depth and snowmelt timing

Snow is an important environmental factor in alpine ecosystems, which influences plant phenology, growth and species composition in various ways. With current climate warming, the snow-to-rain ratio is decreasing, and the timing of snowmelt advancing. In a 2-year field experiment above treeline in the Swiss Alps, we investigated how a substantial decrease in snow depth and an earlier snowmelt affect plant phenology, growth, and reproduction of the four most abundant dwarf-shrub species in an alpine tundra community. By advancing the timing when plants started their growing season and thus lost their winter frost hardiness, earlier snowmelt also changed the number of low-temperature events they experienced while frost sensitive. This seemed to outweigh the positive effects of a longer growing season and hence, aboveground growth was reduced after advanced snowmelt in three of the four species studied. Only Loiseleuria procumbens, a specialist of wind exposed sites with little snow, benefited from an advanced snowmelt. We conclude that changes in the snow cover can have a wide range of species-specific effects on alpine tundra plants. Thus, changes in winter climate and snow cover characteristics should be taken into account when predicting climate change effects on alpine ecosystems.