The role of vegetation structural diversity in regulating the microclimate of human-modified tropical ecosystems.

Vegetation regulates microclimate stability through biophysical mechanisms such as evaporation, transpiration and shading. Therefore, thermal conditions in tree-dominated habitats will frequently differ significantly from standardized free-air temperature measurements. The ability of forests to buffer temperatures nominates them as potential sanctuaries for tree species intolerant to the increasingly challenging thermal conditions established by climate change. Although many factors influencing thermal conditions beneath the vegetation cover have been ascertained, the role of three-dimensional vegetation structure in regulating the understory microclimate remains understudied. Recent advances in remote sensing technologies, such as terrestrial laser scanning, have allowed scientists to capture the three-dimensional structural heterogeneity of vegetation with a high level of accuracy. Here, we examined the relationships between vegetation structure parametrized from voxelized laser scanning point clouds, air and soil temperature ranges, as well as offsets between field-measured temperatures and gridded free-air temperature estimates in 17 sites in a tropical mountain ecosystem in Southeast Kenya. Structural diversity generally exerted a cooling effect on understory temperatures, but vertical diversity and stratification explained more variation in the understory air and soil temperature ranges (30%-40%) than canopy cover (27%), plant area index (24%) and average stand height (23%). We also observed that the combined effects of stratification, canopy cover and elevation explained more than half of the variation (53%) in understory air temperature ranges. Stratification's attenuating effect was consistent across different levels of elevation. Temperature offsets between field measurements and free-air estimates were predominantly controlled by elevation, but stratification and structural diversity were influential predictors of maximum and median temperature offsets. Moreover, stable understory temperatures were strongly associated with a large offset in daytime maximum temperatures, suggesting that structural diversity primarily contributes to thermal stability by cooling daytime maximum temperatures. Our findings shed light on the thermal influence of vertical vegetation structure and, in the context of tropical land-use change, suggest that decision-makers aiming to mitigate the thermal impacts of land conversion should prioritize management practices that preserve structural diversity by retaining uneven-aged trees and mixing plant species of varying sizes, e.g., silvopastoral, or agroforestry systems.

Satellite observed dryland greening in Asian endorheic basins: Drivers and implications to sustainable development.

A large portion of Central-Western Asia is made up of contiguous closed basins, collectively termed as the Asian Endorheic Basins (AEBs). As these retention basins are only being replenished by the intermittent and scarce rainfall, global warming coupled with ever-rising human demand for water is exerting unprecedented pressures on local water and ecological security. Recent studies revealed a persistent and widespread water storage decline across the AEBs, yet the response of dryland vegetation to this recent hydroclimatic trend and a spatially explicit partitioning of the impact into the hydroclimatic factors and human activities remain largely unknown. To fill in this knowledge gap, we conducted trend and partial correlation analysis of vegetation and hydroclimatic change from 2001 to 2021 using multi-satellite observations, including vegetation greenness, total water storage anomalies (TWSA) and meteorological data. Here we show that much of the AEB (65.53 %), encompassing Mongolia Plateau, Northwest China, Qinghai Tibet Plateau, and Western Asia (except the Arabian Peninsula), exhibited a significant greening trend over the past two decades. In arid AEB, precipitation dominated the vegetation productivity trend. Such a rainfall dominance gave way to TWSA dominance in the hyper-arid AEB. We further showed that the decoupling of rainfall and hyper-arid vegetation greening was largely due to a significant expansion (17.3 %) in irrigated cropland across the hyper-arid AEB. Given the extremely harsh environment in the AEB, our results therefore raised a significant concern on the ecological and societal sustainability in this region, where a mild increase in precipitation cannot catch up the rising evaporative demand and water consumption resulted from global warming and agriculture intensification.

Patterns of tropical forest understory temperatures.

Temperature is a fundamental driver of species distribution and ecosystem functioning. Yet, our knowledge of the microclimatic conditions experienced by organisms inside tropical forests remains limited. This is because ecological studies often rely on coarse-gridded temperature estimates representing the conditions at 2 m height in an open-air environment (i.e., macroclimate). In this study, we present a high-resolution pantropical estimate of near-ground (15 cm above the surface) temperatures inside forests. We quantify diurnal and seasonal variability, thus revealing both spatial and temporal microclimate patterns. We find that on average, understory near-ground temperatures are 1.6 °C cooler than the open-air temperatures. The diurnal temperature range is on average 1.7 °C lower inside the forests, in comparison to open-air conditions. More importantly, we demonstrate a substantial spatial variability in the microclimate characteristics of tropical forests. This variability is regulated by a combination of large-scale climate conditions, vegetation structure and topography, and hence could not be captured by existing macroclimate grids. Our results thus contribute to quantifying the actual thermal ranges experienced by organisms inside tropical forests and provide new insights into how these limits may be affected by climate change and ecosystem disturbances.

Edge effects on tree architecture exacerbate biomass loss of fragmented Amazonian forests.

Habitat fragmentation could potentially affect tree architecture and allometry. Here, we use ground surveys of terrestrial LiDAR in Central Amazonia to explore the influence of forest edge effects on tree architecture and allometry, as well as forest biomass, 40 years after fragmentation. We find that young trees colonising the forest fragments have thicker branches and architectural traits that optimise for light capture, which result in 50% more woody volume than their counterparts of similar stem size and height in the forest interior. However, we observe a disproportionately lower height in some large trees, leading to a 30% decline in their woody volume. Despite the substantial wood production of colonising trees, the lower height of some large trees has resulted in a net loss of 6.0 Mg ha-1 of aboveground biomass - representing 2.3% of the aboveground biomass of edge forests. Our findings indicate a strong influence of edge effects on tree architecture and allometry, and uncover an overlooked factor that likely exacerbates carbon losses in fragmented forests.

Bio-geophysical feedback to climate caused by the conversion of Amazon Forest to soybean plantations.

Over the past two decades, soybean cultivation has become one of the principal replacements for forests in the Brazilian Amazon. Previous studies showed that the conversion of forests into large-scale soybean farms has different effects on local and regional climate than other forms of land use, e.g., conversion to pasture. The bio-geophysical feedbacks that lead to changes in temperature and rainfall caused by the expansion of commodity crops is not fully understood, and this has implications for both modelling potential future climatic change and understanding its impact. Here we performed model simulations to characterize the feedback to climate caused by the replacement of Amazonian forests with soybean and pastures. Our results show that: when compared to deforestation caused by pastures, the conversion of forests into soybean plantations results in more pronounced changes in the atmospheric boundary layer. Because they are characterized by a period of the year with bare soil, soybean fields transmit more long-wave radiation to the atmosphere than pastures, leading to an increase in boundary layer average temperature by 2.4 K. Although soybean plantations tend to strengthen convective lifting, the decrease in boundary layer water vapor content plays a decisive role in reducing rainfall. Finally, we demonstrate that the climatic impacts associated with the replacement of forests by soybean is likely to be magnified with agricultural expansion along new frontiers in the northern and western regions of the Amazon basin due to a more pronounced reduction in water vapor content.

Forest fragmentation impacts the seasonality of Amazonian evergreen canopies.

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.

Large-scale commodity agriculture exacerbates the climatic impacts of Amazonian deforestation.

In the Amazon rainforest, land use following deforestation is diverse and dynamic. Mounting evidence indicates that the climatic impacts of forest loss can also vary considerably, depending on specific features of the affected areas. The size of the deforested patches, for instance, was shown to modulate the characteristics of local climatic impacts. Nonetheless, the influence of different types of land use and management strategies on the magnitude of local climatic changes remains uncertain. Here, we evaluated the impacts of large-scale commodity farming and rural settlements on surface temperature, rainfall patterns, and energy fluxes. Our results reveal that changes in land-atmosphere coupling are induced not only by deforestation size but also, by land use type and management patterns inside the deforested areas. We provide evidence that, in comparison with rural settlements, deforestation caused by large-scale commodity agriculture is more likely to reduce convective rainfall and increase land surface temperature. We demonstrate that these differences are mainly caused by a more intensive management of the land, resulting in significantly lower vegetation cover throughout the year, which reduces latent heat flux. Our findings indicate an urgent need for alternative agricultural practices, as well as forest restoration, for maintaining ecosystem processes and mitigating change in the local climates across the Amazon basin.

Climatic impacts of bushland to cropland conversion in Eastern Africa.

Bushlands (Acacia-Commiphora) constitute the largest and one of the most threatened ecosystems in East Africa. Although several studies have investigated the climatic impacts of land changes on local and global climate, the main focus has been on forest loss and the impacts of bushland clearing thus remain poorly understood. Measuring the impacts of bushland loss on local climate is challenging given that changes often occur at fragmented and small patches. Here, we apply high-resolution satellite imagery and land surface flux modeling approaches to unveil the impacts of bushland clearing on surface biophysical properties and its associated effects on surface energy balance and land surface temperature. Our results show that bushland clearing leads to an average reduction in evapotranspiration of 0.4 mm day-1. The changes in surface biophysical properties affected the surface energy balance components with different magnitude. The reduction in latent heat flux was stronger than other surface energy fluxes and resulted in an average net increase in daytime land surface temperature (LST) of up to 1.75 K. These results demonstrate the important impact of bushland-to-cropland conversion on the local climate, as they reveal increases in LST of a magnitude comparable to those caused by forest loss. This finding highlights the necessity of bushland conservation for regulating the land surface temperature in East Africa and, at the same time, warns of the climatic impacts of clearing bushlands for agriculture.

Climate drivers of the Amazon forest greening.

Our limited understanding of the climate controls on tropical forest seasonality is one of the biggest sources of uncertainty in modeling climate change impacts on terrestrial ecosystems. Combining leaf production, litterfall and climate observations from satellite and ground data in the Amazon forest, we show that seasonal variation in leaf production is largely triggered by climate signals, specifically, insolation increase (70.4% of the total area) and precipitation increase (29.6%). Increase of insolation drives leaf growth in the absence of water limitation. For these non-water-limited forests, the simultaneous leaf flush occurs in a sufficient proportion of the trees to be observed from space. While tropical cycles are generally defined in terms of dry or wet season, we show that for a large part of Amazonia the increase in insolation triggers the visible progress of leaf growth, just like during spring in temperate forests. The dependence of leaf growth initiation on climate seasonality may result in a higher sensitivity of these ecosystems to changes in climate than previously thought.

Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations.

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2= 0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤ r2≤ 0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.

Evaluating the impact of distance measures on deforestation simulations in the fluvial landscapes of amazonia.

Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility in our study area. The most accurate simulation is achieved when time distance to market center is used in association with distance to transport network and additional landscape variables. Although traditional Euclidean measures result in clearly lower simulation accuracy when used separately, the combination of two complementary Euclidean measures enhances simulation accuracy significantly. Our results highlight the need for site and context sensitive selection of accessibility variables. More sophisticated accessibility measures can potentially improve LUCC models' spatial accuracy, which often remains low.

Prospective changes in irrigation water requirements caused by agricultural expansion and climate changes in the eastern arc mountains of Kenya.

Water resources and land use are closely linked with each other and with regional climate, assembling a very complex system. The understanding of the interconnecting relations involved in this system is an essential step for elaborating public policies that can effectively lead to the sustainable use of water resources. In this study, an integrated modelling framework was assembled in order to investigate potential impacts of agricultural expansion and climate changes on Irrigation Water Requirements (IWR) in the Taita Hills, Kenya. The framework comprised a land use change simulation model, a reference evapotranspiration model and synthetic precipitation datasets generated through a Monte Carlo simulation. In order to generate plausible climate change scenarios, outputs from General Climate Models were used as reference to perturbing the Monte Carlo simulations. The results indicate that throughout the next 20 years the low availability of arable lands in the hills will drive agricultural expansion to areas with higher IWR in the foothills. If current trends persist, agricultural areas will occupy roughly 60% of the study area by 2030. This expansion will increase by approximately 40% the annual water volume necessary for irrigation. Climate change may slightly decrease crops' IWR in April and November by 2030, while in May a small increase will likely be observed. The integrated assessment of these environmental changes allowed a clear identification of priority regions for land use allocation policies and water resources management.