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Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. [ABSTRACT FROM AUTHOR]

This paper investigates how former hunter-gatherers living along the southern North Sea coast in NW Europe adapted to long-term and short-term climatic and environmental changes at the beginning of the Holocene. It is argued that contemporaneous hunter-gatherers repeatedly changed their hunting equipment in response to changing climate and environment, not just for functional reasons but mainly driven by socio-territorial considerations. Based on a Bayesian analysis of 122 critically selected radiocarbon dates a broad chronological correlation is demonstrated between rapid changes in the design and technology of stone projectiles and short but abrupt cooling events, occurring at 10.3, 9.3 and 8.2 ka cal BP. Combined with the rapid sea level rises and increased wildfires these climatic events probably impacted the lifeways of hunter-gatherers in such a way that they increasingly faced resource stress and competition, forcing them to invest in the symbolic defense of their social territories. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them. [ABSTRACT FROM AUTHOR]

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest’s location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF. [ABSTRACT FROM AUTHOR]

The dry subtropics are subject to a rapid expansion of crops and pastures over vast areas of natural woodlands and savannas. In this paper, we explored the effect of this transformation on vegetation productivity (magnitude, and seasonal and long-term variability) along aridity gradients which span from semiarid to subhumid conditions, considering exclusively those areas with summer rains (>66%). Vegetation productivity was characterized with the proxy metric “Enhanced Vegetation Index” (EVI) (2000 to 2012 period), on 6186 natural and cultivated sampling points on five continents, and combined with a global climatology database by means of additive models for quantile regressions. Globally and regionally, cultivation amplified the seasonal and inter-annual variability of EVI without affecting its magnitude. Natural and cultivated systems maintained a similar and continuous increase of EVI with increasing water availability, yet achieved through contrasting ways. In natural systems, the productivity peak and the growing season length displayed concurrent steady increases with water availability, while in cultivated systems the productivity peak increased from semiarid to dry-subhumid conditions, and stabilized thereafter giving place to an increase in the growing season length towards wetter conditions. Our results help to understand and predict the ecological impacts of deforestation on vegetation productivity, a key ecosystem process linked to a broad range of services. [ABSTRACT FROM AUTHOR]

Biodiversity loss and climate change are both globally significant issues that must be addressed through collaboration across countries and disciplines. With the December 2015 COP21 climate conference in Paris and the recent creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), it has become critical to evaluate the capacity for global research networks to develop at the interface between biodiversity and climate change. In the context of the European Union (EU) strategy to stand as a world leader in tackling global challenges, the European Commission has promoted ties between the EU and Latin America and the Caribbean (LAC) in science, technology and innovation. However, it is not clear how these significant interactions impact scientific cooperation at the interface of biodiversity and climate change. We looked at research collaborations between two major regions—the European Research Area (ERA) and LAC—that addressed both biodiversity and climate change. We analysed the temporal evolution of these collaborations, whether they were led by ERA or LAC teams, and which research domains they covered. We surveyed publications listed on the Web of Science that were authored by researchers from both the ERA and LAC and that were published between 2003 and 2013. We also run similar analyses on other topics and other continents to provide baseline comparisons. Our results revealed a steady increase in scientific co-authorships between ERA and LAC countries as a result of the increasingly complex web of relationships that has been weaved among scientists from the two regions. The ERA-LAC co-authorship increase for biodiversity and climate change was higher than those reported for other topics and for collaboration with other continents. We also found strong differences in international collaboration patterns within the LAC: co-publications were fewest from researchers in low- and lower-middle-income countries and most prevalent from researchers in emerging countries like Mexico and Brazil. Overall, interdisciplinary publications represented 25.8% of all publications at the interface of biodiversity and climate change in the ERA-LAC network. Further scientific collaborations should be promoted 1) to prevent less developed countries from being isolated from the global cooperation network, 2) to ensure that scientists from these countries are trained to lead visible and recognized biodiversity and climate change research, and 3) to develop common study models that better integrate multiple scientific disciplines and better support decision-making. [ABSTRACT FROM AUTHOR]

Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems. Deforestation is a complex process driven by multiple proximate and underlying factors and a range of scales. In this study we use a multivariate statistical analysis to provide contextual explanation for deforestation in the Usumacinta River Basin based on partial pattern matching. Our approach avoided testing trivial null hypotheses of lack of association and investigated the strength and form of the response to drivers. As not all factors involved in deforestation are easily mapped as GIS layers, analytical challenges arise due to lack of a one to one correspondence between mappable attributes and drivers. We avoided testing simple statistical hypotheses such as the detectability of a significant linear relationship between deforestation and proximity to roads or water. We developed a series of informative generalised additive models based on combinations of layers that corresponded to hypotheses regarding processes. The importance of the variables representing accessibility was emphasised by the analysis. We provide evidence that land tenure is a critical factor in shaping the decision to deforest and that direct beam insolation has an effect associated with fire frequency and intensity. The effect of winter insolation was found to have many applied implications for land management. The methodology was useful for interpreting the relative importance of sets of variables representing drivers of deforestation. It was an informative approach, thus allowing the construction of a comprehensive understanding of its causes. [ABSTRACT FROM AUTHOR]

