Tree Cover Change Research Articles

Monitoring Tree Cover Change Using the CuSum Algorithm: A Case Study in the Southern Western Ghats of Kerala

Monitoring Tree Cover Change Using the CuSum Algorithm: A Case Study in the Southern Western Ghats of Kerala

Robust Trend Analysis in Environmental Remote Sensing: A Case Study of Cork Oak Forest Decline

We introduce a novel methodological framework for robust trend analysis (RTA) using remote sensing data to enhance the accuracy and reliability of detecting significant environmental trends. Our approach sequentially integrates the Theil–Sen (TS) slope estimator, the Contextual Mann–Kendall (CMK) test, and the false discovery rate (FDR) control. This comprehensive method addresses common challenges in trend analysis, such as handling small, noisy datasets with outliers and issues related to spatial autocorrelation, cross-correlation, and multiple testing. We applied this RTA workflow to study tree cover trends in Los Alcornocales Natural Park (Southern Spain), Europe’s largest cork oak forest, analysing interannual changes in tree cover from 2000 to 2022 using Terra MODIS MOD44B data. Our results reveal that the TS estimator provides a robust measure of trend direction and magnitude, but its effectiveness is dramatically enhanced when combined with the CMK test. This combination highlights significant trends and effectively corrects for spatial autocorrelation and cross-correlation, ensuring that genuine environmental signals are distinguished from statistical noise. Unlike previous workflows, our approach incorporates the FDR control, which successfully filtered out 29.6% of false discoveries in the case study, resulting in a more stringent assessment of true environmental trends captured by multi-temporal remotely sensed data. In the case study, we found that approximately one-third of the area exhibits significant and statistically robust declines in tree cover, with these declines being geographically clustered. Importantly, these trends correspond with relevant changes in tree cover, emphasising the ability of RTA to detect relevant environmental changes. Overall, our findings underscore the crucial importance of combining these methods, as their synergy is essential for accurately identifying and confirming robust environmental trends. The proposed RTA framework has significant implications for environmental monitoring, modelling, and management.

Modelling Tree Allometries to Understand the Impact of African Savannah Elephant Herbivory Dynamics on the Vegetation Structure and Tree Cover Change in a Protected Area

ABSTRACTIn landscapes with high elephant density, trees often exhibit more open canopies with fewer branches and foliage due to browsing pressure. This can result in altered tree morphology, with trees exhibiting stunted growth, multiple stems or unusual branching patterns in response to repeated damage from browsing. The objectives of this research were to (i) model the vegetation structure allometries, (ii) assess the impact of African savannah elephant (Loxodonta africana) herbivory on the vegetation structure and (iii) assess tree cover change and vegetation performance over time in Mana Pools National Park in Zimbabwe. We established 26 plots of 30 × 30 m size. Selection of sampling plots was done following several steps. First, a fish net grid with 30 × 30 m polygons was created and projected on the polygon of Mana Pools National Park. The polygons for exclusion zones were then clipped from the fish net grid using the clip tool in ArcGIS Pro 3.0. Then, selection of sampling plots was done initially by stratified random sampling using the Sampling Design Tool add in for ArcGIS Pro 3.0. Landsat images for the years 2003, 2013 and 2023 were used to assess land use land cover (LULC) time series and to calculate Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for the period. A generalised linear model (GLM) was used to analyse tree allometries. Further statistical investigations were performed using Bayesian piecewise regression (BPR) and Bayesian regression modelling (BRM). Basal area, number of stems, height, long canopy, diameter and basal circumference were all significantly different (p < 0.05) across all sampled plots. The change in growing conditions occurring as a tree grows beyond the reach of the African savannah elephant browsing indicates a natural system breakpoint. The best‐fitting models were a simple linear model and a two breakpoint model for the plant population exposed to elephant herbivory. LULC, NDVI and SAVI confirm evidence of high tree regeneration over 2 decades. Understanding the dynamics in vegetation and LULC changes is critical for effective conservation and management of the habitats for African savannah elephants, as well as for maintaining the health and resilience of forest ecosystems.

