Integrated Monitoring and Information Systems for Managing Aquatic Invasive Species in a Changing Climate

Abstract:  Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.     

Future habitat loss and extinctions driven by land‐use change in biodiversity hotspots under four scenarios of climate‐change mitigation

Numerous species have been pushed into extinction as an increasing portion of Earth's land surface has been appropriated for human enterprise. In the future, global biodiversity will be affected by both climate change and land‐use change, the latter of which is currently the primary driver of species extinctions. How societies address climate change will critically affect biodiversity because climate‐change mitigation policies will reduce direct climate‐change impacts; however, these policies will influence land‐use decisions, which could have negative impacts on habitat for a substantial number of species. We assessed the potential impact future climate policy could have on the loss of habitable area in biodiversity hotspots due to associated land‐use changes. We estimated past extinctions from historical land‐use changes (1500–2005) based on the global gridded land‐use data used for the Intergovernmental Panel on Climate Change Fifth Assessment Report and habitat extent and species data for each hotspot. We then estimated potential extinctions due to future land‐use changes under alternative climate‐change scenarios (2005–2100). Future land‐use changes are projected to reduce natural vegetative cover by 26‐58% in the hotspots. As a consequence, the number of additional species extinctions, relative to those already incurred between 1500 and 2005, due to land‐use change by 2100 across all hotspots ranged from about 220 to 21000 (0.2% to 16%), depending on the climate‐change mitigation scenario and biological factors such as the slope of the species–area relationship and the contribution of wood harvest to extinctions. These estimates of potential future extinctions were driven by land‐use change only and likely would have been higher if the direct effects of climate change had been considered. Future extinctions could potentially be reduced by incorporating habitat preservation into scenario development to reduce projected future land‐use changes in hotspots or by lessening the impact of future land‐use activities on biodiversity within hotspots.     

Evaluating and managing wildlife impacts of climate change under uncertainty

Wildlife managers face the daunting task of managing wildlife in light of uncertainty about the nature and extent of future climate change and variability and its potential adverse impacts on wildlife. A conceptual framework is developed for managing wildlife under such uncertainty. The framework uses fuzzy logic to test hypotheses about the extent of the wildlife impacts of past climate change and variability, and fuzzy multiple attribute evaluation to determine best compensatory management actions for adaptively managing the potential adverse impacts of future climate change and variability on wildlife. A compensatory management action is one that can offset some of the potential adverse impacts of climate change and variability on wildlife. Implementation of the proposed framework requires wildlife managers to: (1) select climate impact states, hypotheses about climate impact states, possible management actions for alleviating adverse wildlife impacts of climate change and variability, and future climate change scenarios; (2) choose biological attributes or indicators of species integrity; (3) adjust those attributes for changes in non-climatic variables; (4) define linguistic variables and associated triangular fuzzy numbers for rating both the acceptability of biological conditions under alternative management actions and the relative importance of biological attributes; (5) select minimum or maximum acceptable levels of the attributes and reliability levels for chance constraints on the biological attributes; and (6) define fuzzy sets on the extent of species integrity and biological conditions and select a fuzzy relation between species integrity and biological conditions. A constructed example is used to illustrate a hypothetical application of the framework by a wildlife management team. An overall best compensatory management action across all climate change scenarios is determined using the minimax regret criterion, which is appropriate when the management team cannot assign or is unwilling to assign probabilities to the future climate change scenarios. Application of the framework can be simplified and expedited by incorporating it in a web-based, interactive, decision support tool.     

Range-wide effects of breeding- and nonbreeding-season climate on the abundance of a Neotropical migrant songbird

Geographic variation in the population dynamics of a species can result from regional variability in climate and how it affects reproduction and survival. Identifying such effects for migratory birds requires the integration of population models with knowledge of migratory connectivity between breeding and nonbreeding areas. We used Bayesian hierarchical models with 26 years of Breeding Bird Survey data (1982-2007) to investigate the impacts of breeding- and nonbreeding-season climate on abundance of American Redstarts (Setophaga ruticilla) across the species range. We focused on 15 populations defined by Bird Conservation Regions, and we included variation across routes and observers as well as temporal trends and climate effects. American Redstart populations that breed in eastern North America showed increased abundance following winters with higher plant productivity in the Caribbean where they are expected to overwinter. In contrast, western breeding populations showed little response to conditions in their expected wintering areas in west Mexico, perhaps reflecting lower migratory connectivity or differential effects of winter rainfall on individuals across the species range. Unlike the case with winter climate, we found few effects of temperature prior to arrival in spring (March-April) or during the nesting period (May-June) on abundance the following year. Eight populations showed significant changes in abundance, with the steepest declines in the Atlantic Northern Forest (-3.4%/yr) and the greatest increases in the Prairie Hardwood Transition (4%/yr). This study emphasizes how the effects of climate on populations of migratory birds are context dependent and can vary depending on geographic location and the period of the annual cycle. Such knowledge is essential for predicting regional variation in how populations of a species might vary in their response to climate change.     