Risk assessment regarding the distribution of malaria vectors and environmental variables underpinning their distribution under changing climates is crucial towards malaria control and eradication. On this basis, we used Maximum Entropy (MaxEnt) Model to estimate the potential future distribution of major transmitters of malaria in Nigeria—Anopheles gambiae sensu lato and its siblings: Anopheles gambiae sensu stricto, and Anopheles arabiensis under low and high emissions scenarios. In the model, we used mosquito occurrence data sampled from 1900 to 2010 alongside land use and terrain variables, and bioclimatic variables for baseline climate 1960–1990 and future climates of 2050s (2041–2060) and 2070s (2061–2080) that follow RCP2.6 and RCP8.5 scenarios. The Anopheles gambiae species are projected to experience large shift in potential range and population with increased distribution density, higher under high emissions scenario (RCP8.5) and 2070s than low emission scenario (RCP2.6) and 2050s. Anopheles gambiae sensu stricto and Anopheles arabiensis are projected to have highest invasion with 47–70% and 10–14% percentage increase, respectively in Sahel and Sudan savannas within northern states in 2041–2080 under RCP8.5. Highest prevalence is predicted for Humid forest and Derived savanna in southern and North Central states in 2041–2080; 91–96% and 97–99% for Anopheles gambiae sensu stricto, and 67–71% and 72–75% for Anopheles arabiensis under RCP2.6 and RCP8.5, respectively. The higher magnitude of change in species prevalence predicted for the later part of the 21st century under high emission scenario, driven mainly by increasing and fluctuating temperature, alongside longer seasonal tropical rainfall accompanied by drier phases and inherent influence of rapid land use change, may lead to more significant increase in malaria burden when compared with other periods and scenarios during the century; especially in Humid forest, Derived savanna, Sahel and Sudan savannas. [ABSTRACT FROM AUTHOR]

The adaptability of our species, as revealed by the geographic routes and palaeoenvironmental contexts of human dispersal beyond Africa, is a prominent topic in archaeology and palaeoanthropology. Northern and Central Asia have largely been neglected as it has been assumed that the deserts and mountain ranges of these regions acted as ‘barriers’, forcing human populations to arc north into temperate and arctic Siberia. Here, we test this proposition by constructing Least Cost Path models of human dispersal under glacial and interstadial conditions between prominent archaeological sites in Central and East Asia. Incorporating information from palaeoclimatic, palaeolake, and archaeological data, we demonstrate that regions such as the Gobi Desert and the Altai Mountain chains could have periodically acted as corridors and routes for human dispersals and framing biological interactions between hominin populations. Review of the archaeological datasets in these regions indicates the necessity of wide-scale archaeological survey and excavations in many poorly documented parts of Eurasia. We argue that such work is likely to highlight the ‘northern routes’ of human dispersal as variable, yet crucial, foci for understanding the extreme adaptive plasticity characteristic of the emergence of Homo sapiens as a global species, as well as the cultural and biological hybridization of the diverse hominin species present in Asia during the Late Pleistocene. [ABSTRACT FROM AUTHOR]

Global climate change alters the dynamic of natural ecosystems and directly affects species distributions, persistence and diversity. The impacts of climate change may lead to dramatic changes in biotic interactions, such as pollination and seed dispersal. Life history traits are extremely important to consider the vulnerability of a species to climate change, producing more robust models than those based primarily on species distributions. Here, we hypothesized that rising temperatures and aridity will reduce suitable habitats for the endemic flora of the Caatinga, the most diverse dry tropical forest on Earth. Specifically, species with specialized reproductive traits (e.g. vertebrate pollination, biotic dispersal, obligatory cross-pollination) should be more affected by climate change than those with generalist traits. We performed two ecological niche models (current and future) to simulate the effects of climate change on the distribution area of endemic species in relation to life-history traits. We used the MIROC-ESM and CCSM4 models for both intermediate (RCP4.5) and highest predicted (RCP8.5) GHG emission scenarios, with a resolution of 30' (~1 km2). Habitat with high occurrence probability (>80%) of endemic species will be reduced (up to ~10% for trees, ~13% for non-arboreous, 10–28% for species with any pollination/reproductive system), with the greatest reductions for species with specialized reproductive traits. In addition, the likely concentration of endemic plants in the extreme northeastern portion of the Caatinga, in more mesic areas, coincides with the currently most human-modified areas of the ecosystem, which combined with climate change will further contract suitable habitats of endemic species. In conclusion, plant species endemic to the Caatinga are highly vulnerable to even conservative scenarios of future climate change and may lose much of their climatic envelopes. New protected areas should be located in the northeastern portion of the Caatinga, which hosts a more favorable climate, but is currently exposed to escalating agricultural intensification. [ABSTRACT FROM AUTHOR]

Climate change in recent decades has been identified as a significant threat to natural environments and human wellbeing. This is because some of the contemporary changes to climate are abrupt and result in persistent changes in the state of natural systems; so called regime shifts (RS). This study aimed to detect and analyse the timing and strength of RS in Estonian climate at the half-century scale (1966−2013). We demonstrate that the extensive winter warming of the Northern Hemisphere in the late 1980s was represented in atmospheric, terrestrial, freshwater and marine systems to an extent not observed before or after the event within the studied time series. In 1989, abiotic variables displayed statistically significant regime shifts in atmospheric, river and marine systems, but not in lake and bog systems. This was followed by regime shifts in the biotic time series of bogs and marine ecosystems in 1990. However, many biotic time series lacked regime shifts, or the shifts were uncoupled from large-scale atmospheric circulation. We suggest that the latter is possibly due to complex and temporally variable interactions between abiotic and biotic elements with ecosystem properties buffering biotic responses to climate change signals, as well as being affected by concurrent anthropogenic impacts on natural environments. [ABSTRACT FROM AUTHOR]

Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future. [ABSTRACT FROM AUTHOR]

