Anthropogenic Land Cover Change Research Articles

Unoccupied aerial vehicles as a tool to map lizard operative temperature in tropical environments

AbstractTo understand how ectotherms will respond to warming temperatures, we require information on thermal habitat quality at spatial resolutions and extents relevant to the organism. Measuring thermal habitat quality is either limited to small spatial extents, such as with ground‐based 3D operative temperature (Te) replicas, representing the temperature of the animal at equilibrium with its environment, or is based on microclimate derived from physical models that use land cover variables and downscale coarse climate data. We draw on aspects of both these approaches and test the ability of unoccupied aerial vehicle (UAV) data (optical RGB) to predict fine‐scale heterogeneity in sub‐canopy lizard (Anolis bicaorum) Te in tropical forest using random forest models. Anolis bicaorum is an endemic, critically endangered, species, facing significant threats of habitat loss and degradation, and work was conducted as part of a larger project. Our findings indicate that a model incorporating solely air temperature, measured at the centre of the 20 × 20 m plot, and ground‐based leaf area index (LAI) measurements, measured at directly above the 3D replica, predicted Te well. However, a model with air temperature and UAV‐derived canopy metrics performed slightly better with the added advantage of enabling the mapping of Te with continuous spatial extent at high spatial resolutions, across the whole of the UAV orthomosaic, allowing us to capture and map Te across the whole of the survey plot, rather than purely at 3D replica locations. Our work provides a feasible workflow to map sub‐canopy lizard Te in tropical environments at spatial scales relevant to the organism, and across continuous areas. This can be applied to other species and can represent species within the same community that have evolved a similar thermal niche. Such methods will be imperative in risk modelling of such species to anthropogenic land cover and climate change.

High genetic connectivity of two pollinating flies despite urban disturbance

AbstractHoverflies (Syrphidae) are essential pollinators, and their severe decline jeopardizes their invaluable contribution to plant diversity and agricultural production. However, we know little about the dispersal abilities of hoverflies in urbanized landscapes, limiting our understanding of the spatiotemporal dynamics of plant–pollinator systems and reducing our ability to preserve biodiversity in the context of global change. Previous work has not addressed how urbanization affects the functional connectivity of hoverflies and whether dispersal is a limiting factor in their population dynamics. In this study, we investigated the spatial genetic structure of two nonmigratory species of hoverflies in two urban areas. We collected more than a thousand specimens of each Syritta pipiens and Myathropa florea, each, by hand netting in two western European urbanized study areas of 490 and 460 km2 in 2021, and we genotyped them at 14 and 24 microsatellite loci, respectively. Based on spatial and nonspatial Bayesian clustering methods, we failed to reject the null hypothesis of panmixia, suggesting that both species exhibited high genetic connectivity despite urbanization. The distribution of allele frequencies was not correlated with geographic distance, implying that isolation‐by‐distance was negligible at the investigated spatial scale in both species. Although anthropogenic land cover changes generally have dramatic consequences on biodiversity, these hoverfly species retain high connectivity, which suggests that dispersal is not a strong limiting factor in their metapopulational dynamics. However, high effective population size and its confounding effect on signals of genetic drift may limit our ability to conclude confidently about landscape effects on gene flow in those two species. Provided we maintain or restore habitat, recolonization may be prompt even in urban areas.

Reconstruction of cropland cover in topographically complex areas: The case of Sichuan Province, China, from 1671 to 2019

Accurately reconstructing cropland cover in topographically complex areas has long been challenging for historical anthropogenic land cover change (ALCC) datasets. Sichuan Province, one of the most topographically complex areas in China, was chosen as a case study. This study integrated historical gazetteers and modern cropland statistics and survey data to examine and correct the prefecture-level cropland area of Sichuan Province. Subsequently, a novel cropland reconstruction model was proposed based on the order of cropland reclamation. Using this model, cropland changes in Sichuan Province from 1671 to 2019 were reconstructed with a spatial resolution of 5′ × 5′. The main findings were as follows: (1) The cropland reconstruction model designed in this study can well reproduce with the cropland cover in Sichuan Province. Compared with the prevailing ALCC datasets, our reconstructions were more consistent with descriptions of cropland changes in Sichuan Province in the literature. (2) The cropland cover in Sichuan Province expanded from northeastern and southern Sichuan to the Chengdu Plain and the hills north of the Yangtze River and then to the mountainous areas in the center and periphery of the basin from 1671 to 1985, after which it shrank in mountainous and urban areas. (3) The changes in cropland cover in Sichuan Province over the past 350 years were shaped by multiple factors such as war, famine, migration, agricultural policies and urbanization. The reconstructions in this study captured the spatial differences in cropland distribution in Sichuan Province, but their accuracy was limited by the cropland estimation method and the satellite-based cropland data used in the reconstruction model.

Effect of land cover pattern on rainfall during a landfalling typhoon: A simulation of Typhoon Hato

The impact of urbanization on weather events has received increasing attention. Taking Typhoon Hato as an example, the impact of anthropogenic land cover change on typhoon landfall and sequential rainfall is quantified in this study. A numerical model is first built based on the Weather Research and Forecast model. Then, the model is validated, the performance of parameters for the different meteorological and microphysical processes is assessed and a set of optimal parameters are selected. After that, the responses of typhoon and the corresponding rainfall to land cover patterns under three conditions of no urbanization, current urbanization and future urbanization in Pearl River Delta are simulated and compared. Verification experiments show that it is necessary to consider the microphysical process to enhance the accuracy of typhoon simulation. The dramatic change of land cover has limited influence on typhoon tracks. However, the urbanized land surface promotes typhoon rainfall significantly. The hourly rainfall rate under the urbanization condition is about double that under the no urbanization condition. With the intensifying urbanization in the future, the maximum hourly rainfall rate will increase by 21%. The urban heat island effect almost disappears as Typhoon Hato approaches the inland region, and the urban dynamic effect plays an important role in typhoon rainfall. The intensified rainfall is related to the retention of typhoon caused by rough surface of the city. The wind speed under the condition of no urbanization is in general 2 m/s greater than that under the urbanization condition. The increase in surface roughness reduces the typhoon movement speed and more rainfall is generated. With the development of urbanization, intensified rainfall at typhoon landfall needs to be paid more attention to.

Multiscale pollen-based reconstructions of anthropogenic land-cover change in Karula Upland, south Estonia

Pollen-based quantitative vegetation reconstructions using multiple sedimentary basins from the same area, along with their quantified relevant pollen source areas, are a powerful means to study how long-term human impact has affected vegetation and shaped the currently protected heritage landscapes at different spatial scales. Our study presents the outcome of a palynological investigation in Karula Upland, south Estonia, for the last 6500 years. Centennial-resolution pollen records from one large (175 ha) and three small (5 ha) lakes, and one small bog (0.1 ha) were used to reconstruct the vegetation at different spatial scales using the Landscape Reconstruction Algorithm. The results are discussed in combination with archaeological sites and historical knowledge.The first signs of small-scale forest clearings connected to local human settlements are already visible in the Middle Stone Age (3100–4100 BCE). The first finds of cereal pollen (2500 BCE) from Lake Ähijärv suggest that grain crops were introduced to south Estonia during the Late Stone Age. The evidence of local crop farming in Karula is traceable since the Bronze Age. The widespread practice of slash-and-burn agriculture led to a major shift in land-cover with replacement of old-growth forests with the early-successional birch, occupying long-term fallows, during Late Bronze Age and Early Iron Age (700–250 BCE). A notable regression in farming is visible during the second part of the Early Iron Age (100–600 CE), with the most prominent change taking place around 500 CE, roughly coinciding with the 6th century Northern Hemisphere climate cooling and Migration Period. Permanent fields gained importance alongside slash-and-burn cultivation, during the Late Iron Age, ca 600–700 CE, shifting the vegetation composition towards more open land-cover. The ∼50 % open mosaic land-cover of the heritage landscape, protected today in Karula Upland, was formed during the Late Iron Age.The current study shows that sedimentary basins as close as ca 2 km from each other sometimes tell different stories, highlighting the need to quantify the size of the pollen source area to combine successfully archaeological, historical, and palynological evidence. Quantitative pollen-based vegetation reconstructions provide an environmental context for known, and possibly unknown, archaeological evidence within the pollen source area.