Urban forest cover and ecosystem service response to fire varies across California communities

Urban fires that result from wildfires are an emerging, extreme event affecting communities and urban forests globally. However, much of the fire effects on urban ecosystems literature is primarily focused on Wildland-Urban Interface (WUI) areas, correlates of building loss, risk mitigation, and wildland vegetation and fuels. Three recent urban fires in California USA provided an opportunity to explore these effects on urban forests: the 2017 Tubbs (Santa Rosa) and Thomas (Ventura) and the 2018 Camp fire that burned Paradise. Accordingly, we analyzed pre- and post-fire neighborhood level urban tree cover (nUTC) change over 5 years using Sentinel and LiDAR data (10m resolution). Then, we explored the effects of fire severity on changes in several regulating ecosystem services (e.g., carbon, air pollution, stormwater). Findings from the Rapid Assessment of Vegetation Condition after Wildfire severity processes and other geospatial datasets show that fire effects were patchy with fire severity within neighborhoods ranging from unburned to extreme. We found that ~5 years after the fires, and relative to adjacent non-fire affected neighborhoods, Ventura and Santa Rosa’s nUTC is recovering to pre-fire levels while Paradise’s nUTC is being consistently lost over time. Ventura and Santa Rosa had 20-25% of their fire affected area outside established WUI boundaries. However, local-scale urban tree cover and ecosystem service supply are lagged, and recovery time depends on the surrounding biome and socio-ecological context. In inland, higher elevation communities – like Paradise – the recovery of nUTC and the associated ecosystem services might materialize over a much longer timeframe. Our study provides a roadmap to assess the response of urban wildfire-affected tree cover and ecosystem services across space and time. It is also one of the first assessments of fire effects on urban ecosystems and communities outside of WUI boundaries that are now experiencing increased threat from wildfires globally.

Direct and indirect effects of climate and seed dynamics on the breeding performance of a seed predator at the distribution edge.

Marginal populations usually have low densities and are considered to be particularly vulnerable to environmental stochasticity. Using data collected in nest boxes, we analyzed the breeding performance of the edible dormouse (Glis glis), an obligate hibernating rodent and a seed predator in deciduous forests, in two populations at the distribution range's edge. Despite being only 20 km apart from each other, Montseny is a large patch of mixed deciduous forests (oaks and beech), whereas Montnegre would be the harshest habitat, that is, a small, isolated patch with only oaks. First, we studied the differences in climate and tree cover change in the two populations. Second, we analyzed the direct and indirect roles of local climate conditions and seed availability on breeding performance over 10 years in each population. Finally, we explored the influence of tree cover change on the occupancy dynamics in the two populations. Our results showed contrasting responses between populations: in Montseny, asynchronous seed production between oaks and beech precluded skip breeding, and breeding performance increased with seed availability. Furthermore, dormice in Montseny may use pollen production to anticipate the amount of beech nut resources and adjust their breeding effort. Boxes showed higher occupancy and colonization and fewer extinctions in Montseny than in Montnegre, where seed availability did not drive breeding performance. Results from Montnegre suggest that skip breeding was an adaptive response to a more pulsed, harsher environment. Here, females produced a similar number of pups than at Montseny. Long-term studies dealing with population responses in marginal habitats can lead to a deeper understanding of the capacities of organisms to adapt to harsh environments. Although local adaptation is frequently documented across various taxa, studies at the distribution edge may shed light on our still limited comprehension of the underlying mechanisms responsible for its occurrence.