South American coralsnakes are characterized by inconspicuous and poorly known species, which are potentially very sensitive to climate change. Here, we assess the impact of future climate change on the distributions of the Micrurus lemniscatus species complex after addressing the Wallacean shortfalls and refining the knowledge about their current geographic distributions. We also evaluate the efficiency of the current reserve network to protect the species in the present and future. We applied ecological niche model tools through a carefully examined set of occurrence records to generate potential present distributions and to project these distributions into future scenarios of climate change. Specific thresholds based on occurrence records along with expert opinions were used to delineate the geographic distribution of each species. A hierarchical ANOVA was applied to evaluate the uncertainties in species distributions across niche modeling methods and climate models and nested into the time factor (present and future). Multiple regression models were used to infer the relative importance of the climatic variables to determine the species’ suitability. A gap analysis was performed to address the representativeness of species distributions into protected areas. Predicted geographic distributions were compatible with the known distributions and the expert opinions, except for M. l. carvalhoi. New areas for field research were identified. Variation in precipitation was the most important factor defining the habitat suitability for all species, except for M. diutius. All taxa (except M. l. lemniscatus) will shrink their distributions in the future; less than 50% of the present suitable areas are protected in reserve networks, and less than 40% of these areas will be held in reserves in the future. We found strong evidence that coralsnakes may be highly sensitive to the ongoing changes and must be protected. [ABSTRACT FROM AUTHOR]

In order to ensure the provision of goods and services from forests, many governments have promoted less-traditional conservation initiatives such as programs of payments for ecosystem services called, more broadly, direct payments for conservation. The Socio Bosque Program (SBP) is a governmental program in Ecuador that directly provides economic incentives to rural families and local and indigenous communities who have voluntarily agreed to comply with some conservation activities. An impact evaluation method (matching) was used to assess the impact of the SBP between 2008 and 2014. This study revealed that on average, the SBP reduced deforestation by 1.5% in those forests that received the SBP’s direct payment. These forests would have been deforested if the SBP had not been implemented. Assessment of the impact of the SBP on individual and collective contracts, using the matching method, revealed that 3.4% and roughly 1% of the forest would have been deforested in the absence of the program, respectively. In other words, the protected area in the collective SBP was 1,247,500 ha and, if the SBP had not been implemented, an area of 11,227 ha would have been lost between 2008 and 2014. The 165,700 ha protected by the individual SBP, it was estimated that 5,733 ha were not deforested due to the implementation of the conservation program. Conventional estimates of the impact of the SBP tend to overestimate avoided deforestation because they do not control for observable covariates that correlate with or affect both SBP participation and deforestation. The conclusions are robust, even given potential hidden biases. The present study demonstrated that the SBP serves to mitigate the effects of climate change, especially with those contracts that are intended for individual owners. [ABSTRACT FROM AUTHOR]

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively. [ABSTRACT FROM AUTHOR]

Reduced climatic suitability due to climate change in cocoa growing regions of Ghana is expected in the coming decades. This threatens farmers’ livelihood and the cocoa sector. Climate change adaptation requires an improved understanding of existing cocoa production systems and farmers’ coping strategies. This study characterized current cocoa production, income diversification and shade tree management along a climate gradient within the cocoa belt of Ghana. The objectives were to 1) compare existing production and income diversification between dry, mid and wet climatic regions, and 2) identify shade trees in cocoa agroforestry systems and their distribution along the climatic gradient. Our results showed that current mean cocoa yield level of 288kg ha-1yr-1 in the dry region was significantly lower than in the mid and wet regions with mean yields of 712 and 849 kg ha-1 yr-1, respectively. In the dry region, farmers diversified their income sources with non-cocoa crops and off-farm activities while farmers at the mid and wet regions mainly depended on cocoa (over 80% of annual income). Two shade systems classified as medium and low shade cocoa agroforestry systems were identified across the studied regions. The medium shade system was more abundant in the dry region and associated to adaptation to marginal climatic conditions. The low shade system showed significantly higher yield in the wet region but no difference was observed between the mid and dry regions. This study highlights the need for optimum shade level recommendation to be climatic region specific. [ABSTRACT FROM AUTHOR]

We summarize thermal-biology data of 69 species of Amazonian lizards, including mode of thermoregulation and field-active body temperatures (Tb). We also provide new data on preferred temperatures (Tpref), voluntary and thermal-tolerance ranges, and thermal-performance curves (TPC’s) for 27 species from nine sites in the Brazilian Amazonia. We tested for phylogenetic signal and pairwise correlations among thermal traits. We found that species generally categorized as thermoregulators have the highest mean values for all thermal traits, and broader ranges for Tb, critical thermal maximum (CTmax) and optimal (Topt) temperatures. Species generally categorized as thermoconformers have large ranges for Tpref, critical thermal minimum (CTmin), and minimum voluntary (VTmin) temperatures for performance. Despite these differences, our results show that all thermal characteristics overlap between both groups and suggest that Amazonian lizards do not fit into discrete thermoregulatory categories. The traits are all correlated, with the exceptions of (1) Topt, which does not correlate with CTmax, and (2) CTmin, and correlates only with Topt. Weak phylogenetic signals for Tb, Tpref and VTmin indicate that these characters may be shaped by local environmental conditions and influenced by phylogeny. We found that open-habitat species perform well under present environmental conditions, without experiencing detectable thermal stress from high environmental temperatures induced in lab experiments. For forest-dwelling lizards, we expect warming trends in Amazonia to induce thermal stress, as temperatures surpass the thermal tolerances for these species. [ABSTRACT FROM AUTHOR]

Vulnerability, understood as the propensity to be adversely affected, has attained importance in the context of climate change by helping to understand what makes populations and territories predisposed to its impacts. Conditions of vulnerability may vary depending on the characteristics of each territory studied—social, environmental, infrastructural, public policies, among others. Thus, the present study aimed to evaluate what makes the municipalities of the state of Amazonas, Brazil, vulnerable to climate change in the context of the largest tropical forest in the world, and which regions of the State are the most susceptible. A Municipal Vulnerability Index was developed, which was used to associate current socio-environmental characteristics of municipalities with climate change scenarios in order to identify those that may be most affected by climate change. The results showed that poor adaptive capacity and poverty had the most influence on current vulnerability of the municipalities of Amazonas with the most vulnerable areas being the southern, northern, and eastern regions of the state. When current vulnerability was related to future climate change projections, the most vulnerable areas were the northern, northeastern, extreme southern, and southwestern regions. From a socio-environmental and climatic point of view, these regions should be a priority for public policy efforts to reduce their vulnerability and prepare them to cope with the adverse aspects of climate change. [ABSTRACT FROM AUTHOR]