Role of multidecadal climate variability in a range extension of pinyon pine

Evidence from woodrat middens and tree rings at Dutch John Mountain (DJM) in northeastern Utah reveal spatiotemporal patterns of pinyon pine (Pinus edulis Engelm.) colonization and expansion in the past millennium. The DJM population, a northern outpost of pinyon, was established by long-distance dispersal (approximately 40 km). Growth of this isolate was markedly episodic and tracked multidecadal variability in precipitation. Initial colonization occurred by AD 1246, but expansion was forestalled by catastrophic drought (1250-1288), which we speculate produced extensive mortality of Utah Juniper (Juniperus osteosperma (Torr.) Little), the dominant tree at DJM for the previous approximately 8700 years. Pinyon then quickly replaced juniper across DJM during a few wet decades (1330-1339 and 1368-1377). Such alternating decadal-scale droughts and pluvial events play a key role in structuring plant communities at the landscape to regional level. These decadal-length precipitation anomalies tend to be regionally coherent and can synchronize physical and biological processes across large areas. Vegetation forecast models must incorporate these temporal and geographic aspects of climate variability to accurately predict the effects of future climate change.     

Climate change and poverty in Africa

Africa is most vulnerable to climate change, although it makes the least contribution to factors that result in global and regional climatic changes. High levels of vulnerability and low adaptive capacity across the continent have been linked to, among other things, poverty. This paper discusses and analyses the relationship between climate change and poverty in Africa. It investigates the relationship between climate change and poverty patterns in Africa, analyses the resultant impact, and discusses potential adaptation policies for moderating the consequences of climatic changes on poverty in the region. The record shows that climate change is happening. What is not discussed or is little researched is the potential devastating impact of climate change on socio-economic development in Africa and the policy measures available to the continent for adaptation.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Klimafolgenforschung

Some case studies are described to show progress, potentials and limits of present day climate impact research. The examples given cover impacts on Lakes worldwide, Europe's cost lines, landscapes in the USA, South America and in Germany and on the people living there. Forecasts using not only future scenarios of climatic but of socieal change as well are rare. It is rather state of the art to use future climate scenarios to analyse the vulnerability of today's regional structures. The objective is to identify weak points and measures to eliminate them. Mostly the analysis is based on the consideration of global climate scenarios on one hand and regionally specific economic patterns on the other. But now regionalized climate models and scenarios are used more and more to describe climate change. In most impact studies more accurate and concrete results are obtained and this is demonstrated in the Brandenburg study.     

Climate correlates of 20 years of trophic changes in a high-elevation riparian system

The consequences of climate change for ecosystem structure and function remain largely unknown. Here, I examine the ability of climate variation to explain long-term changes in bird and plant populations, as well as trophic interactions in a high-elevation riparian system in central Arizona, USA, based on 20 years of study. Abundances of dominant deciduous trees have declined dramatically over the 20 years, correlated with a decline in overwinter snowfall. Snowfall can affect overwinter presence of elk, whose browsing can significantly impact deciduous tree abundance. Thus, climate may affect the plant community indirectly through effects on herbivores, but may also act directly by influencing water availability for plants. Seven species of birds were found to initiate earlier breeding associated with an increase in spring temperature across years. The advance in breeding time did not affect starvation of young or clutch size. Earlier breeding also did not increase the length of the breeding season for single-brooded species, but did for multi-brooded species. Yet, none of these phenology-related changes was associated with bird population trends. Climate had much larger consequences for these seven bird species by affecting trophic levels below (plants) and above (predators) the birds. In particular, the climate-related declines in deciduous vegetation led to decreased abundance of preferred bird habitat and increased nest predation rates. In addition, summer precipitation declined over time, and drier summers also were further associated with greater nest predation in all species. The net result was local extinction and severe population declines in some previously common bird species, whereas one species increased strongly in abundance, and two species did not show clear population changes. These data indicate that climate can alter ecosystem structure and function through complex pathways that include direct and indirect effects on abundances and interactions of multiple trophic components.     