Application of herbivore ecometrics to reconstruct Neogene terrestrial palaeoenvironments in Falcón, Venezuela

Despite its important position close to the Isthmus of Panama, and abundance of fossil localities, the palaeoenvironment of the Falcón Basin in northwestern Venezuela has been understudied. The basin includes a sequence containing 6 terrestrial fossil assemblages, of which 5 are well-sampled enough for palaeoenvironmental reconstruction. Here we use these assemblages as a test case for taxon-free approaches in the Neotropics, that have been used in studies elsewhere, including dental functional traits, body mass and mesowear. Mesowear reveals browsing and grazing diets from the Late Miocene to the Late Pleistocene, and though the toxodontids (the most abundant mammalian herbivores) show a consistent browsing signal, other approaches support an environment which was largely more open than previously suggested. We find limited evidence for any dramatic climatic shift, instead finding more gradual changes in precipitation and tree cover. Ultimately, we find enough consistency in our results with those of other proxies to suggest that the methods employed here could potentially be applied to other localities in South America.

Learning from local knowledge on changes in tree-cover and water availability: the case of the contested agroforested landscape of the Mt. Elgon Water Tower, Uganda

Participatory Rural Appraisal was used to compare stakeholder perceptions of spatial and temporal variation in tree cover and water availability using Uganda’s Mt. Elgon Water Tower as a case study. This study was guided by the research question: How do multi-level stakeholders’ perceptions of changes in tree-cover and water availability vary across spatial and temporal scales of the water tower? Five Participatory Rural Appraisal tools were applied to understand multi-level stakeholders’ perspectives on the changes in tree-cover and water availability. Data was collected from farmers’ focus group discussions, key experts from local government offices and structured household interviews with local communities. This study focused on the upper and lower zones of the water tower, which differ in terms of proximity to Mt. Elgon National Forest Park, household water-use, elevation, and tree-cover. Results showed that there are both similarities and differences in perceptions of changes in tree cover and water availability among stakeholders. Farmers and key experts perceived a decrease in water availability and a decrease in overall tree cover for the period 1990–2020. There are differences in stakeholders’ perceptions of water availability across the zones and sub-catchments. For instance, more farmers in Sipi River Sub-catchment perceived a decrease in water availability during 2006–2020 compared to 1990–2005 period. There were notable contradictions in farmers’ and key experts’ perceptions on tree cover. Farmers’ perceptions of 1990–2020 precipitation were in agreement with trends in existing precipitation data. Declining trends of natural tree cover especially outside the Mt. Elgon national forest park pose great threat to water resources originating from forests. Changes in tree cover and water availability in the study area can be partly explained by the tree species grown. Local stakeholders’ perceptions complemented the existing data gaps in explaining the changes in tree cover and water availability. Participatory Rural Appraisal tools are helpful for documenting the perceptions of local communities. However, this cannot replace reliable data resulting from large-scale efforts for monitoring changes and variations in tree-cover and water availability. The findings of this paper can be valuable to inform strategies for community involvement in sustainable agroforested landscape management.

High-resolution satellite images reveal the prevalent positive indirect impact of urbanization on urban tree canopy coverage in South America

Trees in urban areas act as carbon sinks and provide ecosystem services for residents. However, the impact of urbanization on tree coverage in South America remains poorly understood. Here, we make use of very high resolution satellite imagery to derive urban tree coverage for 882 cities in South America and developed a tree coverage impacted (TCI) coefficient to quantify the direct and indirect impacts of urbanization on urban tree canopy (UTC) coverage. The direct effect refers to the change in tree cover due to the rise in urban intensity compared to scenarios with extremely low levels of urbanization, while the indirect impact refers to the change in tree coverage resulting from human management practices and alterations in urban environments. Our study revealed the negative direct impacts and prevalent positive indirect impacts of urbanization on UTC coverage. In South America, 841 cities exhibit positive indirect impacts, while only 41 cities show negative indirect impacts. The prevalent positive indirect effects can offset approximately 48% of the direct loss of tree coverage due to increased urban intensity, with full offsets achieved in Argentinian and arid regions of South America. In addition, human activity factors play the most important role in determining the indirect effects of urbanization on UTC coverage, followed by climatic and geographic factors. These findings will help us understand the impact of urbanization on UTC coverage along the urban intensity gradient and formulate policies and strategies to promote sustainable urban development in South America.