Seasonally dry forests in the neotropics are heavily threatened by a combination of human disturbances and climate change; however, the severity of these threats is seldom contrasted. This study aims to quantify and compare the effects of deforestation and climate change on the natural spatial ranges of 17 characteristic tree species of southern Ecuador dry deciduous forests, which are heavily fragmented and support high levels of endemism as part of the Tumbesian ecoregion. We used 660 plant records to generate species distribution models and land-cover data to project species ranges for two time frames: a simulated deforestation scenario from 2008 to 2014 with native forest to anthropogenic land-use conversion, and an extreme climate change scenario (CCSM4.0, RCP 8.5) for 2050, which assumed zero change from human activities. To assess both potential threats, we compared the estimated annual rates of species loss (i.e., range shifts) affecting each species. Deforestation loss for all species averaged approximately 71 km2/year, while potential climate-attributed loss was almost 21 km2/year. Moreover, annual area loss rates due to deforestation were significantly higher than those attributed to climate-change (P < 0.01). However, projections into the future scenario show evidence of diverging displacement patterns, indicating the potential formation of novel ecosystems, which is consistent with other species assemblage predictions as result of climate change. Furthermore, we provide recommendations for management and conservation, prioritizing the most threatened species such as Albizia multiflora, Ceiba trichistandra, and Cochlospermum vitifolium. [ABSTRACT FROM AUTHOR]

Protected areas are arguably the most important instrument of biodiversity conservation. To keep them fit under climate change, their management needs to be adapted to address related direct and indirect changes. In our study we focus on the adaptation of conservation management planning, evaluating management plans of 60 protected areas throughout Germany with regard to their climate change-robustness. First, climate change-robust conservation management was defined using 11 principles and 44 criteria, which followed an approach similar to sustainability standards. We then evaluated the performance of individual management plans concerning the climate change-robustness framework. We found that climate change-robustness of protected areas hardly exceeded 50 percent of the potential performance, with most plans ranking in the lower quarter. Most Natura 2000 protected areas, established under conservation legislation of the European Union, belong to the sites with especially poor performance, with lower values in smaller areas. In general, the individual principles showed very different rates of accordance with our principles, but similarly low intensity. Principles with generally higher performance values included holistic knowledge management, public accountability and acceptance as well as systemic and strategic coherence. Deficiencies were connected to dealing with the future and uncertainty. Lastly, we recommended the presented principles and criteria as essential guideposts that can be used as a checklist for working towards more climate change-robust planning. [ABSTRACT FROM AUTHOR]

Gross primary production (GPP) is the Earth’s largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales. [ABSTRACT FROM AUTHOR]

Habitat loss and fragmentation are among the biggest threats to tropical biodiversity and associated ecosystem services. We examined forest dynamics in a mid-elevation 365-ha fragment in southern Costa Rica. The fragment was isolated in the mid-1970s and belongs to the Las Cruces Biological Station. A 2.25-ha permanent plot was established in the center of the old-growth forest (>400 m to nearest edge boundary) and all plants >5 cm DBH were censused, mapped, and identified to species in two surveys taken ~5–6 years apart (>3,000 stems/survey). Although the reserve maintains high species richness (>200 spp.), with many rare species represented by only one individual, we document a strong shift in composition with a two-fold increase in the number of soft-wooded pioneer individuals. The dominant late-successional understory tree species, Chrysochlamys glauca (Clusiaceae), and most species in the Lauraceae, declined dramatically. Turnover was high: 22.9% of stems in the first survey were lost, and 27.8% of stems in the second survey represented new recruits. Mean tree diameter decreased significantly and there was a 10% decrease in overall biomass. Such alteration has been documented previously but only in smaller fragments or within ~100 m of an edge boundary. Further penetration into this fragment was perhaps driven by a progressive invasion of disturbance-adapted species into the fragment’s core over time; the loss of once-dominant late successional species could be a contributing factor. The pattern found is of particular concern given that such fragments represent a substantial portion of today’s remaining tropical habitat; further studies in similar-sized fragments that have been isolated for similar prolonged periods are called for. [ABSTRACT FROM AUTHOR]

Hantavirus Cardiopulmonary Syndrome (HCPS) is a disease caused by Hantavirus, which is highly virulent for humans. High temperatures and conversion of native vegetation to agriculture, particularly sugarcane cultivation can alter abundance of rodent generalist species that serve as the principal reservoir host for HCPS, but our understanding of the compound effects of land use and climate on HCPS incidence remains limited, particularly in tropical regions. Here we rely on a Bayesian model to fill this research gap and to predict the effects of sugarcane expansion and expected changes in temperature on Hantavirus infection risk in the state of São Paulo, Brazil. The sugarcane expansion scenario was based on historical data between 2000 and 2010 combined with an agro-environment zoning guideline for the sugar and ethanol industry. Future evolution of temperature anomalies was derived using 32 general circulation models from scenarios RCP4.5 and RCP8.5 (Representative greenhouse gases Concentration Pathways adopted by IPCC). Currently, the state of São Paulo has an average Hantavirus risk of 1.3%, with 6% of the 645 municipalities of the state being classified as high risk (HCPS risk ≥ 5%). Our results indicate that sugarcane expansion alone will increase average HCPS risk to 1.5%, placing 20% more people at HCPS risk. Temperature anomalies alone increase HCPS risk even more (1.6% for RCP4.5 and 1.7%, for RCP8.5), and place 31% and 34% more people at risk. Combined sugarcane and temperature increases led to the same predictions as scenarios that only included temperature. Our results demonstrate that climate change effects are likely to be more severe than those from sugarcane expansion. Forecasting disease is critical for the timely and efficient planning of operational control programs that can address the expected effects of sugarcane expansion and climate change on HCPS infection risk. The predicted spatial location of HCPS infection risks obtained here can be used to prioritize management actions and develop educational campaigns. [ABSTRACT FROM AUTHOR]

