Relative importance of long‐term changes in climate and land‐use on the phenology and abundance of legume crop specialist and generalist aphids

Abstract Insect populations are prone to respond to global changes through shifts in phenology, distribution and abundance. However, global changes cover several factors such as climate and land-use, the relative importance of these being largely unknown. Here, we aim at disentangling the effects of climate, land-use, and geographical drivers on aphid abundance and phenology in France, at a regional scale and over the last 40 years. We used aerial data obtained from suction traps between 1978 and 2015 on five aphid species varying in their degree of specialization to legumes, along with climate, legume crop area and geographical data. Effects of environmental and geographical variables on aphid annual abundance and spring migration dates were analyzed using generalized linear mixed models. We found that within the last four decades, aphids have advanced their spring migration by a month, mostly due to the increase in temperature early in the year, and their abundance decreased by half on average, presumably in response to a combination of factors. The influence of legume crop area decreased with the degree of specialization of the aphid species to such crops. The effect of geographical variation was high even when controlling for environmental variables, suggesting that many other spatially structured processes act on aphid population characteristics. Multifactorial analyses helped to partition the effects of different global change drivers. Climate and land-use changes have strong effects on aphid populations, with important implications for future agriculture. Additionally, trait-based response variation could have major consequences at the community scale.     

Carbon cycle responses of semi‐arid ecosystems to positive asymmetry in rainfall

Recent evidence shows that warm semi‐arid ecosystems are playing a disproportionate role in the interannual variability and greening trend of the global carbon cycle given their mean lower productivity when compared with other biomes (Ahlström et al. 2015 Science, 348, 895). Using multiple observations (land‐atmosphere fluxes, biomass, streamflow and remotely sensed vegetation cover) and two state‐of‐the‐art biospheric models, we show that climate variability and extremes lead to positive or negative responses in the biosphere, depending on vegetation type. We find Australia to be a global hot spot for variability, with semi‐arid ecosystems in that country exhibiting increased carbon uptake due to both asymmetry in the interannual distribution of rainfall (extrinsic forcing), and asymmetry in the response of gross primary production (GPP) to rainfall change (intrinsic response). The latter is attributable to the pulse‐response behaviour of the drought‐adapted biota of these systems, a response that is estimated to be as much as half of that from the CO₂ fertilization effect during 1990–2013. Mesic ecosystems, lacking drought‐adapted species, did not show an intrinsic asymmetric response. Our findings suggest that a future more variable climate will induce large but contrasting ecosystem responses, differing among biomes globally, independent of changes in mean precipitation alone. The most significant changes are occurring in the extensive arid and semi‐arid regions, and we suggest that the reported increased carbon uptake in response to asymmetric responses might be contributing to the observed greening trends there.     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution

Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red‐eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated‐detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit improved only marginally when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red‐eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. The weak correlation between vital rates and temporal changes in covariates indicated that we have yet to identify the most relevant components of global change influencing the distributions of these species and, more importantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.     

Land-cover data improve bioclimatic models for anurans and turtles at a regional scale

Aim We investigated whether accounting for land cover could improve bioclimatic models for eight species of anurans and three species of turtles at a regional scale. We then tested whether accounting for spatial autocorrelation could significantly improve bioclimatic models after statistically controlling for the effects of land cover. Location Nova Scotia, eastern Canada. Methods Species distribution data were taken from a recent (1999–2003) herpetofaunal atlas. Generalized linear models were used to relate the presence or absence of each species to climate and land‐cover variables at a 10‐km resolution. We then accounted for spatial autocorrelation using an autocovariate or third‐order trend surface of the geographical coordinates of each grid square. Finally, variance partitioning was used to explore the independent and joint contributions of climate, land cover and spatial autocorrelation. Results The inclusion of land cover significantly increased the explanatory power of bioclimatic models for 10 of the 11 species. Furthermore, including land cover significantly increased predictive performance for eight of the 11 species. Accounting for spatial autocorrelation improved model fit for rare species but generally did not improve prediction success. Variance partitioning demonstrated that this lack of improvement was a result of the high correlation between climate and trend‐surface variables. Main conclusions The results of this study suggest that accounting for the effects of land cover can significantly improve the explanatory and predictive power of bioclimatic models for anurans and turtles at a regional scale. We argue that the integration of climate and land‐cover data is likely to produce more accurate spatial predictions of contemporary herpetofaunal diversity. However, the use of land‐cover simulations in climate‐induced range‐shift projections introduces additional uncertainty into the predictions of bioclimatic models. Further research is therefore needed to determine whether accounting for the effects of land cover in range‐shift projections is merited.     