Accounting for albedo change to identify climate-positive tree cover restoration

Restoring tree cover changes albedo, which is the fraction of sunlight reflected from the Earth’s surface. In most locations, these changes in albedo offset or even negate the carbon removal benefits with the latter leading to global warming. Previous efforts to quantify the global climate mitigation benefit of restoring tree cover have not accounted robustly for albedo given a lack of spatially explicit data. Here we produce maps that show that carbon-only estimates may be up to 81% too high. While dryland and boreal settings have especially severe albedo offsets, it is possible to find places that provide net-positive climate mitigation benefits in all biomes. We further find that on-the-ground projects are concentrated in these more climate-positive locations, but that the majority still face at least a 20% albedo offset. Thus, strategically deploying restoration of tree cover for maximum climate benefit requires accounting for albedo change and we provide the tools to do so.

Characterization of Change in Tree Cover State and Condition over the Conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Beyond the metropolis: street tree communities and resident perceptions on ecosystem services in small urban centers in India

Abstract Although 41% of the global urban population lives in smaller cities, the nature and trajectories of urban nature, ecosystem services and human-nature connections in smaller centers is relatively unknown. While megacities in developed countries move towards biophilic urban planning and participatory decision making, basic information on tree communities and their perceived services is a bottleneck in achieving these goals in such small urban centers. Through a combination of field measurements (258 transects, 931 trees) and semi-structured interviews (497 individuals), we assessed the street tree community and resident perceptions of ecosystem service values in two coastal cities on the west coast of India that are under rapid change. We found that mean street tree density is low in both cities, and corresponds to perceptions of recent change in tree cover (−28% in Kochi, −11% in Panjim). The street tree community in both cities were dominated by ornamental avenue trees such as Albizia saman and Peltophorum pterocarpum, but native coastal species like Cocos nucifera, Terminalia catappa and Thespesia populnea were also common. Despite recent urban growth, residents in both cities reported low value of trees for food, fodder and medicine, but high value for regulating services like shade and water. Moreover, we found strong evidence for aesthetic and cultural values of trees in both cities. Our study establishes critical baselines for biophilic planning in these small urban centers towards urban sustainability in India.

Climate-limited vegetation change in the conterminous United States of America.

The effects of climate change on vegetation composition and distribution are evident in different ecosystems around the world. Although some climate-derived alterations on vegetation are expected to result in changes in lifeform fractional cover, disentangling the direct effects of climate change from different non-climate factors, such as land-use change, is challenging. By applying "Liebig's law of the minimum" in a geospatial context, we determined the climate-limited potential for tree, shrub, herbaceous, and non-vegetation fractional cover change for the conterminous United States and compared these potential rates to observed change rates for the period 1986 to 2018. We found that 10% of the land area of the conterminous United States appears to have climate limitations on the change in fractional cover, with a high proportion of these sites located in arid and semiarid ecosystems in the Southwest part of the country. The rates of change in lifeform fractional cover for the remaining area of the country are likely limited by non-climate factors such as the disturbance regime, land management, land-use history, soil conditions, and species interactions and adaptations.

Reassessing the role of urban green space in air pollution control

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

Trade-off of ecosystem productivity and water use related to afforestation in southcentral USA under climate change