Water-use efficiency (WUE), defined as the ratio of net primary productivity (NPP) to evapotranspiration (ET), is an important indicator to represent the trade-off pattern between vegetation productivity and water consumption. Its dynamics under climate change are important to ecohydrology and ecosystem management, especially in the drylands. In this study, we modified and used a late version of Boreal Ecosystem Productivity Simulator (BEPS), to quantify the WUE in the typical dryland ecosystems, Temperate Eurasian Steppe (TES). The Aridity Index (AI) was used to specify the terrestrial water availability condition. The regional results showed that during the period of 1999–2008, the WUE has a clear decreasing trend in the spatial distribution from arid to humid areas. The highest annual average WUE was in dry and semi-humid sub-region (DSH) with 0.88 gC mm-1 and the lowest was in arid sub-region (AR) with 0.22 gC mm-1. A two-stage pattern of WUE was found in TES. That is, WUE would enhance with lower aridity stress, but decline under the humid environment. Over 65% of the region exhibited increasing WUE. This enhancement, however, could not indicate that the grasslands were getting better because the NPP even slightly decreased. It was mainly attributed to the reduction of ET over 70% of the region, which is closely related to the rainfall decrease. The results also suggested a similar negative spatial correlation between the WUE and the mean annual precipitation (MAP) at the driest and the most humid ends. This regional pattern reflected the different roles of water in regulating the terrestrial ecosystems under different aridity levels. This study could facilitate the understanding of the interactions between terrestrial carbon and water cycles, and thus contribute to a sustainable management of nature resources in the dryland ecosystems. [ABSTRACT FROM AUTHOR]

Understanding the processes that influence species diversity is still a challenge in ecological studies. However, there are two main theories to discuss this topic, the niche theory and the neutral theory. Our objective was to understand the importance of environmental and spatial processes in structuring bird communities within the hydrological seasons in dry forest areas in northeastern Brazil. The study was conducted in two National Parks, the Serra da Capivara and Serra das Confusões National Parks, where 36 areas were sampled in different seasons (dry, dry/rainy transition, rainy, rainy/dry transition), in 2012 and 2013. We found with our results that bird species richness is higher in the rainy season and lower during the dry season, indicating a strong influence of seasonality, a pattern also found for environmental heterogeneity. Richness was explained by local environmental factors, while species composition was explained by environmental and spatial factors. The environmental factors were more important in explaining variations in composition. Climate change predictions have currently pointed out frequent drought events and a rise in global temperature by 2050, which would lead to changes in species behavior and to increasing desertification in some regions, including the Caatinga. In addition, the high deforestation rates and the low level of representativeness of the Caatinga in the conservation units negatively affects bird communities. This scenario has demonstrated how climatic factors affect individuals, and, therefore, should be the starting point for conservation initiatives to be developed in xeric environments. [ABSTRACT FROM AUTHOR]

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present. [ABSTRACT FROM AUTHOR]

Aim: To test whether novel and previously hypothesized biogeogaphic barriers in the Australian Tropics represent significant disjunction points or hard barriers, or both, to the distribution of plants. Location: Australian tropics: Australian Monsoon Tropics and Australian Wet Tropics. Methods: The presence or absence of 6,861 plant species was scored across 13 putative biogeographic barriers in the Australian Tropics, including two that have not previously been recognised. Randomizations of these data were used to test whether more species showed disjunctions (gaps in distribution) or likely barriers (range limits) at these points than expected by chance. Results: Two novel disjunctions in the Australian Tropics flora are identified in addition to eleven putative barriers previously recognized for animals. Of these, eleven disjunction points (all within the Australian Monsoon Tropics) were found to correspond to range-ending barriers to a significant number of species, while neither of the two disjunctions found within the Australian Wet Tropics limited a significant number of species’ ranges. Main conclusions: Biogeographic barriers present significant distributional limits to native plant species in the Australian Monsoon Tropics but not in the Australian Wet Tropics. [ABSTRACT FROM AUTHOR]

West Africa has been described as a hotspot of climate change. The reliance on rain-fed agriculture by over 65% of the population means that vulnerability to climatic hazards such as droughts, rainstorms and floods will continue. Yet, the vulnerability and risk levels faced by different rural social-ecological systems (SES) affected by multiple hazards are poorly understood. To fill this gap, this study quantifies risk and vulnerability of rural communities to drought and floods. Risk is assessed using an indicator-based approach. A stepwise methodology is followed that combines participatory approaches with statistical, remote sensing and Geographic Information System techniques to develop community level vulnerability indices in three watersheds (Dano, Burkina Faso; Dassari, Benin; Vea, Ghana). The results show varying levels of risk profiles across the three watersheds. Statistically significant high levels of mean risk in the Dano area of Burkina Faso are found whilst communities in the Dassari area of Benin show low mean risk. The high risk in the Dano area results from, among other factors, underlying high exposure to droughts and rainstorms, longer dry season duration, low caloric intake per capita, and poor local institutions. The study introduces the concept of community impact score (CIS) to validate the indicator-based risk and vulnerability modelling. The CIS measures the cumulative impact of the occurrence of multiple hazards over five years. 65.3% of the variance in observed impact of hazards/CIS was explained by the risk models and communities with high simulated disaster risk generally follow areas with high observed disaster impacts. Results from this study will help disaster managers to better understand disaster risk and develop appropriate, inclusive and well integrated mitigation and adaptation plans at the local level. It fulfills the increasing need to balance global/regional assessments with community level assessments where major decisions against risk are actually taken and implemented. [ABSTRACT FROM AUTHOR]

Here we conduct research to understand the evolutionary history of a shrubby species known as Agarito (Berberis trifoliolata), an endemic species to the Chihuahuan Desert. We identify genetic signatures based on plastid DNA and AFLP markers and perform niche modelling and spatial connectivity analyses as well as niche modelling based on records in packrats to elucidate whether orogenic events such as mountain range uplift in the Miocene or the contraction/expansion dynamics of vegetation in response to climate oscillations in the Pliocene/Pleistocene had an effect on evolutionary processes in Agarito. Our results of current niche modelling and palaeomodelling showed that the area currently occupied by Berberis trifoliolata is substantially larger than it was during the Last Interglacial period and the Last Glacial Maximum. Agarito was probably confined to small areas in the Northeastern and gradually expanded its distribution just after the Last Glacial Maximum when the weather in the Chihuahuan Desert and adjacent regions became progressively warmer and drier. The most contracted range was predicted for the Interglacial period. Populations remained in stable areas during the Last Glacial Maximum and expanded at the beginning of the Holocene. Most genetic variation occured in populations from the Sierra Madre Oriental. Two groups of haplotypes were identified: the Mexican Plateau populations and certain Northeastern populations. Haplogroups were spatially connected during the Last Glacial Maximum and separated during interglacial periods. The most important prediction of packrat middens palaeomodelling lies in the Mexican Plateau, a finding congruent with current and past niche modelling predictions for agarito and genetic results. Our results corroborate that these climate changes in the Pliocene/Pleistocene affected the evolutionary history of agarito. The journey of agarito in the Chihuahuan Desert has been dynamic, expanding and contracting its distribution range and currently occupying the largest area in its history. [ABSTRACT FROM AUTHOR]

Climate change is recognized as an important threat to global biodiversity because it increases the risk of extinction of many species on the planet. Mexico is a megadiverse country and native tree species such as red cedar (Cedrela odorata) can be used to maintain forests while helping mitigate climate change, because it is considered a fast growing pioneer species with great economic potential in the forestry industry. In order to assess possible shifts in areas suitable for C. odorata plantations in Mexico with ecological niche models, we used the MaxLike algorithm, climate variables, the geo-referenced records of this species, three general circulation models and three scenarios of future emissions. Results show a current potential distribution of 573,079 km2 with an average probability of occurrence of 0.93 (± 0.13). The potential distribution area could increase up to 650,356 km2 by 2060 according to the general circulation model HADCM3 B2, with an average probability of occurrence of 0.86 (± 0.14). Finally, we delimited an area of 35,377 km2 that has a high potential for the establishment of C. odorata plantations, by selecting those sites with optimal conditions for its growth that are outside protected areas and are currently devoid of trees. C. odorata has a significant potential to help in the mitigation of the effects of climate change. Using MaxLike we identified extense areas in Mexico suitable to increase carbon sequestration through plantations of this highly valued native tree species. [ABSTRACT FROM AUTHOR]

Paraná, Yungas and Chaco Serrano ecoregions are among the most species-rich terrestrial habitats at higher latitude. However, the information for tiger moths, one of the most speciose groups of moths, is unknown in these ecoregions. In this study, we assess their species richness and composition in all three of these ecoregions. Also we investigated whether the species composition of tiger moths is influenced by climatic factors and altitude. Tiger moth species were obtained with samples from 71 sites using standardized protocols (21 sites were in Yungas, 19 in Paraná and 31 in Chaco Serrano). Rarefaction-extrapolation curves, non-parametric estimators for incidence and sample coverage indices were performed to assess species richness in the ecoregions studied. Non metric multidimensional scaling and adonis tests were performed to compare the species composition of tiger moths among ecoregions. Permutest analysis and Pearson correlation were used to evaluate the relationship among species composition and annual mean temperature, annual temperature range, annual precipitation, precipitation seasonality and altitude. Among ecoregions Paraná was the richest with 125 species, followed by Yungas with 63 species and Chaco Serrano with 24 species. Species composition differed among these ecoregions, although Yungas and Chaco Serrano were more similar than Paraná. Species composition was significantly influenced by climatic factors and altitude. This study showed that species richness and species composition of tiger moths differed among the three ecoregions assessed. Furthermore, not only climatic factors and altitude influence the species composition of tiger moths among ecoregions, but also climatic seasonality at higher latitude in Neotropical South America becomes an important factor. [ABSTRACT FROM AUTHOR]

Wildfires are becoming increasingly dominant in tropical landscapes due to reinforcing feedbacks between land cover change and more severe dry conditions. This study focused on the Bolivian Chiquitania, a region located at the southern edge of Amazonia. The extensive, unique and well-conserved tropical dry forest in this region is susceptible to wildfires due to a marked seasonality. We used a novel approach to assess fire risk at the regional level driven by different development trajectories interacting with changing climatic conditions. Possible future risk scenarios were simulated using maximum entropy modelling with presence-only data, combining land cover, anthropogenic and climatic variables. We found that important determinants of fire risk in the region are distance to roads, recent deforestation and density of human settlements. Severely dry conditions alone increased the area of high fire risk by 69%, affecting all categories of land use and land cover. Interactions between extreme dry conditions and rapid frontier expansion further increased fire risk, resulting in potential biomass loss of 2.44±0.8 Tg in high risk area, about 1.8 times higher than the estimates for the 2010 drought. These interactions showed particularly high fire risk in land used for ‘extensive cattle ranching’, ‘agro-silvopastoral use’ and ‘intensive cattle ranching and agriculture’. These findings have serious implications for subsistence activities and the economy in the Chiquitania, which greatly depend on the forestry, agriculture and livestock sectors. Results are particularly concerning if considering the current development policies promoting frontier expansion. Departmental protected areas inhibited wildfires when strategically established in areas of high risk, even under drought conditions. However, further research is needed to assess their effectiveness accounting for more specific contextual factors. This novel and simple modelling approach can inform fire and land management decisions in the Chiquitania and other tropical forest landscapes to better anticipate and manage large wildfires in the future. [ABSTRACT FROM AUTHOR]

There is a pressing need to assess resilience of coastal ecosystems against sea level rise. To develop appropriate response strategies against future climate disturbances, it is important to estimate the magnitude of disturbances that these ecosystems can absorb and to better understand their underlying processes. Hammocks (petenes) coastal ecosystems are highly vulnerable to sea level rise linked to climate change; their vulnerability is mainly due to its close relation with the sea through underground drainage in predominantly karstic soils. Hammocks are biologically important because of their high diversity and restricted distribution. This study proposes a strategy to assess resilience of this coastal ecosystem when high-precision data are scarce. Approaches and methods used to derive ecological resilience maps of hammocks are described and assessed. Resilience models were built by incorporating and weighting appropriate indicators of persistence to assess hammocks resilience against flooding due to climate change at “Los Petenes Biosphere Reserve”, in the Yucatán Peninsula, Mexico. According to the analysis, 25% of the study area is highly resilient (hot spots), whereas 51% has low resilience (cold spots). The most significant hot spot clusters of resilience were located in areas distant to the coastal zone, with indirect tidal influence, and consisted mostly of hammocks surrounded by basin mangrove and floodplain forest. This study revealed that multi-criteria analysis and the use of GIS for qualitative, semi-quantitative and statistical spatial analyses constitute a powerful tool to develop ecological resilience maps of coastal ecosystems that are highly vulnerable to sea level rise, even when high-precision data are not available. This method can be applied in other sites to help develop resilience analyses and decision-making processes for management and conservation of coastal areas worldwide. [ABSTRACT FROM AUTHOR]

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. [ABSTRACT FROM AUTHOR]

Studies based on contemporary plant occurrences and pollen fossil records have proposed that the current disjunct distribution of seasonally dry tropical forests (SDTFs) across South America is the result of fragmentation of a formerly widespread and continuously distributed dry forest during the arid climatic conditions associated with the Last Glacial Maximum (LGM), which is known as the modern-day dry forest refugia hypothesis. We studied the demographic history of Tabebuia rosealba (Bignoniaceae) to understand the disjunct geographic distribution of South American SDTFs based on statistical phylogeography and ecological niche modeling (ENM). We specifically tested the dry forest refugia hypothesis; i.e., if the multiple and isolated patches of SDTFs are current climatic relicts of a widespread and continuously distributed dry forest during the LGM. We sampled 235 individuals across 18 populations in Central Brazil and analyzed the polymorphisms at chloroplast (trnS-trnG, psbA-trnH and ycf6-trnC intergenic spacers) and nuclear (ITS nrDNA) genomes. We performed coalescence simulations of alternative hypotheses under demographic expectations from two a priori biogeographic hypotheses (1. the Pleistocene Arc hypothesis and, 2. a range shift to Amazon Basin) and other two demographic expectances predicted by ENMs (3. expansion throughout the Neotropical South America, including Amazon Basin, and 4. retraction during the LGM). Phylogenetic analyses based on median-joining network showed haplotype sharing among populations with evidence of incomplete lineage sorting. Coalescent analyses showed smaller effective population sizes for T. roseoalba during the LGM compared to the present-day. Simulations and ENM also showed that its current spatial pattern of genetic diversity is most likely due to a scenario of range retraction during the LGM instead of the fragmentation from a once extensive and largely contiguous SDTF across South America, not supporting the South American dry forest refugia hypothesis. [ABSTRACT FROM AUTHOR]

The McMurdo Dry Valleys constitute the largest ice free area of Antarctica. The area is a polar desert with an annual precipitation of ∼ 3 cm water equivalent, but contains several lakes fed by glacial melt water streams that flow from four to twelve weeks of the year. Over the past ∼20 years, data have been collected on the lakes located in Taylor Valley, Antarctica as part of the McMurdo Dry Valley Long-Term Ecological Research program (MCM-LTER). This work aims to understand the impact of climate variations on the biological processes in all the ecosystem types within Taylor Valley, including the lakes. These lakes are stratified, closed-basin systems and are perennially covered with ice. Each lake contains a variety of planktonic and benthic algae that require nutrients for photosynthesis and growth. The work presented here focuses on Lake Fryxell, one of the three main lakes of Taylor Valley; it is fed by thirteen melt-water streams. We use a functional regression approach to link the physical, chemical, and biological processes within the stream-lake system to evaluate the input of water and nutrients on the biological processes in the lakes. The technique has been shown previously to provide important insights into these Antarctic lacustrine systems where data acquisition is not temporally coherent. We use data on primary production (PPR) and chlorophyll-A (CHL)from Lake Fryxell as well as discharge observations from two streams flowing into the lake. Our findings show an association between both PPR, CHL and stream input. [ABSTRACT FROM AUTHOR]

The frequency, magnitude, and size of forest disturbances are increasing globally. Much recent research has focused on how the occurrence of one disturbance may affect susceptibility to subsequent disturbances. While much has been learned about such linked disturbances, the strength of the interactions is likely to be contingent on the severity of disturbances as well as climatic conditions, both of which can affect disturbance intensity and tree resistance to disturbances. Subalpine forests in western Colorado were affected by extensive and severe wildfires in the late 19th century and an extensive and severe outbreak of spruce beetle (Dendroctonus rufipennis) in the 1940s. Previous research found that most, but not all, of the stands that burned and established following the late 19th century fires were not susceptible to the 1940s outbreak as beetles preferentially attack larger trees and stands in advanced stages of development. However, previous research also left open the possibility that some stands that burned and established following the 19th century fires may have been attacked during the 1940s outbreak. Understanding how strongly stand structure, as shaped by disturbances of varying severity, affected susceptibility to past outbreaks is important to provide a baseline for assessing the degree to which recent climate change may be relaxing the preferences of beetles for larger trees and for stands in latter stages of structural development and thereby changing the nature of linked disturbances. Here, dendroecological methods were used to study disturbance history and tree age of stands in the White River National Forest in Western Colorado that were identified in historical documents or remotely-sensed images as having burned in the 19th century and having been attacked by spruce beetle in the 1940s. Dendroecological reconstructions indicate that in young post-fire stands only old remnant trees that survived the otherwise stand-replacing fires were killed in the 1940s outbreak. No young post-fire trees (< ca. 128 years) were susceptible to the 1940s outbreak, implying that under the relatively cool and wet conditions of the mid-20th century, susceptibility to and spatial patterns of spruce beetle outbreak were most likely controlled by variations in severity of prior disturbance by fire. This study provides a baseline for comparing linked disturbances under the relatively warmer and drier conditions of recent (e.g. post-1990) outbreaks in order to assess how climate mitigates the degree to which pre-disturbance history and structure affect susceptibility to disturbances. [ABSTRACT FROM AUTHOR]

Based on two chloroplast DNA sequences, psbA-trnH and trnT-trnF, phylogeographical patterns of a desert shrub, Ephedra przewalskii, were examined across most of its geographic range in northwestern China. A total of sixteen haplotypes were detected. There was a common haplotype in each basin, that was haplotype A in Tarim Basin, haplotype G in Junggar Basin, and haplotype M in Qaidam Basin. Genetic variance mainly occurred among populations, geographic regions, and eleven geographic groups subdivided by SAMOVA analysis. E. przewalskii likely had a smaller and more fragmented geographic range during the Last Glacial Maximum, which was determined based on ecological niche modelling. Three groups of E. przewalskii populations were detected to have experience range expansion, and this was based on significant values of Fu’s FS, Tajima’s D, and unimodel mismatch distributions. The cold and dry climate during the glacial period of the Quaternary is postulated to have been a driver for significant genetic isolation and divergence among populations or groups in E. przewalskii, whereas the warmer and wetter climate during the interglacial period is speculated to have provided favourable conditions for range expansion of the species. [ABSTRACT FROM AUTHOR]

Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians. [ABSTRACT FROM AUTHOR]

Do forest owners’ levels of education or value profiles explain their responses to climate change? The cultural cognition thesis (CCT) has cast serious doubt on the familiar and often criticized "knowledge deficit" model, which says that laypeople are less concerned about climate change because they lack scientific knowledge. Advocates of CCT maintain that citizens with the highest degrees of scientific literacy and numeracy are not the most concerned about climate change. Rather, this is the group in which cultural polarization is greatest, and thus individuals with more limited scientific literacy and numeracy are more concerned about climate change under certain circumstances than those with higher scientific literacy and numeracy. The CCT predicts that cultural and other values will trump the positive effects of education on some forest owners' attitudes to climate change. Here, using survey data collected in 2010 from 766 private forest owners in Sweden and Germany, we provide the first evidence that perceptions of climate change risk are uncorrelated with, or sometimes positively correlated with, education level and can be explained without reference to cultural or other values. We conclude that the recent claim that advanced scientific literacy and numeracy polarizes perceptions of climate change risk is unsupported by the forest owner data. In neither of the two countries was university education found to reduce the perception of risk from climate change. Indeed in most cases university education increased the perception of risk. Even more importantly, the effect of university education was not dependent on the individuals' value profile. [ABSTRACT FROM AUTHOR]

Provenance studies are an increasingly important analog for understanding how trees adapted to particular climatic conditions might respond to climate change. Dendrochronological analysis can illuminate differences among trees from different seed sources in terms of absolute annual growth and sensitivity to external growth factors. We analyzed annual radial growth of 567 36-year-old pitch pine (Pinus rigida Mill.) trees from 27 seed sources to evaluate their performance in a New Jersey Pine Barrens provenance experiment. Unexpectedly, missing rings were prevalent in most trees, and some years—1992, 1999, and 2006—had a particularly high frequency of missing rings across the plantation. Trees from local seed sources (<55 km away from the plantation) had a significantly smaller percentage of missing rings from 1980–2009 (mean: 5.0%), relative to northernmost and southernmost sources (mean: 9.3% and 7.9%, respectively). Some years with a high frequency of missing rings coincide with outbreaks of defoliating insects or dry growing season conditions. The propensity for missing rings synchronized annual variations in growth across all trees and might have complicated the detection of potential differences in interannual variability among seed sources. Average ring width was significantly larger in seed sources from both the southernmost and warmest origins compared to the northernmost and coldest seed sources in most years. Local seed sources had the highest average radial growth. Adaptation to local environmental conditions and disturbances might have influenced the higher growth rate found in local seed sources. These findings underscore the need to understand the integrative impact of multiple environmental drivers, such as disturbance agents and climate change, on tree growth, forest dynamics, and the carbon cycle. [ABSTRACT FROM AUTHOR]

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state’s fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change. [ABSTRACT FROM AUTHOR]

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

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. [ABSTRACT FROM AUTHOR]