How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes

We forced a global terrestrial carbon cycle model by climate fields of 14 ocean and atmosphere general circulation models (OAGCMs) to simulate the response of terrestrial carbon pools and fluxes to climate change over the next century. These models participated in the second phase of the Coupled Model Intercomparison Project (CMIP2), where a 1% per year increase of atmospheric CO₂ was prescribed. We obtain a reduction in net land uptake because of climate change ranging between 1.4 and 5.7 Gt C yr^?1 at the time of atmospheric CO₂ doubling. Such a reduction in terrestrial carbon sinks is largely dominated by the response of tropical ecosystems, where soil water stress occurs. The uncertainty in the simulated land carbon cycle response is the consequence of discrepancies in land temperature and precipitation changes simulated by the OAGCMs. We use a statistical approach to assess the coherence of the land carbon fluxes response to climate change. The biospheric carbon fluxes and pools changes have a coherent response in the tropics, in the Mediterranean region and in high latitudes of the Northern Hemisphere. This is because of a good coherence of soil water content change in the first two regions and of temperature change in the high latitudes of the Northern Hemisphere. Then we evaluate the carbon uptake uncertainties to the assumptions on plant productivity sensitivity to atmospheric CO₂ and on decomposition rate sensitivity to temperature. We show that these uncertainties are on the same order of magnitude than the uncertainty because of climate change. Finally, we find that the OAGCMs having the largest climate sensitivities to CO₂ are the ones with the largest soil drying in the tropics, and therefore with the largest reduction of carbon uptake.     

A Land System representation for global assessments and land‐use modeling

Current global scale land‐change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land‐use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human‐environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi‐)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land‐use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land‐change models that include the human drivers of land change are best parameterized at sub‐global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.     

Global ecosystems and fire: Multi‐model assessment of fire‐induced tree‐cover and carbon storage reduction

In this study, we use simulations from seven global vegetation models to provide the first multi‐model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001–2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire‐induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state‐of‐the‐art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.     

Spatial heterogeneity of climate and land-cover constraints on distributions of tick-borne pathogens

Aim To compare the geographical distributions of two tick‐borne pathogens vectored by different tick species, to examine the relative importance of climate, land cover and host density in structuring these distributions, and to assess the spatial variability of these environmental constraints across the species ranges. Location South‐central and south‐eastern North America. Methods Presence/absence data for two tick‐borne pathogens, Ehrlichia chaffeensis and Anaplasma phagocytophilum, were obtained for 567 counties from a regional data base based on white‐tailed deer (Odocoileus virginianus) serology. Environmental variables describing climate, land cover and deer density were calculated for these counties. Global logistic regression analysis was used to screen the environmental variables and select a parsimonious subset of predictors. Local analysis was carried out using geographically weighted regression (GWR) to explore spatial variability in the parameters of the regression models. Cluster analysis was applied to the GWR output to identify zones with distinctive species–habitat relationships. Results Global habitat models for E. chaffeensis and A. phagocytophilum included temperature, humidity, precipitation and forest cover as explanatory variables. The E. chaffeensis model also included forest fragmentation, whereas the A. phagocytophilum model included deer density. Local analyses revealed that climate was the primary correlate of pathogen presence in the eastern portion of the study area, whereas forest cover and fragmentation constrained the western range boundaries. Habitat relationships for all variables were weak in and around the Mississippi Delta. Main conclusions Efforts to model pathogen and disease ranges, and to predict shifts in response to global change should consider future scenarios of land‐cover change as well as climate change, and should address the possibility of spatial heterogeneity in species–habitat relationships. The methods presented here outline an approach for objectively delineating geographical zones with similar species–environment relationships, which can then be used to stratify landscapes for the purposes of further explanatory and predictive modelling.     

Anticipating the spatio‐temporal response of plant diversity and vegetation structure to climate and land use change in a protected area