Correcting climate model simulations in Heihe River using the multivariate bias correction package

The simulations from climate models require bias correction prior to use in impact assessments or when used as predictors in statistical or dynamic downscaling models. Recent works have sought to address each of these limitations and the results are the Multivariate Recursive Nesting Bias Correction (MRNBC) and Multivariate recursive Quantile-matching Nested Bias Correction (MRQNBC) methods. The model was applied to a mountain region of Heihe River. A comparison of the historical and generated statistics shows that the model preserves all the important characteristics of meteorological variables at daily, monthly, seasonally and annual time scales. This study has documented the performance of Multivariate Recursive Nesting Bias Correction to remove the discrepancy between the predictors in the simulated GCM and the reanalysis NCEP data and assess the projected future precipitation accuracy in the headwater region of Heihe River. A relatively high spatial resolution GCM outputs—ACCESS1-3—from the CMIP5 Earth System Models (ESMs) was employed to downscale for the historical 1960–2005 and the future period 2010–2100 under the scenarios of Representative Concentration Pathways RCP4.5 and RCP8.5. The MRNBC method can dramatically increase the performance of the simulated precipitation data. Verified by statistical score metrics applied for evaluation of the results, the developed method appears to be an important statistical tool in the correction of the bias between the GCM output and the reanalysis data, leading to significant improvements in the predictive performance accuracy of the precipitation projections. The projected precipitation under RCP8.5 appeared to exhibit the significant increasing trend relative to the RCP4.5 scenario in the headwater region of Heihe River. Future precipitation will increasing by 8% and 20% for near and long term period under RCP4.5 and increasing 14% and 37% for near and long term period, under RCP8.5, respectively.     

Invasion, Disturbance, and Competition: Modeling the Fate of Coastal Plant Populations

Abstract:  Wetland habitats are besieged by biotic and abiotic disturbances such as invasive species, hurricanes, habitat fragmentation, and salinization. Predicting how these factors will alter local population dynamics and community structure is a monumental challenge. By examining ecologically similar congeners, such as Iris hexagona and I. pseudacorus (which reproduce clonally and sexually and tolerate a wide range of environmental conditions), one can identify life-history traits that are most influential to population growth and viability. We combined empirical data and stage-structured matrix models to investigate the demographic responses of native ( I. hexagona ) and invasive ( I. pseudacorus ) plant populations to hurricanes and salinity stress in freshwater and brackish wetlands. In our models I. hexagona and I. pseudacorus responded differently to salinity stress, and species coexistence was rare. In 82% of computer simulations of freshwater marsh, invasive iris populations excluded the native species within 50 years, whereas native populations excluded the invasive species in 99% of the simulations in brackish marsh. The occurrence of hurricanes allowed the species to coexist, and species persistence was determined by the length of time it took the ecosystem to recover. Rapid recovery (2 years) favored the invasive species, whereas gradual recovery (30 years) favored the native species. Little is known about the effects of hurricanes on competitive interactions between native and invasive plant species in marsh ecosystems. Our models contribute new insight into the relationship between environmental disturbance and invasion and demonstrate how influential abiotic factors such as climate change will be in determining interspecific interactions.     

Matching the Multiple Scales of Conservation with the Multiple Scales of Climate Change

Abstract:  To anticipate the rapidly changing world resulting from global climate change, the projections of climate models must be incorporated into conservation. This requires that the scales of conservation be aligned with the scales of climate-change projections. We considered how conservation has incorporated spatial scale into protecting biodiversity, how the projections of climate-change models vary with scale, and how the two do or do not align. Conservation planners use information about past and current ecological conditions at multiple scales to identify conservation targets and threats and guide conservation actions. Projections of climate change are also made at multiple scales, from global and regional circulation models to projections downscaled to local scales. These downscaled projections carry with them the uncertainties associated with the broad-scale models from which they are derived; thus, their high resolution may be more apparent than real. Conservation at regional or global scales is about establishing priorities and influencing policy. At these scales, the coarseness and uncertainties of global and regional climate models may be less important than what they reveal about possible futures. At the ecoregional scale, the uncertainties associated with downscaling climate models become more critical because the distributions of conservation targets on which plans are founded may shift under future climates. At a local scale, variations in topography and land cover influence local climate, often overriding the projections of broad-scale climate models and increasing uncertainty. Despite the uncertainties, ecologists and conservationists must work with climate-change modelers to focus on the most likely projections. The future will be different from the past and full of surprises; judicious use of model projections at appropriate scales may help us prepare.     

Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species-energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients. Despite its common status, M. lucifugus was only detected during -50% of the surveys in occupied sample units. The overall naive estimate for the proportion of the study region occupied by the species was 0.69, but after accounting for imperfect detection, this increased to -0.90. Our models provide evidence of an association between NPP and forest cover and M. lucifugus distribution, with implications for the projected effects of accelerated climate change in the region, which include net aridification as snowpack and stream flows decline. Annual turnover, the probability that an occupied sample unit was a newly occupied one, was estimated to be low (-0.04-0.14), resulting in flat trend estimated with relatively high precision (SD = 0.04). We mapped the variation in predicted occurrence probabilities and corresponding prediction uncertainty along the productivity gradient. Our results provide a much needed baseline against which future anticipated declines in M. lucifugus occurrence can be measured. The dynamic distribution modeling approach has broad applicability to regional bat monitoring efforts now underway in several countries and we suggest ways to improve and expand our grid-based monitoring program to gain robust insights into bat population status and trend across large portions of North America.     

Integrated model projections of climate change impacts on a North American lake

Climate change is likely to impact terrestrial and aquatic ecosystems via numerous physical and biological mechanisms. This study outlines a framework for projecting potential impacts of climate change on lakes using linked environmental models. Impacts of climate drivers on catchment hydrology and thermal balance in Onondaga Lake (New York State) are simulated using mechanistic models HSPF and UFILS4. Outputs from these models are fed into a lake ecosystem model, developed in AQUATOX. Watershed simulations project increases in the magnitude of peak flows and consequent increases in catchment nutrient export as the magnitude of extreme precipitation events increases. This occurs concurrently with a decrease in annual stream discharge as a result of increased evapotranspiration. Simulated lake water temperatures increase by as much as 5 °C during the 2040-2069 time period, accompanied by a prolonging of the duration of summer stratification. Projected changes include shifts in the timing of nutrient cycling between lake sediments and water column. Plankton taxa projected to thrive under climate change include green algae and Bosmina longirostris. Responses for species at higher trophic levels are mixed. Benthic macroinvertebrates may either prosper (zebra mussels) or decline (chironomids), while fish (e.g., gizzard shad) exhibit high seasonal variability without any clear trend.     

Toward a Management Framework for Networks of Protected Areas in the Face of Climate Change

Abstract: Networks of sites of high importance for conservation of biological diversity are a cornerstone of current conservation strategies but are fixed in space and time. As climate change progresses, substantial shifts in species’ ranges may transform the ecological community that can be supported at a given site. Thus, some species in an existing network may not be protected in the future or may be protected only if they can move to sites that in future provide suitable conditions. We developed an approach to determine appropriate climate‐change adaptation strategies for individual sites within a network that was based on projections of future changes in the relative proportions of emigrants (species for which a site becomes climatically unsuitable), colonists (species for which a site becomes climatically suitable), and persistent species (species able to remain within a site despite the climatic change). Our approach also identifies key regions where additions to a network could enhance its future effectiveness. Using the sub‐Saharan African Important Bird Area (IBA) network as a case study, we found that appropriate conservation strategies for individual sites varied widely across sub‐Saharan Africa, and key regions where new sites could help increase network robustness varied in space and time. Although these results highlight the potential difficulties within any planning framework that seeks to address climate‐change adaptation needs, they demonstrate that such planning frameworks are necessary, if current conservation strategies are to be adapted effectively, and feasible, if applied judiciously.     

温带落叶林的植物物候特征及其对气候变化的响应

植被物候是气候变化对生物圈产生长期或短期影响的重要指示因子。气候变化已经明显改变了许多物种的营养生长和繁殖物候,尤其是在温带地区。研究温带森林物候变化及其对全球变暖的响应,对认识森林物种共存,协同进化以及森林保护和经营等有重要意义。通过概述温带森林下物候研究的进展发现,光照和积温是影响木本植物展叶及繁殖物候的关键因素,林下层树木通过更早展叶,以尽量减少生长季林冠层遮阴对下层树木生长的影响,更早时期开花的树木具有从顶部向四周次第开花的时空格局,林冠层树种开花具有较好的同步性。而草本植物的物候通常受融雪时间和冠层动态的影响更大,并且,温带森林下不同生活史对策的草本植物的物候特征对气候变化的响应也不尽相同,存在明显的季节动态。繁殖物候、光照的季节变化、光合特征、授粉成功之间的联系决定了林下不同繁殖特性的草本植物的繁殖成功率。量化的、多指标、多对象的定位监测是精准物候研究的基础,物候变化的机理和建立可预测的物候模型将是未来研究的重点。     

Fire Management,Managed Relocation,and Land Conservation Options for Long‐Lived Obligate Seeding Plants under Global Changes in Climate,Urbanization, and Fire Regime