The increase of tree canopy cover due to woody plant encroachment and tree plantations modifies both carbon and water dynamics. The tradeoffs between ecosystem net primary productivity (NPP) and water use with increasing tree cover in different climate conditions, particularly under future climate scenarios, are not well understood. Within the climate transition zone of the southern Great Plains, USA, we used the Soil and Water Assessment Tool+ (SWAT+) to investigate the combined impacts of increasing tree cover and climate change on carbon and water dynamics in three watersheds representing semiarid, subhumid, and humid climates. Model simulations incorporated two land use modifications (Baseline: existing tree cover; Forest +: increasing evergreen tree cover), in conjunction with two climate change projections (the RCP45 and the RCP85), spanning two time periods (historic: 1991–2020; future: 2070–2099). With climate change, the subhumid and humid watersheds exhibited a greater increase in evapotranspiration (ET) and a corresponding reduction in runoff compared to the semi-arid watershed, while the semi-arid and subhumid watersheds encountered pronounced losses in water availability for streams (>200 mm/year) due to increasing tree cover and climate change. With every 1 % increase in tree cover, both NPP and water use efficiency were projected to increase in all three watersheds under both climate change scenarios, with the subhumid watershed demonstrating the largest increases (>0.16 Mg/ha/year and 170 %, respectively). Increasing tree cover within grasslands, either through woody plant expansion or afforestation, boosts ecosystem NPP, particularly in subhumid regions. Nevertheless, this comes with a notable decrease in water resources, a concern made worse by future climate change. While afforestation offers the potential for greater NPP, it also brings heightened water scarcity concerns, highlighting the importance of tailoring carbon sequestration strategies within specific regions to mitigate unintended repercussions on water availability.

Historical changes in tree and impervious surface cover following urban renewal in a small postindustrial city.

Changes in tree cover and impervious surfaces have been observed across many cities in the United States over the past 70 years. Many municipalities are implementing tree planting programs in efforts to increase tree cover. A detailed understanding of historical changes in land cover can inform urban forest management. I applied a convolutional neural network image segmentation approach to historical aerial imagery to delineate changes in land cover in 1957, 1974, and 2017 in Utica, New York, a small, postindustrial city. The model predicted tree, pavement, and building land cover in each year with overall accuracies ranging from 82-87%. From 1957 to 2017, tree cover declined in many areas and impervious surface cover (buildings and pavement) increased. Tree cover gains largely occurred in uninhabited, natural areas; whereas, the greatest declines in tree coverage occurred in many residential areas following the start of the urban renewal efforts in 1957. Current tree planting efforts targeted at homeowners could drive disparities in future tree cover since several areas of Utica with low tree have a high proportion of renter occupied homes and a low median household income. Convolutional Neural Network approaches for image segmentation of aerial imagery are a helpful tool in understanding patterns in changes in tree and impervious surfaces. A better understanding of the legacies of historical policies and neighborhood-scale changes in land cover can assist in highlighting priorities for urban forest management and justice-oriented urban forestry approaches to urban tree planting.

Fire, Rain and CO2: Potential Drivers of Tropical Savanna Vegetation Change, with Implications for Carbon Crediting

A global trend of increasing tree cover in savannas has been observed and ascribed to a range of possible causes, including CO2 levels, changing rainfall and fire frequency. We tested these explanations in the Australian tropical savanna, taking 96 savanna ‘cool burning’ projects from Australia’s emissions offset scheme as case studies. We obtained readings of tree cover and explanatory variables from published remote sensing or spatial data sources. These were analysed using time-series linear regression to obtain coefficients for the influence of severe fire occurrence, annual rainfall and prior percentage tree cover. Although statistically significant coefficients for the key variables were found in only half (severe fire) or one quarter (rainfall) of the individual project models, when comparing all the model coefficients across the rainfall gradient, ecologically coherent explanations emerge. No residual trend was observed, suggesting rising CO2 levels have not influenced tree cover over the study period. Our approach models tree cover change by separating ecological drivers from human-controlled factors such as fire management. This is an essential design feature of national emissions inventories and emissions offsets programs, where crediting must be additional to the expected baseline, and arise from human activity.

Conservation policies and management in the Ukrainian Emerald Network have maintained reforestation rate despite the war

The Russian-Ukrainian War, ongoing since 2014, impacts an area containing Emerald Network environmental-protection sites created through the implementation of the Bern Convention on the Conservation of European Wildlife and Natural Habitats. Here we explore the impact of this conflict on institutional links supporting environmental sustainability and conservation efforts. Using satellite data, we analyzed tree cover changes in the Luhansk region’s Emerald Network protected areas from 1996 to 2020. The results reveal that the implementation of Bern Convention conservation policies led to a shift from deforestation (−4% each) to reforestation (+8% and +10%) on both sides of the Emerald Network divided by the demarcation line in 2014. It also shows that despite the war, territories under Ukraine control after 2014 continued reforestation (+9%), while sites under Russian control experienced dramatic forest loss (−25%). These findings emphasize the significant consequences of warfare-induced separation of local institutions on conservation areas and underscore the positive impact of the Emerald Network establishment, both before and after the conflict’s onset.