Vegetation is a key driver of ecosystem functioning (e.g. productivity and stability) and of the maintenance of biodiversity (e.g. creating habitats for other species groups). While vegetation sensitivity to climate change has been widely investigated, its spatio‐temporally response to the dual effects of land management and climate change has been ignored at landscape scale. Here we use a dynamic vegetation model called FATE‐HD, which describes the dominant vegetation dynamics and associated functional diversity, in order to anticipate vegetation response to climate and land‐use changes in both short and long‐term perspectives. Using three contrasted management scenarios for the Ecrins National Park (French Alps) developed in collaboration with the park managers, and one regional climate change scenario, we tracked the dynamics of vegetation structure (forest expansion) and functional diversity over 100 yr of climate change and a further 400 additional years of stabilization. As expected, we observed a slow upward shift in forest cover distribution, which appears to be severely impacted by pasture management (i.e. maintenance or abandonment). The time lag before observing changes in vegetation cover was the result of demographic and seed dispersal processes. However, plant diversity response to environmental changes was rapid. After land abandonment, local diversity increased and spatial turnover was reduced, whereas local diversity decreased following land use intensification. Interestingly, in the long term, as both climate and management scenarios interacted, the regional diversity declined. Our innovative spatio‐temporally explicit framework demonstrates that the vegetation may have contrasting responses to changes in the short and the long term. Moreover, climate and land‐abandonment interact extensively leading to a decrease in both regional diversity and turnover in the long term. Based on our simulations we therefore suggest a continuing moderate intensity pasturing to maintain high levels of plant diversity in this system.     

A multi-modeling approach to evaluating climate and land use change impacts in a Great Lakes River Basin

River ecosystems are driven by linked physical, chemical, and biological subsystems, which operate over different temporal and spatial domains. This complexity increases uncertainty in ecological forecasts, and impedes preparation for the ecological consequences of climate change. We describe a recently developed “multi-modeling” system for ecological forecasting in a 7600 km² watershed in the North American Great Lakes Basin. Using a series of linked land cover, climate, hydrologic, hydraulic, thermal, loading, and biological response models, we examined how changes in both land cover and climate may interact to shape the habitat suitability of river segments for common sport fishes and alter patterns of biological integrity. In scenario-based modeling, both climate and land use change altered multiple ecosystem properties. Because water temperature has a controlling influence on species distributions, sport fishes were overall more sensitive to climate change than to land cover change. However, community-based biological integrity metrics were more sensitive to land use change than climate change; as were nutrient export rates. We discuss the implications of this result for regional preparations for climate change adaptation, and the extent to which the result may be constrained by our modeling methodology.     

Terrestrial and aquatic responses to climate change and human impact on the southeastern Tibetan Plateau during the past two centuries

Rapid population growth and economic development have led to increased anthropogenic pressures on the Tibetan Plateau, causing significant land cover changes with potentially severe ecological consequences. To assess whether or not these pressures are also affecting the remote montane‐boreal lakes on the SE Tibetan Plateau, fossil pollen and diatom data from two lakes were synthesized. The interplay of aquatic and terrestrial ecosystem response was explored in respect to climate variability and human activity over the past 200 years. Nonmetric multidimensional scaling and Procrustes rotation analysis were undertaken to determine whether pollen and diatom responses in each lake were similar and synchronous. Detrended canonical correspondence analysis was used to develop quantitative estimates of compositional species turnover. Despite instrumental evidence of significant climatic warming on the southeastern Plateau, the pollen and diatom records indicate very stable species composition throughout their profiles and show only very subtle responses to environmental changes over the past 200 years. The compositional species turnover (0.36–0.94 SD) is relatively low in comparison to the species reorganizations known from the periods during the mid‐ and early‐Holocene (0.64–1.61 SD) on the SE Plateau, and also in comparison to turnover rates of sediment records from climate‐sensitive regions in the circum arctic. Our results indicate that climatically induced ecological thresholds are not yet crossed, but that human activity has an increasing influence, particularly on the terrestrial ecosystem in our study area. Synergistic processes of post‐Little Ice Age warming, 20th century climate warming and extensive reforestations since the 19th century have initiated a change from natural oak‐pine forests to seminatural, likely less resilient pine‐oak forests. Further warming and anthropogenic disturbances would possibly exceed the ecological threshold of these ecosystems and lead to severe ecological consequences.     

Changing environmental gradients over forty years alter ecomorphological variation in Guadalupe Bass Micropterus treculii throughout a river basin