Most species face multiple anthropogenic disruptions. Few studies have quantified the cumulative influence of multiple threats on species of conservation concern, and far fewer have quantified the potential relative value of multiple conservation interventions in light of these threats. We linked spatial distribution and population viability models to explore conservation interventions under projected climate change, urbanization, and changes in fire regime on a long‐lived obligate seeding plant species sensitive to high fire frequencies, a dominant plant functional type in many fire‐prone ecosystems, including the biodiversity hotspots of Mediterranean‐type ecosystems. First, we investigated the relative risk of population decline for plant populations in landscapes with and without land protection under an existing habitat conservation plan. Second, we modeled the effectiveness of relocating both seedlings and seeds from a large patch with predicted declines in habitat area to 2 unoccupied recipient patches with increasing habitat area under 2 projected climate change scenarios. Finally, we modeled 8 fire return intervals (FRIs) approximating the outcomes of different management strategies that effectively control fire frequency. Invariably, long‐lived obligate seeding populations remained viable only when FRIs were maintained at or above a minimum level. Land conservation and seedling relocation efforts lessened the impact of climate change and land‐use change on obligate seeding populations to differing degrees depending on the climate change scenario, but neither of these efforts was as generally effective as frequent translocation of seeds. While none of the modeled strategies fully compensated for the effects of land‐use and climate change, an integrative approach managing multiple threats may diminish population declines for species in complex landscapes. Conservation plans designed to mitigate the impacts of a single threat are likely to fail if additional threats are ignored. Manejo de Incendios, Reubicación Administrada y Opciones de Conservación de Suelo para Plantas de Vida Larga con Sembrado Obligado bajo los Cambios Globales en el Clima, la Urbanización y el Régimen de Incendios     

Rainfall-human-spatial interactions in a salinity-prone agricultural region of the Western Australian wheat-belt

To explore the complexity of temporal and spatial dynamics of an agricultural landscape under various external and internal driven scenarios, SimKat, an agent-based model, has been developed with the simulation computer program CORMAS. This model combines simplified bio-physical processes of land cover, regional dry-land salinity changes, rainfall impact on productivity, farm profitability and the complexity of land-use decisions of individual farmers in a dry-land agricultural catchment (no irrigation). In this model, simulated farmers formulate individual decisions dealing with land-use changes based on the combined performance of their past land cover productivity and market returns. The willingness to adapt to market drivers and the ability to maximize returns vary between farmers. In addition, farmers in the model can demonstrate various attitudes towards dry-land salinity mitigation as a consequence of experiencing and perceiving salinity on their farm, in the neighborhood or across the entire region. Consequently, farmers can adopt land cover strategies aimed at reducing dry-land salinity. Aggregating the simulated individual behavior of farmers combined with historical rainfall and market price records, reproduced similar aggregated trends of land-cover changes, regional salinity change and farm number decline as observed in the last 20 years in the subject region (Katanning, Western Australia). Using the model in an initial exploratory study on the impact of rainfall variability and change highlighted the importance of average rainfall decline and the widespread willingness of farmers to adapt perennial vegetation in their farming systems to combat regional dry-land salinity. Rainfall decline, as one of the observed consequences of climate change in this region, can also lead to prolonged sequences of dry seasons in the future. Adaptation by farmers to sequences of dry and wet seasons, rather than an average trend in rainfall, seems to be critical for farm survival in this region. Intensifying cropping during wet seasons to maximize farm returns can increase vulnerability in subsequent periods of dry seasons, in particular where alternative income from pasture and sheep production has been lost in the adaptation process.     

The Melting Himalayas: Cascading Effects of Climate Change on Water, Biodiversity, and Livelihoods

Abstract:  The Greater Himalayas hold the largest mass of ice outside polar regions and are the source of the 10 largest rivers in Asia. Rapid reduction in the volume of Himalayan glaciers due to climate change is occurring. The cascading effects of rising temperatures and loss of ice and snow in the region are affecting, for example, water availability (amounts, seasonality), biodiversity (endemic species, predator–prey relations), ecosystem boundary shifts (tree-line movements, high-elevation ecosystem changes), and global feedbacks (monsoonal shifts, loss of soil carbon). Climate change will also have environmental and social impacts that will likely increase uncertainty in water supplies and agricultural production for human populations across Asia. A common understanding of climate change needs to be developed through regional and local-scale research so that mitigation and adaptation strategies can be identified and implemented. The challenges brought about by climate change in the Greater Himalayas can only be addressed through increased regional collaboration in scientific research and policy making.     

Phenological tracking enables positive species responses to climate change

Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically "track" climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlier-active competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced their phenology with warming also increased their performance, whereas those that did not advance tended to decline in performance with warming. This indicates that species that cannot phenologically "track" climate may be at increased risk with future climate change, and it suggests that phenological monitoring may provide an important tool for setting future conservation priorities.