Impacts of anthropogenic land use and land cover change on climate extremes based on CMIP6-LUMIP experiments: part II. Future period

Impacts of anthropogenic land use and land cover change on climate extremes based on CMIP6-LUMIP experiments: part II. Future period

Past anthropogenic land use change caused a regime shift of the fluvial response to Holocene climate change in the Chinese Loess Plateau

Abstract. The Wei River catchment in the southern part of the Chinese Loess Plateau (CLP) is one of the centers of the agricultural revolution in China. The area has experienced intense land use changes since ∼6000 BCE, which makes it an ideal place to study the response of fluvial systems to past anthropogenic land cover change (ALCC). We apply a numerical landscape evolution model that combines the Landlab landscape evolution model with an evapotranspiration model to investigate the direct and indirect effects of ALCC on hydrological and morphological processes in the Wei River catchment since the mid-Holocene. The results show that ALCC has not only led to changes in discharge and sediment load in the catchment but also affected their sensitivity to climate change. When the proportion of agricultural land area exceeded 50 % (around 1000 BCE), the sensitivity of discharge and sediment yield to climate change increased abruptly indicating a regime change in the fluvial catchment. This was associated with a large sediment pulse in the lower reaches. The model simulation results also show a link between human settlement, ALCC and floodplain development: changes in agricultural land use led to downstream sediment accumulation and floodplain development, which in turn resulted in further spatial expansion of agriculture and human settlement.

An Overview of Anthropogenic Changes in Land Use and Land Cover, with Specific Attention to Climate Change and Unsustainable Agriculture

The worldwide need for food and the alterations in bioenergy demands associated with shifts in land use and land cover changes (LULCC) have given rise to environmental apprehensions, including global warming and climate change. There is substantial evidence indicating that we are currently witnessing human-induced transformations that could potentially result in a sixth mass extinction event. This study seeks to explore the connections between land use and land cover change (LULCC), forests, biodiversity, the carbon cycle, hydrology, climate, and various biogeochemical feedback mechanisms. These interrelationships play a crucial role in shaping future environmental outcomes and influencing climate change. Additionally, the review critically assesses existing research on the correlation between LULCC and climate, along with associated processes. The paper delves into ongoing investigations surrounding LULCC, its ecological repercussions, and its influence on the regulatory mechanisms of terrestrial ecosystems, ecosystem services, atmospheric chemistry, and the climate. It underscores the importance of developing land-use strategies rooted in a scientific evaluation of LULCC to promote sustainability and wider economic development, with a particular emphasis on addressing climate change. Global agreements and protocols also call for land use strategies that consider the implications of environmental degradation.

Land cover changes and carbon dynamics in Central India's dry tropical forests: A 25-year assessment and nature-based eco-restoration approaches

Anthropogenic land use and land cover changes are major drivers of environmental degradation and declining soil health across heterogeneous landscapes in Central India. To examines the land cover changes and spatio-temporal variations in forest carbon stock and soil organic carbon (SOC) over the past 25 years in central India. Geospatial techniques, coupled with ground measurements were employed to detect changes in land cover, carbon stocks in vegetation, and soil carbon in various vegetation types. The results indicate that forested areas have decreased, while agriculture and habitation have expanded between 1997 and 2022. Vegetation C stocks varied significantly (P < 0.05) from 39.42 to 139.95 Mg ha−1 and the SOC varied from 7.02 to 17.98 Mg ha−1 under different soil profiles across vegetation types, which decreased with soil depth, while the pH and bulk density increased. The maximum bulk density in the soil was found at a depth of 40–60 cm (lower profile) in Bamboo Brake, while the minimum was observed under Dense Mixed Forest at a depth of 0–20 cm (top profile). The topsoil profile contributed 33.6%–39%, the middle profile (20–40 cm) was 33.6%–34.4%, and the lower profile was 26.5%–30.8% of soil organic carbon. The study site has experienced rapid carbon losses due to changes in land cover, such as illegal expansion of agriculture, encroachments into forest fringes, and activities like selective logging and overgrazing, which have degraded dense forests. The ecological engineering of degraded ecosystems poses a great challenge and application of complex biological, mechanical and engineering measures is highly cumbersome, expensive, uneconomical and practically not feasible for upscaling. Nevertheless, proposed nature-based solutions mimic natural reparation and processes provide sustainable interventions for the reclamation of ruined landscapes besides improving ecological integrity and rendering many co-benefits to ecosystems and human societies.

Breakdown in seasonal dynamics of subtropical ant communities with land-cover change.

Concerns about widespread human-induced declines in insect populations are mounting, yet little is known about how land-use change modifies both the trends and variability of insect communities, particularly in understudied regions. Here, we examine how the seasonal activity patterns of ants-key drivers of terrestrial ecosystem functioning-vary with anthropogenic land-cover change on a subtropical island landscape, and whether differences in temperature or species composition can explain observed patterns. Using trap captures sampled biweekly over 2 years from a biodiversity monitoring network covering Okinawa Island, Japan, we processed 1.2 million individuals and reconstructed activity patterns within and across habitat types. Forest communities exhibited greater temporal variability of activity than those in more developed areas. Using time-series decomposition to deconstruct this pattern, we found that sites with greater human development exhibited ant communities with diminished seasonality, reduced synchrony and higher stochasticity compared with sites with greater forest cover. Our results cannot be explained by variation in regional or site temperature patterns, or by differences in species richness or composition among sites. Our study raises the possibility that disruptions to natural seasonal patterns of functionally key insect communities may comprise an important and underappreciated consequence of global environmental change that must be better understood across Earth's biomes.

Watershed-Mediated Ecomorphological Variation: A Case Study with the Twin-Striped Clubtail Dragonfly (Hylogomphus geminatus).

Anthropogenic land-cover change is modifying ecosystems at an accelerating rate. Changes to ecomorphologically variable taxa within those ecosystems serve as early-warning signs that resources on which humans and other animals depend are being altered. One known ecomorphologically variable taxon is Hylogomphus geminatus, a species of dragonfly in the southeastern United States that shows pronounced variation in total body length across its limited geographic range. We measured total length of live as well as preserved museum specimens of H. geminatus and the sympatric species Progomphus obscurus (as a means for comparison). Both species showed significant size differences linked to HUC-8 watersheds in which they occur. H. geminatus showed additional significant differences on either side of the Apalachicola River, Florida, for all comparisons by sex. In overlapping watersheds, the species tended to show the same trends in length relative to their respective averages. Smaller body length was associated with more urban and agricultural land cover. These findings indicate that ecomorphological variation is tied to the watershed scale and point to significant variations on either side of the Apalachicola River. More thorough future analyses would be needed to verify trends in body length and identify the drivers behind them.

Identifying a scenario for preindustrial cropland cover using cultivation data: A case study of France, Germany and Italy

Cropland expansion is effected by physiogeographic and sociocultural factors, which vary across region and over time, but have not been adequately represented in large-scale anthropogenic land cover change scenarios. Taking preindustrial cropland expansion in France, Germany, and Italy as a case study, this study first adopted a productivity-based estimation of cropland per capita, which converted crop yield to cropland demand per capita through negative correlations under different crop rotations, to improve the accuracy of national cropland areas. Then, a new allocation algorithm was proposed to allocate national cropland areas into 5′× 5′ grids. The algorithm combines land suitability, which characterizes regional differentiation of potential productivity indicated by physiogeographic factors (climate, topography, soil, etc.) that dominate cultivation, and cultivation preference, which quantifies sociocultural impacts by kernel density estimation based on city information (i.e., location, size, accessibility). The cropland cover scenario here shows similar phases but different modes of cropland expansion in these countries: (1) National cropland areas increased 1.73–2.46 times during the 11th–13th centuries, manifested by the expanding cultivated ranges in France and Germany and the increasing cultivation intensity in Italy. (2) National cropland fractions decreased by 9.16–19.98 percentage points in the 14th century, accompanied by widespread reductions in cultivation intensity. (3) Cropland gradually recovered toward its peak in 1300 AD during the 15th–18th centuries, achieved by general and remarkable increases in cultivation intensity. Compared to representative global datasets, this study is more consistent with cultivation-related descriptions in the literature, especially with respect to the cropland expansion in newly cultivated regions and on marginal lands.

High-resolution land use and land cover dataset for regional climate modelling: historical and future changes in Europe

Abstract. Anthropogenic land use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently being extensively investigated within the World Climate Research Program (WCRP) Coordinated Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) Land Use and Climate Across Scales (LUCAS) using an ensemble of different regional climate models (RCMs) coupled with diverse land surface models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM–LSM simulations. To account for these needs, we generated the LUCAS Land Use and land Cover change (LUC) dataset version 1.1 at 0.1∘ resolution for Europe with annual LULC maps from 1950 to 2100 (https://doi.org/10.26050/WDCC/LUC_hist_EU_v1.1, Hoffmann et al., 2022b, https://doi.org/10.26050/WDCC/LUC_future_EU_v1.1, Hoffmann et al., 2022a), which is tailored to use in state-of-the-art RCMs. The plant functional type (PFT) distribution for the year 2015 (i.e. the Modelling human LAND surface Modifications and its feedbacks on local and regional cliMATE – LANDMATE – PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details on the conversion method, cross-walking procedure, and evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (2022b). Subsequently, we applied the land use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25∘ resolution as input for Coupled Modelling Intercomparison Project Phase 6 (CMIP6) experiments, to derive LULC distributions at high spatial resolution and at annual time steps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a land use translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to other annual LULCC datasets. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different shared socioeconomic pathway (SSP) and representative concentration pathway (RCP) combinations used in the framework of CMIP6. The resulting LULCC maps can be applied as land use forcing to the new generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions worldwide.

How Does Intensive Land Use Affect Low-Carbon Transition in China? New Evidence from the Spatial Econometric Analysis

Anthropogenic land cover change is one of the primary sources of increasing carbon emissions and affects the potential of terrestrial ecosystems to store carbon and act as carbon sinks. As a necessary means to reduce land expansion, land-use intensification significantly impacts greenhouse gas emission reduction and the low-carbon transition of the economy. This paper constructs a framework for the relationship between intensive land use (ILU) and low carbon transition (LCT), considering direct and spatially driven effects. First, this paper constructs a multidimensional indicator to measure intensive land use and documents the spatial pattern of intensive land use levels in China. Second, this paper assesses the spatial driving effect of intensive land use on China’s economic low-carbon transition. Based on data from 283 Chinese cities from 2006–2019 and using a spatial Durbin model, the study provides empirical evidence that intensive land use can significantly promote low-carbon transition in neighboring and economically linked cities (especially in eastern cities, large and medium-sized cities, and veteran economic circles). Tests introducing exogenous policy shocks further confirm the robustness of the findings. In addition, industrial structure transformation and technology spillovers are identified as the dual mechanism channels of intensive land use for low-carbon transition in China, and the spatial driving effect on neighboring cities attenuating with geographic distance is also confirmed.

Did the Bronze Age deforestation of Europe affect its climate? A regional climate model study using pollen-based land cover reconstructions

Abstract. This paper studies the impact of land use and land cover change (LULCC) on the climate around 2500 years ago (2.5 ka), a period of rapid transitions across the European landscape. One global climate model was used to force two regional climate models (RCMs). The RCMs used two land cover descriptions. The first was from a dynamical vegetation model representing potential land cover, and the second was from a land cover description reconstructed from pollen data by statistical interpolation. The two different land covers enable us to study the impact of land cover on climate conditions. Since the difference in landscape openness between potential and reconstructed land cover is mostly due to LULCC, this can be taken as a measure of early anthropogenic effects on climate. Since the sensitivity to LULCC is dependent on the choice of climate model, we also use two RCMs. The results show that the simulated 2.5 ka climate was warmer than the simulated pre-industrial (PI, 1850 CE) climate. The largest differences are seen in northern Europe, where the 2.5 ka climate is 2–4 ∘C warmer than the PI period. In summer, the difference between the simulated 2.5 ka and PI climates is smaller (0–3 ∘C), with the smallest differences in southern Europe. Differences in seasonal precipitation are mostly within ±10 %. In parts of northern Europe, the 2.5 ka climate is up to 30 % wetter in winter than that of the PI climate. In summer there is a tendency for the 2.5 ka climate to be drier than the PI climate in the Mediterranean region. The results also suggest that LULCC at 2.5 ka impacted the climate in parts of Europe. Simulations including reconstructed LULCC (i.e. those using pollen-derived land cover descriptions) give up to 1 ∘C higher temperature in parts of northern Europe in winter and up to 1.5 ∘C warmer in southern Europe in summer than simulations with potential land cover. Although the results are model dependent, the relatively strong response implies that anthropogenic land cover changes that had occurred during the Neolithic and Bronze Age could have affected the European climate by 2.5 ka.

More than agriculture: Analysing time-cumulative human impact on European land-cover of second half of the Holocene

Assessment of past anthropogenic modifications of land-cover dynamics is key to understanding the human role in the Earth system. Recent advances in palaeoenvironmental sciences allow us to assess the long-term impacts of anthropization on ecosystems, landscapes, and land-cover.Our study aims to evaluate the role of human impact on European land-cover over the past 6000 years by comparing two independent datasets. First, we use a dynamic vegetation model forced by debiased climate model outputs. The climate model uses natural forcings only and therefore the computed vegetation distribution is interpreted as the potential natural vegetation. Second, we use pollen-based reconstructions, which intrinsically include anthropogenic influence. The discrepancies between the two datasets are attributed to human activity and quantified in a form of a human pressure index (HPI).Patterns of spatio-temporal evolution of the HPI agree with previously published data about the spread of agriculture in Europe. In particular, both HPI and anthropogenic land-cover change (ALCC) scenarios indicate a rapid increase of the human pressure around 1200–1700 BP, and a significant increase of agriculture-related land-cover modifications by nearly 60% throughout the second half of the Holocene. However, initially high HPI values (up to 70%) at 5700–6200 BP, which correlate with population estimates (r = 0.75, p-value <0.005), suggest high levels of anthropogenic land-cover transformations, introduced by earlier agricultural as well as non-agricultural activities.The results of our study suggest that vegetation cover of the Mid-Holocene substantially differed from the state of potential natural vegetation (PNV) due to cumulative effect of early human alterations on the land-cover. This challenges the hypothesis that vegetation in the Mid-Holocene was in a relatively natural state and contributes valuable insights to the onset of agriculture as the start of the Anthropocene.

GIS and remote sensing Based Analysis of Land use and Land cover Change in the Upper Anger watershed, Western Ethiopia

ABSTRACT Anthropogenic land use and land cover (LULC) change was the most serious problem in worldwide. This study attempted to investigate spatiotemporal LULC changes in the Upper Anger watershed, Western Ethiopia. In the present study, Landsat TM of 1990, Landsat ETM+ of 2003, and Landsat OLI/TIRS of 2020 were used to analyze the LULC change and Normalized Difference Vegetation Index (NDVI). The supervised classification with maximum likelihood algorithm was employed for classification of the LULC. The result shows that the agricultural land was increased by 707.4 km2, whereas forest land was decreased by 179.9 km2. Consequently, agricultural land and bare land were increased with rate of 23.6 km2/year and 0.5 km2/year, while grassland and forest cover decreased by rate of 18.2 km2/year and 6 km2/year, respectively, from 1990 to 2020. The maximum NDVI value was declined with 0.19 from 1990 to 2020 due to expansion of agricultural land, bare land, and settlement in the study area. About 530 km2 of grassland and 241.5 km2 of forest cover were converted into other land cover classes between 1990 and 2020. Thus, appropriate land use planning and environmental education should be promoted to minimize the rapid loss of forests and grasslands in the study area.

Spatial and Temporal Diversity Variation in the Anopheles Communities in Malaria-Endemic Regions of Colombia.

This study aimed to evaluate at a temporospatial scale, the influence of anthropogenic land cover changes in the Anopheles species community composition and diversity in two Colombian malaria-endemic regions, Bajo Cauca and Pacific. To determine variations over time, mosquitoes were collected in two time periods; land cover types were characterized on orthorectified aerial photographs, and landscape metrics were estimated for each locality and period. A temporal dissimilarity analysis to evaluated species replacement and the nestedness species loss/gain showed the influence of the species loss or gain component on Anopheles species assemblage (23%). The relationship between land cover variation and Anopheles beta diversity, evaluated by regression analysis, showed the effect of forest variation in the Anopheles community (βsim and forest r2 = 0.9323; βsne and forest r2 = 0.9425). Furthermore, a canonical correspondence analysis showed that the land cover types associated with Anopheles species presence were bare soil, shrub, wet areas, and forest. Results demonstrated the impact of land cover changes attributed to human activities on Anopheles population dynamics, over time; this was evidenced as species loss or gain, which was specific to each locality. Notably, the main malaria vectors were dominant in most localities over time, suggesting their tolerance to anthropogenic transformations; alternatively, the environmental changes are providing adequate ecological conditions for their persistence. Finally, the data generated are relevant for understanding the impact that environmental change may have on the dynamics of the neotropical malaria vectors. Thus, this research has potential implications for vector control interventions.

Management-induced changes in soil organic carbon on global croplands

Abstract. Soil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975–2010, this SOC debt continued to expand by 5 GtC (0.14 GtC yr−1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtC yr−1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement – also within computationally demanding integrated (land use) assessment modeling.

Holocene deforestation history of NE Belgium: An evaluation of pollen- and population-based approaches for reconstructing land cover

Several methods to reconstruct past land cover are available which can be roughly divided into approaches based on pollen data and approaches based on (estimates of) historical human population. In this study, the REVEALS model and non-metric multidimensional scaling (NMDS) are applied to pollen sequences obtained from multiple alluvial floodplains located in the sandy and loamy regions of northeastern Belgium, thereby obtaining the first regional (semi-)quantitative estimates of Holocene landscape openness for this area. These estimates are subsequently compared to the two most widely-used scenarios for anthropogenic land cover change (ALCC): KK10 and HYDE.In contrast with the two population-based ALCC scenarios, the pollen-based reconstructions are well in agreement and indicate considerable variability in past land cover, not only between the two regions but even between the individual catchments. This agreement implies that NMDS could serve as an alternative approach to provide insight in large amounts of pollen data in case not all required model parameters are available to run the REVEALS model. Moreover, NMDS can provide a better understanding of which taxa are related to a particular type of landscape. Taking into account such insights in the interpretation of the REVEALS model output might help to pinpoint the onset of significant human impact on the landscape more precisely. Given that alluvial sites often experienced early anthropogenic impact, including pollen data obtained from alluvial sites could not only improve the spatial coverage and accuracy of current pollen-based land cover reconstructions but could also improve our understanding of human transformation of the landscape, which can in turn contribute to an improvement of the ALCC scenarios.