Understanding the degree of intraspecific variation within and among populations is a key aspect of predicting the capacity of a species to respond to anthropogenic disturbances. However, intraspecific variation is usually assessed at either limited temporal, but broad spatial scales or vice versa, which can make assessing changes in response to long‐term disturbances challenging. We evaluated the relationship between the longitudinal gradient of changing flow regimes and land use/land cover patterns since 1980 and morphological variation of Guadalupe Bass Micropterus treculii throughout the Colorado River Basin of central Texas. The Colorado River Basin in Texas has experienced major alterations to the hydrologic regime due to changing land‐ and water‐use patterns. Historical collections of Guadalupe Bass prior to rapid human‐induced change present the unique opportunity to study the response of populations to varying environmental conditions through space and time. Morphological differentiation of Guadalupe Bass associated with temporal changes in flow regimes and land use/land cover patterns suggests that they are exhibiting intraspecific trait variability, with contemporary individuals showing increased body depth, in response to environmental alteration through time (specifically related to an increase in herbaceous land cover, maximum flows, and the number of low pulses and high pulses). Additionally, individuals from tributaries with increased hydrologic alteration associated with urbanization or agricultural withdrawals tended to have a greater distance between the anal and caudal fin. These results reveal trait variation that may help to buffer populations under conditions of increased urbanization and sprawl, human population growth, and climate risk, all of which impose novel selective pressures, especially on endemic species like Guadalupe Bass. Our results contribute an understanding of the adaptability and capacity of an endemic population to respond to expected future changes based on demographic or climatic projection.     

Modelling the impact of climate and land use change on the geographical distribution of leaf anatomy in a temperate flora

Variation in plant functional traits has been related to variation in environmental conditions. In particular, the relationship between leaf traits and climate has received much attention. This paper presents a functional‐trait‐centred approach to identify potential impacts of climate and land use change on plant species assemblages. Using species atlas data, we modelled the relative frequencies of species with different leaf anatomies (LARF) as a function of observed climate and land use data on a regular spatial grid across Germany. Subsequently, we projected the geographical distribution of LARF with simulated climate and land use data for the late 21st century under two future scenarios. We used a conditional autoregressive regression model to account for spatially structured variation in LARF that remained unexplained by the environmental factors considered. We found a clear relationship between the climatic gradient of water availability and shifts in LARF: increasing water deficit was associated with a decreasing proportion of species with hygromorphic leaves in the composition and increasing proportions of species with scleromorphic and mesomorphic leaves. The variation in LARF due to land use was only small. Under future environmental scenarios the proportion of species with hygromorphic leaves was projected to decrease in all parts of Germany, whereas the proportions of species with sclero‐ and mesomorphic leaves were projected to increase on average. In particular, Germany's south‐western and north‐eastern areas were projected to experience functional change in LARF. Our study highlights the relationship between functional traits and plant species vulnerability to climate change. Our results suggest that the functional‐trait‐centred approach can provide a powerful additional modelling tool to estimate potential impacts of climate change on plant species assemblages.     

黄河源头地区土地覆盖的时空变化特征

以野外调查和遥感影像为主要信息源, 结合统计资料和基础地理信息数据, 研究了20世纪80年代中期以来黄河源头地区土地覆盖格局的空间特征以及动态变化趋势, 探讨了导致黄河源区生态环境变化的主要影响因素。研究结果表明, 黄河源头地区土地覆盖类型的斑块密度变化差异明显;土地利用类型的镶嵌格局在空间和时间上均有变化。占据优势的草地生态系统20 年来遭受不同程度破坏, 黄河源区的气候呈暖干化趋势, 研究区域土地覆盖类型空间结构变化明显;高寒环境和气候演化趋势对土地覆盖的变化起决定性作用。     

Desertification alters regional ecosystem–climate interactions

We studied the spatial patterns and temporal dynamics of vegetation structural responses to precipitation variation in grassland, transitional, and desertified‐shrubland ecosystems in an 800 km² region of Northern Chihuahua, USA. Airborne high‐fidelity imaging spectroscopy data collected from 1997 to 2001 provided spatially detailed measurements of photosynthetic and senescent canopy cover and bare soil extent. The observations were made following wintertime and summer monsoonal rains, which varied in magnitude by >300% over the study period, allowing an assessment of ecosystem responses to climate variation in the context of desertification. Desertification caused a persistent increase in both photosynthetic vegetation (PV) and bare soil cover, and a lasting decrease in nonphotosynthetic vegetation (NPV). We did not observe a change in the spatial variability of PV cover, but its temporal variation decreased substantially. In contrast, desertification caused the spatial variability of NPV to increase markedly, while its temporal variation did not change. Both the spatial and temporal variation of exposed bare surfaces decreased with desertification. Desertification appeared to be linked to a shift in seasonal precipitation use by vegetation from mainly summer to winter inputs, resulting in an apparent decoupling of vegetation responses to inter‐annual monsoonal variation. Higher winter rainfall led to decreased springtime spatial variability in the PV cover of desertified areas. Higher summer rainfall resulted in decreased PV cover variation in grassland, transition and desertified‐shrubland regions. The effects of desertification on NPV dynamics were more than three times greater than on PV or bare soil dynamics. Using remotely sensed PV and NPV as proxies for net primary production (NPP) and litter dynamics, respectively, we estimated that desertification decreases the temporal variability of NPP and increases spatial variation of litter production and loss. Quantitative studies of surface biological materials and ecosystem processes can now be measured with high ‘structural’ detail using imaging spectroscopy and shortwave‐infrared spectral mixture analysis.     

Morphological variation in salamanders and their potential response to climate change

Despite the recognition that some species might quickly adapt to new conditions under climate change, demonstrating and predicting such a fundamental response is challenging. Morphological variations in response to climate may be caused by evolutionary changes or phenotypic plasticity, or both, but teasing apart these processes is difficult. Here, we built on the number of thoracic vertebrae (NTV) in ectothermic vertebrates, a known genetically based feature, to establish a link with body size and evaluate how climate change might affect the future morphological response of this group of species. First, we show that in old‐world salamanders, NTV variation is strongly related to changes in body size. Secondly, using 22 salamander species as a case study, we found support for relationships between the spatial variation in selected bioclimatic variables and NTV for most of species. For 44% of species, precipitation and aridity were the predominant drivers of geographical variation of the NTV. Temperature features were dominant for 31% of species, while for 19% temperature and precipitation played a comparable role. This two‐step analysis demonstrates that ectothermic vertebrates may evolve in response to climate change by modifying the number of thoracic vertebrae. These findings allow to develop scenarios for potential morphological evolution under future climate change and to identify areas and species in which the most marked evolutionary responses are expected. Resistance to climate change estimated from species distribution models was positively related to present‐day species morphological response, suggesting that the ability of morphological evolution may play a role for species’ persistence under climate change. The possibility that present‐day capacity for local adaptation might help the resistance response to climate change can be integrated into analyses of the impact of global changes and should also be considered when planning management actions favouring species persistence.     

A new land-cover map of Africa for the year 2000

Aim In the framework of the Global Land Cover 2000 (GLC 2000), a land‐cover map of Africa has been produced at a spatial resolution of 1 km using data from four sensors on‐board four different Earth observing satellites. Location The map documents the location and distribution of major vegetation types and non‐vegetated land surface formations for the entire African continent plus Madagascar and the other surrounding islands. Methods The bulk of these data were acquired on a daily basis throughout the year 2000 by the VEGETATION sensor on‐board the SPOT‐4 satellite. The map of vegetation cover has been produced based upon the spectral response and the temporal profile of the vegetation cover. Digital image processing and geographical information systems techniques were employed, together with local knowledge, high resolution imagery and expert consultation, to compile a cartographic map product. Radar data and thermal sensors were also used for specific land‐cover classes. Results A total of 27 land cover categories are documented, which has more thematic classes than previously published land cover maps of Africa contain. Systematic comparison with existing land cover data and 30‐m resolution imagery from Landsat are presented, and the map is also compared with other pan‐continental land cover maps. The map and digital data base are freely available for non‐commercial uses from http://www.gvm.jrc.it/tem/africa/products.htm Main conclusions The map improves our state of knowledge of the land‐cover of Africa and presents the most spatially detailed view yet published at this scale. This first version of the map should provide an important input for regional stratification and planning purposes for natural resources, biodiversity and climate studies.     

Local and cross‐seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site‐specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site‐specific crop cover, and county‐level herbicide (glyphosate) application. We also incorporated cross‐seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county‐level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide‐resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site‐specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine‐resolution temporal fluctuations in population‐level responses to environmental conditions when inferring the dynamics of migratory species.     

Degraded rangeland dominated by unpalatable forbs exhibits large-scale spatial heterogeneity

The spatial heterogeneity of vegetation and soil increases in response to land degradation caused by grazing mainly at a large spatial scale. This increase has been frequently associated with shrub invasion, but shrub invasion does not necessarily accompany land degradation. Instead, dominance by unpalatable forbs has been reported in some regions, but the spatial heterogeneity of such degraded rangeland has not been studied. We investigated the spatial heterogeneity of rangeland dominated by unpalatable forbs at a large spatial scale using Mongolian rangeland as an example. Spatial heterogeneity of the total vegetation cover and community heterogeneity were analyzed for three levels of land degradation. We found that the least-degraded site had homogeneous total vegetation cover and community, that the site with intermediate degradation exhibited low heterogeneity of the total vegetation cover but significant community type variation, and that the most degrade sites exhibited a periodic pattern of total vegetation cover as a result of a mixture of dense and sparse patches of unpalatable forbs. These different responses can be used to assess land degradation levels and may have potential to monitor land degradation at a large scale by satellite images.