Mapping and Understanding Changes in Tree Cover in Nepal: 1992 to 2016

Since the 1980s, Nepal, one of the poorest countries in the world, has gained worldwide recognition for its successful community forestry program. Researchers, however, have not previously documented the spatially explicit impacts of this forest transition because of the topographic effects, e.g., shading, clouds, snow, and ice, hindered remote-sensing imagery analysis. This multi-disciplinary research project used United States Geological Survey (USGS) Landsat 5, 7, and 8 surface reflected-correct imagery from 1988 to 2016 that were available in Google Earth Engine to map forest cover change across the country. We then used a RandomForest (machine learning method) and multilevel regression analyses to assess associations between changes in forest cover and physiographic and socio-economic variables. We found that between 1992 and 2016, forest cover in Nepal almost doubled. Among other variables, being a member of a community-forestry user group, and receiving remittance income from children who had migrated elsewhere to work had a positive impact on forest cover.

TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change

Abstract. Land cover changes have been proposed to play a significant role, alongside emission reductions, in achieving the temperature goals agreed upon under the Paris Agreement. Such changes carry both global implications, pertaining to the biogeochemical effects of land cover change and thus the global carbon budget, and regional or local implications, pertaining to the biogeophysical effects arising within the immediate area of land cover change. Biogeophysical effects of land cover change are of high relevance to national policy and decision makers, and accounting for them is essential for effective deployment of land cover practices that optimise between global and regional impacts. To this end, Earth system model (ESM) outputs that isolate the biogeophysical responses of climate to land cover changes are key in informing impact assessments and supporting scenario development exercises. However, generating multiple such ESM outputs in a manner that allows comprehensive exploration of all plausible land cover scenarios is computationally untenable. This study proposes a framework to explore in an agile manner the local biogeophysical responses of climate under customised tree cover change scenarios by means of a computationally inexpensive emulator, the Tree cover change clIMate Biophysical responses EmulatoR (TIMBER) v0.1. The emulator is novel in that it solely represents the biogeophysical responses of climate to tree cover changes, and it can be used as either a standalone device or as a supplement to existing climate model emulators that represent the climate responses from greenhouse gas (GHG) or global mean temperature (GMT) forcings. We start off by modelling local minimum, mean, and maximum surface temperature responses to tree cover changes by means of a month- and Earth system model (ESM)-specific generalised additive model (GAM) trained over the whole globe; 2 m air temperature responses are then diagnosed from the modelled minimum and maximum surface temperature responses using observationally derived relationships. Such a two-step procedure accounts for the different physical representations of surface temperature responses to tree cover changes under different ESMs whilst respecting a definition of 2 m air temperature that is more consistent across ESMs and with observational datasets. In exploring new tree cover change scenarios, we employ a parametric bootstrap sampling method to generate multiple possible temperature responses, such that the parametric uncertainty within the GAM is also quantified. The output of the final emulator is demonstrated for the Shared Socioeconomic Pathway (SSP) 1-2.6 and 3-7.0 scenarios. Relevant temperature responses are identified as those displaying a clear signal in relation to their surrounding parametric uncertainty, calculated as the signal-to-noise ratio between the sample set mean and sample set variability. The emulator framework developed in this study thus provides a first step towards bridging the information gap surrounding biogeophysical implications of land cover changes, allowing for smarter land use decision making.

The challenge of comparing pollen-based quantitative vegetation reconstructions with outputs from vegetation models – a European perspective

Abstract. We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene.