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Mapping the structure of Borneo's tropical forests across a degradation gradient

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  • Forest Research Centre
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... Forest canopy structure can be up-scaled from plots and mapped using remote sensing data (Hadi et al., 2017;Pfeifer et al., 2012;Pfeifer et al., 2016). For example, forest leaf area index, LAI, and fractional vegetation cover, FCover, measured in a forest landscape in Borneo showed mathematical relationships with satellite-derived spectral and texture information, which allowed mapping LAI and FCover for each pixel in the landscape (Pfeifer et al., 2016). ...
... Forest canopy structure can be up-scaled from plots and mapped using remote sensing data (Hadi et al., 2017;Pfeifer et al., 2012;Pfeifer et al., 2016). For example, forest leaf area index, LAI, and fractional vegetation cover, FCover, measured in a forest landscape in Borneo showed mathematical relationships with satellite-derived spectral and texture information, which allowed mapping LAI and FCover for each pixel in the landscape (Pfeifer et al., 2016). Forest canopies are also mechanistically linked to both temperature and ground vegetation productivity through their effects on radiation fluxes within forest stands (Deardorff, 1978). ...
... We computed two indices to obtain texture information for a given pixel and its neighbourhood for each of these three bands: MEAN and DISSIMILARITY. This was implemented on a grey-level co-occurrence matrix with a 90 degree shift and 64 grey-levels and a window size of 3 × 3 pixels for each band (Pfeifer et al., 2016). We also computed mean and standard deviation maps of NDVI using the focal function in the 'raster' package specifying a moving window size of 8 pixels (Hijmans, 2017). ...
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Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above-ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature ( Thermalground ) and ground vegetation greenness ( NDVIdown ) as potentially suitable metrics of habitat quality. Both have been linked to species demography and community structure in the literature. We test whether they can be measured consistently from the ground and whether they can be up-scaled indirectly using canopy structure maps (Leaf Area Index, LAI , and Fractional vegetation cover, FCover ) developed from Landsat remote sensing data. We measured Thermalground and NDVIdown across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both metrics decline significantly with increasing canopy closure and leaf area, implying a potential pathway for upscaling both metrics using canopy structure maps derived using earth observation. Specifically, our findings suggest that opening forest canopies by 20% or decreasing forest canopy LAI by one unit would result in increases of Thermalground by 1.2 °C across the range of observations studied. NDVIdown appears to decline by 0.1 in response to an increase in canopy LAI by 1 unit and declines nonlinearly with canopy closure. Accounting for micro-scale variation in temperature and resources is seen as essential to improve biodiversity impact predictions. Our study suggests that mapping ground surface temperature and ground vegetation greenness utilising remotely sensed canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, this approach will be constrained by the predictive capacity of models used to map field-derived forest canopy attributes. Furthermore, sampling efforts are needed to capture spatial and temporal variation in Thermalground within and across days and seasons to validate the transferability of our findings. Finally, whilst our approach shows that surface temperature and ground vegetation greenness might be suitable habitat quality metric used in biodiversity monitoring, the next step requires that we map demographic traits of species of different threat status onto maps of these metrics in landscapes differing in disturbance and management histories. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation at the landscape scale.
... The relative changes in PAI observed ( Figure 2) are over three times greater than those suggested by previous estimates of PAI across the degradation gradient at SAFE, estimated using 5-m resolution RapidEye imagery calibrated against PAI estimates from hemispherical photographs (Pfeifer et al., 2016). Pfeifer et al. (2016) suggest a more moderate decline of ~15% across the degradation gradient. ...
... The relative changes in PAI observed ( Figure 2) are over three times greater than those suggested by previous estimates of PAI across the degradation gradient at SAFE, estimated using 5-m resolution RapidEye imagery calibrated against PAI estimates from hemispherical photographs (Pfeifer et al., 2016). Pfeifer et al. (2016) suggest a more moderate decline of ~15% across the degradation gradient. This result may reflect the saturation of PAI estimates in hemispherical photographs in tropical forests (Vincent et al., 2017), reducing the apparent impact of degradation on PAI. ...
Article
Forest degradation through logging is pervasive throughout the world’s tropical forests, leading to changes in the three‐dimensional canopy structure that have profound consequences for wildlife, microclimate and ecosystem functioning. Quantifying these structural changes is fundamental to understanding the impact of degradation, but is challenging in dense, structurally complex forest canopies. We exploit discrete‐return airborne LiDAR surveys across a gradient of logging intensity in Sabah, Malaysian Borneo, and assess how selective logging has affected canopy structure (Plant Area Index, PAI, and its vertical distribution within the canopy). LiDAR products compared well to independent, analogue models of canopy structure produced from detailed ground‐based inventories undertaken in forest plots, demonstrating the potential for airborne LiDAR to quantify the structural impacts of forest degradation at landscape scale, even in some of the world’s tallest and most structurally complex tropical forests. PAI estimates across the plot network exhibited a strong linear relationship with stem basal area (R2 = 0.95). After at least 11‐14 years of recovery, PAI was ~28% lower in moderately logged plots and ~52% lower in heavily logged plots than in old‐growth forest plots. These reductions in PAI are associated with near‐complete lack of trees >30‐m tall, which has not been fully compensated for by increasing plant area lower in the canopy. This structural change drives a marked reduction in the diversity of canopy environments, with the deep, dark understory conditions characteristic of old‐growth forests far less prevalent in logged sites, with full canopy recovery likely to take decades. Synthesis and Applications. Effective management and restoration of tropical forests requires detailed monitoring of the forest and its environment. We demonstrate that airborne LiDAR can effectively map the canopy architecture of the complex tropical forests of Borneo, capturing the three‐dimensional impact of degradation on canopy structure at landscape scales, therefore facilitating efforts to restore and conserve these ecosystems.
... Above-ground biomass and carbon stock, integrating other structure parameters such as tree or stem diameter [86], are mainly used as indicators of forest degradation (Table 2). To model biomass, regressions between field measurements (e.g., above-ground biomass, volume, basal area, number of stems), at inventory plot or tree scale, and metrics from remote sensing data (aerial LiDAR [87], optical [88], radar [89]) are performed. In Borneo, above-ground biomass was calculated (Root mean square error (RMSE) = 20.3 ...
... High-resolution optical data can detect canopy gaps up to a certain size [79,80], especially when working at sub-pixel scale (Table 3) or with multitemporal data. They can help to measure biomass [88] and species composition [98]. However, image resolution limits the accuracy of the results. ...
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In the context of the climate and biodiversity crisis facing our planet, tropical forests playing a key role in global carbon flux and containing over half of Earth's species are important to preserve. They are today threatened by deforestation but also by forest degradation, which is more difficult to study. Here, we performed a systematic review of studies on moist tropical forest degradation using remote sensing and fitting indicators of forest resilience to perturbations. Geographical repartition, spatial extent and temporal evolution were analyzed. Indicators of compositional, structural and regeneration criteria were noted as well as remote sensing indices and metrics used. Tropical moist forest degradation is not extensively studied especially in the Congo basin and in southeast Asia. Forest structure (i.e., canopy gaps, fragmentation and biomass) is the most widely and easily measured criteria with remote sensing, while composition and regeneration are more difficult to characterize. Mixing LiDAR/Radar and optical data shows good potential as well as very high-resolution satellite data. The awaited GEDI and BIOMASS satellites data will fill the actual gap to a large extent and provide accurate structural information. LiDAR and unmanned aerial vehicles (UAVs) form a good bridge between field and satellite data. While the performance of the LiDAR is no longer to be demonstrated, particular attention should be brought to the UAV that shows great potential and could be more easily used by local communities and stakeholders.
... We sampled salvage logged forests in the SAFE experimental area in the North East of the Kalabakan Forest Reserve (4°42′ N, 117°34′ E; 72 km 2 ). This area has been subject to multiple rounds of unrestricted commercial logging for all large timber trees (diameter at breast height > 40cm) between 1978 and the early 2000's (Reynolds, Payne, Sinun, Mosigil, & Walsh, 2011), leaving a structurally heterogeneous forest with few large trees and a dense understory (mean aboveground tree biomass: 42.4 t/ha, Pfeifer et al., 2016). These areas are intersected by numerous logging roads and are dominated by less productive vines, pioneer tree species, and invasive vegetation (Pfeifer et al., 2016). ...
... This area has been subject to multiple rounds of unrestricted commercial logging for all large timber trees (diameter at breast height > 40cm) between 1978 and the early 2000's (Reynolds, Payne, Sinun, Mosigil, & Walsh, 2011), leaving a structurally heterogeneous forest with few large trees and a dense understory (mean aboveground tree biomass: 42.4 t/ha, Pfeifer et al., 2016). These areas are intersected by numerous logging roads and are dominated by less productive vines, pioneer tree species, and invasive vegetation (Pfeifer et al., 2016). The altered forest structure and lower canopy cover affect microclimate, as degraded forests tend to exhibit lower humidity and warmer daytime temperatures (Hardwick et al., 2015;Luskin & Potts, 2011). ...
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Beyond broad‐scale investigations of species diversity and abundance, there is little information on how land conversion in the tropics is affecting the behavior and demographics of surviving species. To fill these knowledge gaps, we explored the effects of land‐use change on the ecologically important and threatened bearded pig (Sus barbatus) over seven years in Borneo. Random placement of camera traps across a land‐use gradient of primary forest, logged forest, and oil palm plantations (32,542 trap nights) resulted in 2,303 independent capture events. Land‐use was associated with changes in the age structure and activity patterns of photographed individuals, alongside large changes in abundance shown previously. The proportion of adults recorded declined from 92% in primary forests to 76% in logged forests, and 67% in plantations, likely indicating increased fecundity in secondary forests. Activity level (capture rate) did not vary, but activity patterns changed markedly, from diurnal in primary forests, crepuscular in logged forests, to nocturnal in plantations. These changes corresponded with avoidance of diurnal human activity and may also protect bearded pigs from increased thermal stress in warmer degraded forests. The percentage of adult captures that were groups rather than individuals increased five‐fold from primary forests (4%) to logged forests (20%), possibly due to increased mating or in response to perceived threats from indirect human disturbance. We recommend further investigation of the demographic and behavioral effects of land‐use change on keystone species as altered population structure, activity patterns, and social behavior may have knock‐on effects for entire ecosystems.
... March and July 2016. The forests at SAFE have undergone two cycles of selective logging, with an estimated aboveground biomass removal of 302.8 t/ha 1 (Pfeifer et al., 2016), and are crossed by a dense network of logging roads (Ewers et al., 2011). We examined four logging roads and three logged forest control sites (Table S1). ...
... Third, as nocturnal endotherms with great capacity to thermoregulate (Yasuda et al., 2000), rats may be less sensitive than other taxa, such as frogs or leaf litter invertebrates, to the altered microclimatic conditions at road edges (Delgado, Morales, Arroyo & Fernandez-Palacios, 2013;Wells et al., 2007). Last, our study area has been repeatedly heavily logged, which created a heterogeneous, patchy forest structure with many canopy gaps throughout the landscape; thus, road edges are not unique or unusual habitats for rats (Pfeifer et al., 2016). ...
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en Selective logging is driving the proliferation of roads throughout tropical rain forests, particularly narrow, unpaved logging roads. However, little is known about the extent of road edge effects or their influence on the movements of tropical understory animal species. Here, we used forest rats to address the following questions: (a) Does the occupancy of rats differ from road edges to forest interior within logged forests? (b) Do roads inhibit the movements of rats within these forests? We established trapping grids along a road edge‐to‐forest interior gradient at four roads and in three control sites within a logged forest in Sabah, Malaysia. To quantify the probability of road crossing, rats were captured, translocated across a road, and then recaptured on subsequent nights. We caught 216 individuals of eight species on 3,024 trap nights. Rat occupancy did not differ across the gradient from road edge to interior, and 48 percent of the 105 translocated individuals crossed the roads and were recaptured. This proportion was not significantly different from that of rats returning in control sites (38% of 60 individuals), suggesting that small roads were not barriers to rat movements within logged forests. Subadults were significantly more likely to return from translocation than adults in both road and control sites. Our results are encouraging for the ecology of small mammal communities in heavily logged forests, because small logging roads do not restrict the movements of rats and therefore are unlikely to create an edge effect or influence habitat selection. Abstrak ms Pembalakan terpilih menggalakkan percambahan jalan di sepanjang hutan hujan tropika, terutamanya sempit, jalan pembalakan tidak berturap. Walaubagaimanapun, sedikit‐sebanyak diketahui tentang sejauh mana kesan kawasan tepi jalan, atau pengaruh mereka terhadap pergerakan spesies haiwan lapisan lantai hutan tropika. Di sini, kami menggunakan tikus hutan sebagai kajian untuk menjawab soalan‐soalan berikut: (a) Adakah kehadiran tikus berbeza dari kawasan tepi jalan berbanding dalam hutan balak? (b) Adakah jalan menghalang pergerakan tikus dalam hutan ini? Kami menubuhkan grid penangkapan di sepanjang kecerunan dalaman ke arah hutan di empat jalan raya dan di tiga tempat kawalan di dalam hutan tebal di Sabah, Malaysia. Tikus yang ditangkap dipindahkan di seberang jalan dan ditangkap semula pada malam berikutnya untuk mengukur kebarangkalian lintasan jalan. Secara keseluruhannya, kami menangkap 216 individu dari lapan spesies dalam 3,024 perangkap malam. Kehadiran tikus tidak berbeza di seluruh kecerunan tepi ke arah jalan, dan 48 peratus daripada 105 orang yang pindah dari balik jalan. Peratusan ini tidak jauh berbeza dengan nisbah tikus yang kembali dari tapak kawalan (38% daripada 60 individu), menunjukkan bahawa jalan‐jalan kecil tidak berfungsi sebagai halangan untuk pergerakan di dalam hutan balak. Sub‐dewasa adalah jauh lebih berkemungkinan untuk kembali dari translokasi daripada orang dewasa di kedua‐dua jalan dan tapak kawalan. Hasil kami mewakili berita baik untuk ekologi komuniti mamalia kecil di hutan yang banyak bertebaran: jalan pembalakan kecil tidak mungkin menghasilkan kesan kelebihan atau mempengaruhi pemilihan habitat, dan tidak mengehadkan pergerakan tikus.
... Seedling monitoring was carried out in 84 selected tree plots in sites ranging from 1028 down to 0.22 Mg ha −1 of AGB, reflecting a gradient from primary through to heavily logged forest (Pfeifer et al 2016). A seedling plot of 5×5 m was established within each of the tree plots in June 2012. ...
... We first constructed a global model which included as predictors two measures of forest structural conditions likely to have causal effects on seedling dynamics: (1) aboveground live tree biomass (AGB) which reflects the historical logging intensity and overall forest quality, and (2) canopy leaf area index (LAI), i.e. total leaf surface area projected on the local horizontal datum, which relates closely to microclimatic conditions, especially daily maximum temperature and daily minimum humidity (Hardwick et al 2015). Both were measured at the vegetation plot level across the SAFE landscape, with AGB showing greater heterogeneity within unlogged forests compared to the canopy measure (Pfeifer et al 2016). As the latter resulted in a strong positively skewed distribution of the variable we applied log10-transformation on AGB values. ...
Article
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Logged tropical forests represent a major opportunity for preserving biodiversity and sequestering carbon, playing a large role in meeting global forest restoration targets. Left alone, these ecosystems have been expected to undergo natural regeneration and succession towards old growth forests, but extreme drought events may challenge this process. While old growth forests possess a certain level of resilience, we lack understanding as to how logging may affect forest responses to drought. This study examines the drought–logging interaction in seedling dynamics within a landscape of logged and unlogged forests in Sabah Malaysia, based on 73 plots monitored before and after the 2015–16 El Niño drought. Drought increased seedling mortality in all forests, but the magnitude of this impact was modulated by logging intensity, with forests with lower canopy leaf area index and above-ground biomass experiencing greater drought induced mortality. Moreover, community traits in more heavily logged forests shifted towards being more ruderal after drought, suggesting that the trajectory of forest succession had been reversed. These results indicate that with reoccurring strong droughts under a changing climate, logged forests that have had over half of their biomass removed may suffer permanently arrested succession. Targeted management interventions may therefore be necessary to lift the vulnerable forests above the biomass threshold.
... The improved performance may be related to their combination of spatial and spectral information, which is consistent with the findings of many previous studies [6,12,27,44,52]. Gu et al. [16], Pfeifer et al. [68], and Pu and Cheng [28] demonstrated that by including texture information into spectral data models, the models' predictive capacity could be improved, especially for the canopy structure at the stand level, which is mainly because the information associated with spectral and textural signatures is complementary in the estimation of forest parameters [59]. In addition, texture was credible in detecting varying forest canopy structural characteristics and is efficient in addressing saturation problems that are associated with vegetation indices when mapping CC, especially in dense canopies [26]. ...
... Young forests with low CC values can lead to enclosures and replanting. Moreover, quantitative maps of forest resources can be used for decision-making by managers and for monitoring a variety of forest inventory parameters, such as forest area changes, biomass accumulation, and health conditions [5,44,68]. ...
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The forest canopy is the medium for energy and mass exchange between forest ecosystems and the atmosphere. Remote sensing techniques are more efficient and appropriate for estimating forest canopy cover (CC) than traditional methods, especially at large scales. In this study, we evaluated the CC of black locust plantations on the Loess Plateau using random forest (RF) regression models. The models were established using the relationships between digital hemispherical photograph (DHP) field data and variables that were calculated from satellite images. Three types of variables were calculated from the satellite data: spectral variables calculated from a multispectral image, textural variables calculated from a panchromatic image (Tpan) with a 15 × 15 window size, and textural variables calculated from spectral variables (TB+VIs) with a 9 × 9 window size. We compared different mtry and ntree values to find the most suitable parameters for the RF models. The results indicated that the RF model of spectral variables explained 57% (root mean square error (RMSE) = 0.06) of the variability in the field CC data. The soil-adjusted vegetation index (SAVI) and enhanced vegetation index (EVI) were more important than other spectral variables. The RF model of Tpan obtained higher accuracy (R2 = 0.69, RMSE = 0.05) than the spectral variables, and the grey level co-occurrence matrix-based texture measure—Correlation (COR) was the most important variable for Tpan. The most accurate model was obtained from the TB+VIs (R2 = 0.79, RMSE = 0.05), which combined spectral and textural information, thus providing a significant improvement in estimating CC. This model provided an effective approach for detecting the CC of black locust plantations on the Loess Plateau.
... In addition to the AGB storage, other forest structure parameters such as canopy cover and tree height also vary across a degradation gradient (Mehta, Sullivan, Walter, Krishnaswamy, & DeGloria, 2008;Pfeifer et al., 2016). Gap fractions in the forest canopy (open gaps in forest canopy not covered by foliage) vary considerably between primary forests compared and forests that have been logged (Pinagé, Matricardi, Osako, & Gomes, 2014). ...
... Forest regeneration and associated increases in forest cover facilitate the rapid increase in carbon stocks (Lohbeck, 2016). The decline in canopy gap fractions (and consequently an increase in canopy cover) is a sign of regeneration in tropical forests (Espirito-Santo et al., 2006;Filer, Keenan, Allen, & Mcalpine, 2009 (Pfeifer et al., 2016). ...
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Community forests are known to play an important role in preserving forests in Cambodia, a country that has seen rapid deforestation in recent decades. The detailed evaluation of the ability of community-protected forests to retain forest cover and prevent degradation in Cambodia will help to guide future conservation management. In this study, a combination of remotely sensing data was used to compare the temporal variation in forest structure for six different community forests located in the Phnom Kulen National Park (PKNP) in Cambodia and to assess how these dynamics vary between community-protected forests and a wider study area. Medium-resolution Landsat, ALOS PALSAR data, and high-resolution LiDAR data were used to study the spatial distribution of forest degradation patterns and their impacts on above-ground biomass (AGB) changes. Analysis of the remotely sensing data acquired at different spatial resolutions revealed that between 2012 and 2015, the community forests had higher forest cover persistence and lower rates of forest cover loss compared to the entire study area. Furthermore, they faced lower encroachment from cashew plantations compared to the wider landscape. Four of the six community forests showed a recovery in canopy gap fractions and subsequently, an increase in the AGB stock. The levels of degradation decreased in forests that had an increase in AGB values. However, all community forests experienced an increase in understory damage as a result of selective tree removal, and the community forests with the sharpest increase in understory damage experienced AGB losses. This is the first time multitemporal high-resolution LiDAR data have been used to analyze the impact of human-induced forest degradation on forest structure and AGB. The findings of this work indicate that while community-protected forests can improve conservation outcomes to some extent, more interventions are needed to curb the illegal selective logging of valuable timber trees. K E Y W O R D S AGB stock, ALOS PALSAR, LiDAR, protected areas
... Most of the area has been subject to at least two rounds of selective logging between the 1980s and the 2000s, a landscape history typical of Sabah and the wider South-East Asian region (Johns 1997;Putz et al. 2012). Most large, commercially valuable timber trees were felled and removed, with an estimated cumulative 302.8 t ha −1 of aboveground tree biomass removed (Pfeifer et al. 2016), leaving continuous, spatially heterogeneous forest which is among the most heavily logged forest in the tropics (Burivalova et al. 2014). Our sites were not logged during the period of this study from 2011 to 2016, however some piecemeal salvage logging occurred within the wider landscape during this timeframe. ...
... Thirdly, even if logging damage at the landscape level is not sufficient to completely disrupt mast fruiting-driven changes to population dynamics, logging disturbance is highly spatially heterogeneous, and the forest at SAFE forms a patchwork of highly variable quality and tree cover (Pfeifer et al. 2015(Pfeifer et al. , 2016. Mast fruiting is already a spatially heterogenous process (Ghazoul 2016), and logging undoubtedly further localizes this by leaving small "islands" of mature dipterocarp trees. ...
Article
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Understanding temporal change and long-term persistence of species and communities is vital if we are to accurately assess the relative values of human-modified habitats for biodiversity. Despite a large literature and emerging consensus demonstrating a high conservation value of selectively logged tropical rainforests, few studies have taken a long-term perspective. We resampled small mammals (≤ 1 kg) in a heavily logged landscape in Sabah, Borneo between 2011 and 2016 to investigate temporal patterns of species-level changes in population density. We found that small mammal population density in heavily logged forest was highly variable among years, consistent with patterns previously observed in unlogged forest, and uncovered evidence suggesting that one species is potentially declining towards local extinction. Across nine species, population densities varied almost sevenfold during our 6-year study period, highlighting the extremely dynamic nature of small mammal communities in this ecosystem. Strictly terrestrial murid species tended to exhibit strong temporal dynamics, whereas semi-arboreal foraging species such as treeshrews had more stable dynamics. We found no relationships between population density and fruit/seed mass, and therefore no evidence that our patterns represent responses to inter-annual mast fruiting of the dominant canopy dipterocarp trees. This may be due to the removal of most of the canopy during logging, and hence the dipterocarp seed resource, although it possibly also reflects spatiotemporal limitations of our data. Our results underline the importance of understanding long-term variability in animal communities before developing conservation and management recommendations for human-altered ecosystems.
... Landsat imagery comprising red, near-infrared and the two short-wave infrared (SWIR) spectral bands (30 m pixels; [42]). We used the raw reflectance data and derived two texture indices (the dissimilarity and average of the reflectance data, calculated using a moving window) for each of the four bands, following [43], giving a total of 12 potential predictors. A machine learning algorithm (random forest models) with 10-fold cross-validation and three repeats linked the satellite data to field-derived measurements of AGB. ...
... Miombo woodlands were the dominant forest type in the study landscape. Normalised difference vegetation index (NDVI) correlates with ground vegetation biomass and productivity under low to medium vegetation density conditions such as the Miombo woodlands [33]. NDVI change, therefore, provides an appropriate proxy measure of forest recovery. ...
Article
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Certified community forests combine local governance with forest certification and aim to serve multiple objectives including forest protection, restoration, human wellbeing and equitable governance. However, the causal pathways by which they impact these objectives remain poorly understood. The ability of protected area impact evaluations to identify complex pathways is limited by a narrow focus on top-down theoretical, quantitative perspectives and inadequate consideration of local context. We used a novel mixed-methods research design that integrates the perspectives of multiple actors to develop a generalized conceptual model of the causal pathways for certified community forests. We tested the model using a combination of statistical matching, structural equation modelling and qualitative analyses for an agroforestry landscape in Tanzania. We found certified community forests positively impacted human wellbeing, equitable governance and forest restoration. Equitable governance had the largest impact on wellbeing, followed by crop yield and forest resource availability. Timber revenues varied widely between villages and the average effect of financial benefits did not impact wellbeing due to the immature stage of the certified timber market. We identified positive interactions and trade-offs between conservation and agriculture. Our findings suggest that no simple solution exists for meeting multiple objectives. However, developing understanding of the pathways linking social and conservation outcomes can help identify opportunities to promote synergies and mitigate negative impacts to reconcile competing objectives. This article is part of the theme issue ‘Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration’.
... Landsat imagery comprising red, near-infrared and the two short-wave infrared (SWIR) spectral bands (30 m pixels; [42]). We used the raw reflectance data and derived two texture indices (the dissimilarity and average of the reflectance data, calculated using a moving window) for each of the four bands, following [43], giving a total of 12 potential predictors. A machine learning algorithm (random forest models) with 10-fold cross-validation and three repeats linked the satellite data to field-derived measurements of AGB. ...
Article
Effective restoration planning tools are needed to mitigate global carbon and biodiversity crises. Published spatial assessments of restoration potential are often at large scales or coarse resolutions inappropriate for local action. Using a Tanzanian case study, we introduce a systematic approach to inform landscape restoration planning, estimating spatial variation in cost-effectiveness, based on restoration method, logistics, biomass modelling and uncertainty mapping. We found potential for biomass recovery across 77.7% of a 53 000 km ² region, but with some natural spatial discontinuity in moist forest biomass, that was previously assigned to human causes. Most areas with biomass deficit (80.5%) were restorable through passive or assisted natural regeneration. However, cumulative biomass gains from planting outweighed initially high implementation costs meaning that, where applicable, this method yielded greater long-term returns on investment. Accounting for ecological, funding and other uncertainty, the top 25% consistently cost-effective sites were within protected areas and/or moderately degraded moist forest and savanna. Agro-ecological mosaics had high biomass deficit but little cost-effective restoration potential. Socio-economic research will be needed to inform action towards environmental and human development goals in these areas. Our results highlight value in long-term landscape restoration investments and separate treatment of savannas and forests. Furthermore, they contradict previously asserted low restoration potential in East Africa, emphasizing the importance of our regional approach for identifying restoration opportunities across the tropics. This article is part of the theme issue ‘Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration’.
... Its presence also serves as a proxy for various plant functions and characteristics [28]. The fractional cover can inform various analyses involving a wide range of ecological processes from flora to fauna dynamics [29], forest growth [30], food web structure [31], vegetation studies [32], land management practices [33], hydrology [34], dynamics of soil carbon [33], disaster risk [35] and drought monitoring [36]. Additionally, these quantities capture the biophysical consequences of several disturbances caused by natural and human drivers [37,38]. ...
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Forests are threatened globally by deforestation. Forest restoration at the landscape scale can reduce these threats. Ground-based and remote sensing inventories are needed to assess restoration success. Fractional canopy cover estimated from forest algorithms can be used to monitor forest loss, growth, and health via remote sensing. Various studies on the fractional cover of forest have been published. However, none has yet conducted a bibliometric analysis. Bibliometrics provide a detailed examination of a topic, pointing academics to new research possibilities. To the best of the authors’ knowledge, this is the first bibliometric study screening publications to assess the incidence of studies of the fractional cover of forests in Web of Science (WoS) and Scopus databases. This research analyses WoS and Scopus publications on the fractional cover of forest dating from 1984 to 2021. The current study uses the Bibliometrix R-package for citation metrics and analysis. The first paper on the fractional cover of forest was published in 1984 and annual publication numbers have risen since 2002. USA and China were the most active countries in the study of fractional cover of forests. A total of 955 documents from 69 countries with multiple languages were retrieved. Vegetation, forestry, and remote sensing were the most discussed topics. Findings suggest more studies on the fractional cover of forests algorithms should be conducted in tropical forest from developing countries.
... Similarly, trees that were planted in regular spacing, such as timber or fruit plantations can be identified and delineated from high-resolution satellite imagery. Here previous studies have used single or multiple satellite observations to map the world's intact forest landscapes (Potapov et al., 2008), small-scale disturbances caused by selective logging (DeVries et al., 2015) or regional gradients of different management (Pfeifer et al., 2016). Yet, until recently, no global remote-sensing derived maps of forest management types existed, with earlier attempts instead relying on several environmental predictors, little independent training or validation data (Schulze et al., 2019), or only being available at coarse scales (Curtis et al., 2018). ...
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Aim Many vertebrate species globally are dependent on forests, most of which require active protection to safeguard global biodiversity. Forests, however, are increasingly either being disturbed, planted or managed in the form of timber or food plantations. Because of a lack of spatial data, forest management has commonly been ignored in previous conservation assessments. Location Global. Methods We combine a new global map of forest management types created solely from remote sensing imagery with spatially explicit information on the distribution of forest‐associated vertebrate species and protected areas globally. Using Bayesian logistic regressions, we explore whether the amount of forested habitat available to a species as well as information on species‐specific threats can explain differences in IUCN extinction risk categories. Results We show that disturbed and human‐managed forests dominate the distributional ranges of most forest‐associated species. Species considered as non‐threatened had on average larger amounts of non‐managed forests within their range. A greater amount of planted forests did not decrease the probability of species being threatened by extinction. Even more worrying, protected areas are increasingly being established in areas dominated by disturbed forests. Conclusion Our results imply that species extinction risk and habitat assessments might have been overly optimistic with forest management practices being largely ignored so far. With forest restoration being at the centre of climate and conservation policies in this decade, we caution that policy makers should explicitly consider forest management in global and regional assessments.
... Badania łączące klasyczne metody fitosocjologiczne z nowoczesnymi metodami analiz obrazowych prowadzone są w bardzo zróżnicowanych ekosystemach i strefach klimatyczno--roślinnych: od torfowisk w płn. Finlandii (Räsänen i Virtanen, 2019) i alaskańskiej tundry (Langford et al., 2016), aż po lasy tropikalne na Borneo (Pfeifer et al., 2016) i tajwańskie lasy mgliste (Schulz et al., 2017). Najrzadziej takie podejście metodyczne wykorzystywane jest w ekosystemach zurbanizowanych -miastach i strefach podmiejskich (Feilhauer et al., 2017). ...
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The aim of this work was to review the latest literature in terms of the use of phytosociological relevés (vegetation plots) in research on the natural environment. The systematic review included 321 articles published in 2010‑2021 in the most renowned journals (indexed in the Web of Science Core Collection with a score ≥100 according to the 2021 list of journals of the Poland’s Ministry of Education and Science). The research questions were: in which fields of science and practice, for what purposes and on what spatial scales the phytosociological relevés are currently used. After initial review, the articles were divided into 10 thematic groups: 1) classification of plant communities, 2) methodological studies, 3) relationship between vegetation and other elements of the environment, 4) occurrence of invasive plant species, 5) indicative role of vegetation, 6) plant communities as habitats for animals, 7) human footprint on vegetation, 8) long-term vegetation changes, 9) combining phytosociological methods with remote sensing methods, 10) social studies. The results showed that phytosociological relevés, as the method to investigate vegetation developed in the first decades of the 20th century, are still widely used in many regions of the world. The most numerous thematic group comprised articles that show how habitat conditions impact the distribution and diversity of plant species and their communities, while the least numerous – studies combining natural and social research. The vast majority of research was dedicated to environmental problems, although social and economic aspects were also present. These were both theoretical and methodological works, as well as detailed studies, which resulted in the formation of recommendations and practical guidelines for nature protection or spatial planning. Recently, relevés have been rarely used solely to distinguish and characterise plant communities, as originally intended by those who invented this method. However, thanks to modern statistical and computer tools, more and more attempts are being made to create automatic classifications with the use of artificial intelligence, e.g. neural networks. The geographic scope was usually restricted to one country (local and regional – 241 articles) or to two or more bordering countries (47). Continental (19) and global (7) studies are less common and studies within Europe prevail. It is because the discussed method was developed and is best known in Europe (Franco-Swiss Phytosociological School), and its dissemination throughout the world is only an evidence of its universality and efficiency. The recent larger-scale studies became possible mainly due to the development of transnational vegetation databases, e.g. the widely utilised European Vegetation Database – EVA.
... Plot code (as in the ForestPlots database) and field name, location and characteristics of the eleven study plots For more details of the logging history see Fisher et al. (2011), Pfeifer et al. (2016, Reynolds et al. (2011), and Struebig et al. (2013). The exact location of the plots was chosen randomly, and the logged plots contain old skid trails, log landing sites and logging roads. ...
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Soil respiration is the largest carbon efflux from the terrestrial ecosystem to the atmosphere, and selective logging influences soil respiration via changes in abiotic (temperature, moisture) and biotic (biomass, productivity, quantity and quality of necromass inputs) drivers. Logged forests are a predominant feature of the tropical forest landscape, their area exceeding that of intact forest. We quantified both total and component (root, mycorrhiza, litter, and soil organic matter, SOM) soil respiration in logged (n=5) and old‐growth (n=6) forest plots in Malaysian Borneo, a region which is a global hotspot for emission from forest degradation. We constructed a detailed below‐ground carbon budget including organic carbon inputs into the system via litterfall and root turnover. Total soil respiration was significantly higher in logged forests than in old‐growth forests (14.3 ± 0.23 and 12.7 ± 0.60 Mg C ha‐1 year‐1, respectively, p=0.037). This was mainly due to the higher SOM respiration in logged forests (55% ± 3.1% of the total respiration in logged forests vs. 50% ± 3.0% in old‐growth forests). In old‐growth forests, annual SOM respiration was equal to the organic carbon inputs into the soil (difference between SOM respiration and inputs 0.18 Mg C ha‐1 year‐1, with 90% confidence intervals of ‐0.41 and 0.74 Mg C ha‐1 year‐1), indicating that the system is in equilibrium, while in logged forests SOM respiration exceeded the inputs by 4.2 Mg C ha‐1 year‐1 (90% CI of 3.6 and 4.9 Mg C ha‐1 year‐1), indicating that the soil is losing carbon. These results contribute towards understanding the impact of logging on below‐ground carbon dynamics, which is one of the key uncertainties in estimating emissions from forest degradation. This study demonstrates how significant perturbation of the below‐ground carbon balance, and consequent net soil carbon emissions, can persist for decades after a logging event in tropical forests.
... In pristine forests, plant canopies intercept solar radiation before it reaches the ground and leaf transpiration helps keep the air moist, buffering the environment below and creating cool, dark and humid conditions that are fairly homogenous (De Frenne et al., 2019;Hardwick et al., 2015;Pfeifer et al., 2019). Logging removes large trees, thereby reducing the density of leaves, and creating gaps in the canopy (Pfeifer et al., , 2016, leading to locally hotter and drier environments . Conversion of forest to agricultural use, such as oil palm plantation, further amplifies this effect. ...
Article
Logging and habitat conversion create hotter microclimates in tropical forest landscapes, representing a powerful form of localised anthropogenic climate change. It is widely believed that these emergent conditions are responsible for driving changes in communities of organisms found in modified tropical forests, although the empirical evidence base for this is lacking. Here we investigated how interactions between the physiological traits of genera and the environmental temperatures they experience lead to functional and compositional changes in communities of ants, a key organism in tropical forest ecosystems. We found that the abundance and activity of ant genera along a gradient of forest disturbance in Sabah, Malaysian Borneo, was defined by an interaction between their thermal tolerance (CTmax) and environmental temperature. In more disturbed, warmer habitats, genera with high CTmax had increased relative abundance and functional activity, and those with low CTmax had decreased relative abundance and functional activity. This interaction determined abundance changes between primary and logged forest that differed in daily maximum temperature by a modest 1.1 °C, and strengthened as the change in microclimate increased with disturbance. Between habitats that differed by 5.6 °C (primary forest to oil palm) and 4.5 °C (logged forest to oil palm), a 1 °C difference in CTmax among genera led to a 23 % and 16 % change in relative abundance, and a 22 % and 17 % difference in functional activity. CTmax was negatively correlated with body size and trophic position, with ants becoming significantly smaller and less predatory as microclimate temperatures increased. Our results provide evidence to support the widely held, but never directly tested, assumption that physiological tolerances underpin the influence of disturbance‐induced microclimate change on the abundance and function of invertebrates in tropical landscapes.
... We estimated True LAI from hemispherical photographs (HP) following processing methods outlined by Pfeifer et al. (2014) and Pfeifer et al. (2016). In each sample unit, 20 upward looking images (10 m apart) were taken, using a Nikon D3100 DSLR camera equipped with a Nikon Fish-eye Nikkor 10.5 mm lens leveled at 1.30 m height aligned with the magnetic north. ...
Article
The Atlantic Forest, a global biodiversity hotspot, has changed dramatically due to land use pressures causing deforestation, degradation, and forest fragmentation. A major challenge is to understand and potentially mitigate the consequences of these changes, for the capacity of forests to deliver essential environmental services to rural areas. Here, we focus on unraveling the mechanisms underpinning spatial variation in forest leaf area index. Forest leaf area index can be used as an environmental indicator that controls key forest functions underlying environmental services and is also expected to respond to land use change. Specifically, we use Structural Equation Modelling to determine the direct and indirect pathways that link environmental drivers to canopy leaf area index (LAI) variation across forest types in the Atlantic Forest in Southern Brazil. We sampled 240 sample units (each 4000 m²), from a systematic and permanent forest inventory set which covers the State of Santa Catarina in a 10 km × 10 km grid, using hemispherical photographs. Environmental variables were extracted for each sample unit, including climatic and topographic data as well as indicators of anthropogenic pressure. Our results showed that forest types differed in their leaf area index (but not all of them) and that forest canopies show complex responses to environmental drivers, encompassing direct and indirect pathways. A major pathway was the positive effect of ‘Distance to city’ on the ‘Percentage of cropland in the matrix’. This led to a decline in the distance of the sample unit to the forest edge, indirectly reducing LAI, presumably because of elevated tree mortality at the forest edge. ‘Terrain steepness’ and ‘Rainfall in the driest month’ independently affected the ‘Percentage of cropland in the matrix’ and the ‘Distance to forest edge’. Halting forest fragmentation and increasing fragment size by landscape planning will mitigate these anthropogenic LAI declines. This can be achieved with a combination of legal and market mechanisms, like enforcement of the Brazilian Forest Act regulation on buffer zones around water bodies and steep slopes, landscape planning, and payment for environmental services to compensate the farmers for maintaining forest cover on otherwise productive land.
... In Gabon, where overall logging intensities averaged 8.11 m 3 ha −1 and 0.82 trees ha −1 , five of the ten 1 ha plots established in the logging area yielded no timber, and two of those were also not traversed by skid trails (Medjibe et al., 2011). Reported levels of spatial variance are noticeably lower in studies in which plots were set up postlogging to represent a range of logging intensities (e.g., Ewers and Banks-Leite, 2013;Riutta et al., 2018), but can nevertheless be substantial, especially when sampled at sub-hectare scales (e.g., Pfeifer et al., 2016;Senior et al., 2017). ...
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The selective logging that characterizes most timber extraction operations in the tropics leaves large patches of logging blocks (i. e., areas allocated for harvesting) intact, with no direct impacts of the harvest. For example, in the ~10,000 ha we sampled in 48 forest management enterprises in Africa (Gabon, Republic of Congo, and the Democratic Republic of Congo), Indonesia, Suriname, and Mexico, an average of 57% (range 22–97%) of the area in logging blocks was not directly affected by timber harvests. The proportion of intact forest within logging blocks decreased very slightly with increases in harvest intensity in the accessed portion of the logging blocks (9–86 m3 ha−1) but decreased strongly with harvest intensity in entire logging blocks (0.3–48.2 m3 ha−1). More forest was left intact in areas farther from roads, on slopes >40%, and within 25 m of perennial streams, but the effect sizes of each of these variables was small (~8%). It is less clear how much of the intact forest left after one harvest will remain intact through the next. Conservation benefits without reductions in timber yields will derive from better management planning so that sensitive and ecologically critical areas, such as steep slopes and riparian buffers, constitute permanent reserves of intact forest in selectively logged landscapes in the tropics.
... Results from the present study are in line with those reported by Khai et al. (2016), which was conducted on tropical selective logging in Myanmar and showed that a high felling intensity causes forest degradation. Studies showing various relationships between logging intensity and its impacts on biodiversity and environment (França et al., 2017;Nurochman et al., 2018;Pfeifer et al., 2016;Rosin et al., 2017;Rozak et al., 2018) are available. The present study shows that although there are differences in the extent and type of damage in West Sumatra and East Kalimantan, in general, the company has attempted to implement RIL by reducing felling intensity, implementing a logging plan by conducting forest inventories prior to the logging process, tree mapping, and planning skid roads. ...
Article
Selective logging in natural forests in Indonesia involves logging trees with a diameter at breast height (dbh) of >50 cm and leads to damage to residual stands. This research was conducted on forest concession areas in West Sumatra and Central Kalimantan to analyze residual stand damage. The type and percentage of damage were calculated at both locations by evaluating 10 plots of 1 ha at each site. All trees with a dbh of >20 cm were measured and classified before and after felling and skidding. The stand density and felling intensity were analyzed to determine the factors affecting the amount of damage. Results indicated six types of damages: broken stem, crown injury, fallen or uprooted trees, leaning, bark and stem injuries, and buttress injury. All six types of damages were found in Central Kalimantan, whereas five types of damages (except buttress injury) were found in West Sumatra. On comparing pre- and post-logging conditions, a higher percentage of damage was identified in Central Kalimantan (27.8%) than in West Sumatra (22.4%). The percentage of tree damage increased in line with the increasing felling intensity at both locations. It was concluded that a higher tree density and felling intensity resulted in a greater residual stand damage both in Central Kalimantan and West Sumatra. Keywords: Felling intensity, Logging, Stand damage, Tropical forest, Indonesia
... We sampled forest-plantation edges in two locations: the experimental landscape at the Stability of Altered Forest Ecosystems (SAFE) project, a landscape-scale deforestation experiment (Ewers et al., 2011;N4 • 41 ′ 58 ′′ , E117 • 37 ′ 40 ′′ ), and a second area of forest ∼23 km west-southwest (N4 • 38 ′ 26 ′′ , E117 • 26 ′ 09 ′′ ). At both edge locations, the forest comprised >1,000 ha tracts of heavily-logged forest, with continuous forest cover extending for ≥1 km behind the edge, and featured a structure typical of logged forest in the region, with few large trees and a dense understorey of vines and herbaceous plants (Pfeifer et al., 2016). Our forest study areas directly adjoined oil palm plantations (managed by Benta Wawasan Sdn Bhd), which were planted between 2004 and 2013, and therefore ranged from young but established plantations (c. 4 years old) to mature plantations (c. 13 years old). ...
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In the face of rapid tropical agricultural expansion, preservation of tropical forest remnants is crucially important. Forest remnants often about the edges of new or established plantations, so landscape-level conservation requires an understanding of the balance between ecosystem services and disservices provided by forest, including potential crop yield reductions caused by species such as rodents, an important pest group in oil palm plantations. However, very little is known about the scale of any spillover of native species which inhabit forest into adjacent agricultural areas. We examined the distribution and behaviour of small mammals across an edge separating logged tropical forest and oil palm plantations in Sabah, Malaysian Borneo, using a dual approach. We used a trapping grid to reveal patterns of species relative abundance across the forest-plantation edge, and tracked individuals of forest species using a spool-and-line. We uncovered little evidence that the native forest small mammal community crosses the edge and uses the plantation, although two invasive small mammal species were found across the whole edge gradient. Of 10 forest species detected, we found only the adaptable murid Maxomys whiteheadi in the plantation, where it persisted at low abundances across all sampling points, including in the plantation interior control site. This pattern is more consistent with persistence of M. whiteheadi throughout plantations than with spill-over from forest fragments. On the forest side, observed species richness of small mammals increased with distance into the interior, suggesting a negative edge effect may exist within forest remnants. Of 23 successfully tracked small mammals, only one M. whiteheadi crossed the forest-plantation edge, and overall, this species was significantly repelled from crossing into plantation habitat. Our results suggest that spillover of native small mammals contributes little to oil palm damage close to forest-plantation edges, but that oil palm negatively impacts small mammal populations within adjacent forest remnants.
... The area has been selectively logged for the first time in the mid 1970s, followed by one to three rounds of logging between 1990 and 2008. The cumulative extracted biomass in the area ranged from 46 to 54 Mg C ha −1 , and the total biomass loss, including collateral damage, increased post-logging mortality and abandonment of some of the felled stems was estimated to be 94-128 Mg C ha −1 (Struebig et al., 2013;Pfeifer et al., 2016;Riutta et al., 2018). Mean extraction volumes are estimated to be 150-179 m 3 ha −1 , compared to 152 m 3 ha −1 across all of Sabah (Fisher et al., 2011). ...
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Microclimate within forests influences ecosystem fluxes and demographic rates. Anthropogenic disturbances, such as selective logging can affect within-forest microclimate through effects on forest structure, leading to indirect effects on forests beyond the immediate impact of logging. However, the scope and predictability of these effects remains poorly understood. Here we use a microclimate thermal proxy (sensitive to radiative, convective, and conductive heat fluxes) measured at the forest floor in three 1-ha forest plots spanning a logging intensity gradient in Malaysian Borneo. We show (1) that thermal proxy ranges and spatiotemporal heterogeneity are doubled between old growth and heavily logged forests, with extremes often exceeding 45°C, (2) that nearby weather station air temperatures provide estimates of maximum thermal proxy values that are biased down by 5–10°C, and (3) that lower canopy density, higher canopy height, and higher biomass removal are associated with higher maximum temperatures. Thus, logged forests are less buffered from regional climate change than old growth forests, and experience much higher microclimate extremes and heterogeneity. Better predicting the linkages between regional climate and its effects on within-forest microclimate will be critical for understanding the wide range of conditions experienced within tropical forests.
... Panels (c and d) show these same patterns for maximum temperature saturating thereafter (Figure 2). As a result, we found that even though logging had a profound impact on the height and density of forest canopies (Figure 3; Hardwick et al., 2015;Pfeifer et al., 2016), only under intense logging pressure or following the conversion of forests to oil-palm plantations was microclimate strongly affected. This is broadly consistent with recent work showing that logged forests in the tropics tend to be largely thermally buffered and do not differ substantially in their microclimate to old-growth stands (Senior, Hill, Benedick, et al., 2017;Senior, Hill, González del Pliego, et al., 2017). ...
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Local‐scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Consequently, understanding what drives variation in forest microclimate is critical to forecasting ecosystem responses to global change, particularly in the tropics where many species already operate close to their thermal limits and rapid land‐use transformation is profoundly altering local environments. Yet our ability to characterize forest microclimate at ecologically meaningful scales remains limited, as understorey conditions cannot be directly measured from outside the canopy. To address this challenge, we established a network of microclimate sensors across a land‐use intensity gradient spanning from old‐growth forests to oil‐palm plantations in Borneo. We then combined these observations with high‐resolution airborne laser scanning data to characterize how topography and canopy structure shape variation in microclimate both locally and across the landscape. In the processes, we generated high‐resolution microclimate surfaces spanning over 350 km2, which we used to explore the potential impacts of habitat degradation on forest regeneration under both current and future climate scenarios. We found that topography and vegetation structure were strong predictors of local microclimate, with elevation and terrain curvature primarily constraining daily mean temperatures and vapour pressure deficit (VPD), whereas canopy height had a clear dampening effect on microclimate extremes. This buffering effect was particularly pronounced on wind‐exposed slopes but tended to saturate once canopy height exceeded 20 m—suggesting that despite intensive logging, secondary forests remain largely thermally buffered. Nonetheless, at a landscape‐scale microclimate was highly heterogeneous, with maximum daily temperatures ranging between 24.2 and 37.2°C and VPD spanning two orders of magnitude. Based on this, we estimate that by the end of the century forest regeneration could be hampered in degraded secondary forests that characterize much of Borneo's lowlands if temperatures continue to rise following projected trends. Written Summary:Local‐scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Yet our ability to capture microclimate at scales relevant for management and conservation remains inherently limited. By combining a network of microclimate sensors with high‐resolution airborne laser scanning data acquired across a land‐use intensity gradient in Borneo, here we characterise how topography and canopy structure shape variation in microclimate in human‐modified tropical landscapes. We estimate that by 2080 forest regeneration could be hampered in large tracts of degraded secondary forest that make up much of Borneo’s lowlands.
... Since the cessation of logging, the LF2 and LF3 catchments have been regenerating with young stands and low-lying understorey with different degree of forest cover at present (Ewers et al., 2011;Struebig et al., 2013). The LF2 is characterised by a more extensive and taller tree cover due to fewer rounds of harvesting ig. 1. Location and land-use of study area Produced using map layers from the SAFE Project repository (SAFE Project, n.d.) and information from existing publication Ewers et al., 2011;Luke et al., 2017;Pfeifer et al., 2016) via the ArcMap GIS software version 10.4. and a longer recovery period whereas the LF3 has a mainly low vegetation cover with few canopy trees. ...
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Full Text: <https://authors.elsevier.com/a/1XqAQ_WGi1y8q> Although erosional impacts of rainforest logging are well established, changes in hydrological dynamics have been less explored especially in the post-logging recovery phase following repeat-logging cycles and mature phase of oil palm plantation cycles. This study addresses this gap by comparing hydrological characteristics of five catchments in a steep land area of Sabah, Malaysian Borneo on a gradient of disturbance and recovery – twice-logged forest, 22 years recovery (LF2); multiple-logged forest, 8 years recovery (LF3); mature oil palm, 20 years old (OP); and two primary forests (PF and VJR) as controls. Each catchment was instrumented with water depth (converted to discharge), conductivity, temperature, and turbidity sensors, and a raingauge connected to a solar-powered datalogger recording data at 5-minute intervals from November 2011 to August 2013. Data were analysed via the flow-duration curve (FDC) supplemented by the runoff coefficient (RR) and coefficient of variation in discharge (QVAR) for aggregated characteristics, as well as via a combination of the Dunn's test and multiple-regression at the storm event scale for focused hydrological dynamics. Results show that OP is characterised by a relatively low RR (0.357) but with high responsiveness during storm events and very low baseflow (38.4% of total discharge). Discharge in the LF3 (RR = 0.796) is always the highest while having an intermediate level of responsiveness. LF2 with longer-term recovery shown a reduction in terms of discharge (RR = 0.640). Being the benchmark, the undisturbed forest (PF) has the most buffered storm response with the highest baseflow (67.9% of total discharge). Stormflow and baseflow are anomalously high and low respectively in the near-primary VJR catchment, but this probably reflects the shallow soils and short-stature rainforest associated with its igneous and metamorphic lithology. From a management aspect, although hydrological recovery is more advanced in the 22 years than in the 8-years post-logging catchment, full recovery is yet to be achieved and might be hastened by enrichment planting of the degraded forest. The low baseflow and flashy nature of the mature oil palm have major implications for downstream water supply in ENSO periods and flooding in La Nina periods. Steep lands in the humid tropics are best avoided from any form of landscape disturbance.
... However, unlike deforestation, forest degradation from logging and wood extraction is hard to detect, and this is a key problem in carbon emission accounting (Carlson et al 2013). Despite efforts to map forest logging with moderate-and high-resolution remote sensing data (Siegert et al 2001, Asner et al 2005, Souza et al 2005, Ellis et al 2016, Pfeifer et al 2016, the detection and mapping of tropical forests impacted by logging or other human activities still remain active areas of research. The problem of detecting degraded forests is particularly difficult in the case of Kalimantan because of the complexity of the terrain causing larger heterogeneity in forest structure. ...
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The forests of Kalimantan are under severe pressure from extensive land use activities dominated by logging, palm oil plantations, and peatland fires. To implement the forest moratorium for mitigating greenhouse gas emissions, Indonesia's government requires information on the carbon stored in forests, including intact, degraded, secondary, and peat swamp forests. We developed a hybrid approach of producing a wall-to-wall map of the aboveground biomass (AGB) of intact and degraded forests of Kalimantan at 1 ha grid cells by combining field inventory plots, airborne lidar samples, and satellite radar and optical imagery. More than 110 000 ha of lidar data were acquired to systematically capture variations of forest structure and more than 104 field plots to develop lidar-biomass models. The lidar measurements were converted into biomass using models developed for 66 439 ha of drylands and 44 250 ha of wetland forests. By combining the AGB map with the national land cover map, we found that 22.3 Mha (10⁶ ha) of forest remain on drylands ranging in biomass from 357.2 ± 12.3 Mgha⁻¹ in relatively intact forests to 134.2 ± 6.1 Mgha⁻¹ in severely degraded forests. The remaining peat swamp forests are heterogeneous in coverage and degradation level, extending over 3.62 Mha and having an average AGB of 211.8 ± 12.7 Mgha⁻¹. Emission factors calculated from aboveground biomass only suggest that the carbon storage potential of more than 15 Mha of degraded and secondary dryland forests will be about 1.1 PgC.
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PurposeThe purpose of our study was to investigate soil chemical properties, soil microbial biomass and soil enzyme activities in a gradient of forest degradation in logged over tropical rain forests, Borneo. We hypothesized that the changes of above-ground vegetation could affect soil organic matter, which further influenced soil microbial biomass and enzyme activities.MethodsA total of 35 forest plots with varying magnitude of logging influences were investigated for vegetation composition and soil parameters. The 35 plots were sorted based on tree genus compositions by a Principal Co-ordinates analysis (PCoA) and PCoA axis-1 values represented a gradient of forest degradation. Soil physicochemical properties, microbial biomass carbon and nitrogen, and four extracellular enzymes were measured.ResultsLinear regression analyses showed that soil organic carbon and total nitrogen concentrations decreased with decreasing PCoA axis-1 values (i.e., increasing magnitude of degradation), while soil pH values increased. Soil microbial biomass carbon and nitrogen, and the activities of four extracellular enzymes all decreased with decreasing PCoA axis-1 values. The activities of four enzymes were correlated with soil microbial biomass. Structural equation modeling showed that soil organic carbon explained the greatest variation of soil microbial biomass.Conclusion Above-ground forest degradation directly affects soil organic matter, which then affects soil microbial biomass. The combined actions of reduced microbial biomass and reduced soil organic matter as the substrate for the enzymes decrease microbial enzyme activities during the process of forest degradation. These changes may in turn feed back to the regrowth or succession of degraded forest ecosystems.
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Several key international policy frameworks involve forests, including the Paris Agreement on Climate Change and the Convention on Biological Diversity (CBD). However, rules and guidelines that treat forest types equally regardless of their ecosystem integrity and risk profiles in terms of forest and carbon loss limit policy effectiveness and can facilitate forest degradation. Here we assess the potential for using a framework of ecosystem integrity to guide policy goals. We review the theory and present a conceptual framework, compare elements of integrity between primary and human-modified forests, and discuss the policy and management implications. We find that primary forests consistently have higher levels of ecosystem integrity and lower risk profiles than human-modified forests. This underscores the need to protect primary forests, develop consistent large-scale data products to identify high-integrity forests, and operationalize a framework of ecosystem integrity. Doing so will optimize long-term carbon storage and the provision of other ecosystem services, and can help guide evolving forest policy at the nexus of the biodiversity and climate crises.
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Forest disturbances can reduce the potential of ecosystems to provide resources and services. Despite the urgent need to understand the effects of logging on tropical ecosystems, the quantification of disturbances arising from selective logging remains a challenge. Here, we used canopy-three-dimensional information retrieved from Terrestrial Laser Scanner (TLS) measurements to investigate the impacts of logging on key structural traits relevant to forest functioning. We addressed the following questions: 1) Which canopy structural traits were mostly affected by logging? 2) Can remotely-sensed canopy structural traits be used to quantify forest disturbances? Fourteen canopy structural traits were applied as input to machine learning models, which were trained to quantify the intensity of logging disturbance. The plots were located in Malaysian Borneo, over a gradient of logging intensity, ranging from forest not recently disturbed by logging, to forest at the early stage of recovery following logging. Our results showed that using the Random Forest regression approach, the Plant Area Index (PAI) between 0 m − 5 m aboveground, Relative Height at 50 %, and metrics describing plant allocation in the middle-higher canopy layer were the strongest predictors of disturbance. In particular, PAI between 35 m and 40 m explained 12 % to 19 % of the structural variability between plots, followed by the relative height at 50 %, (10.5 % − 18.6 %), and the foliage height diversity (7.5 % − 16.9 %). The approach presented in this study allowed a spatially explicitly characterization of disturbances, providing a novel approach for quantifying and monitoring the integrity of tropical forests. Our results indicate that canopy structural traits can provide a robust indication of disturbances, with strong potential to be applied at regional or global scales. The data used in this study are openly available and we encourage other researchers to use them as a benchmark data set to test larger scale approaches based on satellite and airborne platforms.
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The rapid conversion of tropical rainforests into monoculture plantations of rubber (Hevea brasiliensis) in Southeast Asia (SEA) necessitates understanding of rubber tree physiology under local climatic conditions. Frequent fog immersion in the montane regions of SEA may affect the water and carbon budgets of the rubber trees and the plantation ecosystems. We studied the effect of fog on various plant physiological parameters in a mature rubber plantation in southwest China over 3 years. During the study period, an average of 141 fog events occurred every year, and the majority occurred during the dry season, when the temperature was relatively low. In addition to the low temperature, fog events were also associated with low vapor pressure deficit, atmospheric water potential, relative humidity and frequent wet-canopy conditions. We divided the dry season into cool dry (November-February) and hot dry (March-April) seasons and classified days into foggy (FG) and non-foggy (non-FG) days. During the FG days of the cool dry season, the physiological activities of the rubber trees were suppressed where carbon assimilation and evapotranspiration showed reductions of 4% and 15%, respectively, compared to the cool dry non-FG days. Importantly, the unequal declines in carbon assimilation and evapotranspiration led to enhanced crop water productivity (WPc) on cool dry FG days but insignificant WPc values were found between FG and non-FG days of the hot dry season. Our results suggest that, by regulating plant physiology, fog events during the cool dry season significantly reduce water demand and alleviate water stress for the trees through improved WPc.
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Changes in land-use and the associated shifts in environmental conditions can have large effects on the transmission and emergence of mosquito-borne disease. Mosquito-borne disease are particularly sensitive to these changes because mosquito growth, reproduction, survival and susceptibility to infection are all thermally sensitive traits, and land use change dramatically alters local microclimate. Predicting disease transmission under environmental change is increasingly critical for targeting mosquito-borne disease control and for identifying hotspots of disease emergence. Mechanistic models offer a powerful tool for improving these predictions. However, these approaches are limited by the quality and scale of temperature data and the thermal response curves that underlie predictions. Here, we used fine-scale temperature monitoring and a combination of empirical, laboratory and temperature-dependent estimates to estimate the vectorial capacity of Aedes albopictus mosquitoes across a tropical forest–oil palm plantation conversion gradient in Malaysian Borneo. We found that fine-scale differences in temperature between logged forest and oil palm plantation sites were not sufficient to produce differences in temperature-dependent demographic trait estimates using published thermal performance curves. However, when measured under field conditions a key parameter, adult abundance, differed significantly between land-use types, resulting in estimates of vectorial capacity that were 1.5 times higher in plantations than in forests. The prediction that oil palm plantations would support mosquito populations with higher vectorial capacity was robust to uncertainties in our adult survival estimates. These results provide a mechanistic basis for understanding the effects of forest conversion to agriculture on mosquito-borne disease risk, and a framework for interpreting emergent relationships between land-use and disease transmission. As the burden of Ae . albopictus -vectored diseases, such as dengue virus, increases globally and rising demand for palm oil products drives continued expansion of plantations, these findings have important implications for conservation, land management and public health policy at the global scale.
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Habitat fragmentation has become one of the largest areas of research in conservation biology. Empirical studies into habitat fragmentation impacts typically measure ecological responses to metrics describing fragmentation processes, e.g. ‘distance to the nearest forest edge’, ‘forest fragment area’, and ‘landscape habitat amount’. However, these studies often fail to sample across representative ranges of fragmentation metrics characterising the study region. They therefore lack the data to account for correlation among multiple fragmentation metrics and for spatial autocorrelation among sample sites, which reduces the strength of derived predictive models. Here, we draw on approaches used in the mining and soil science industry to develop standardised and repeatable protocols for designing optimised sampling schemes of biodiversity in fragmented landscapes that meet three criteria: the distance between sample sites is maximised to reduce spatial autocorrelation, the full range of values of the metrics of interest are sampled, and the confounding effects of correlated metrics are minimised. We show that our computational methods can optimise the placement of sample sites in fragmented landscapes to minimise, and in some cases to entirely avoid, over‐ or under‐sampling of fragmentation metrics. Our method is flexible enough to cater for any continuous (e.g. maps of percentage tree cover) or categorical (e.g. habitat and land use types) fragmentation metric, and to simultaneously handle combinations of multiple fragmentation metrics and habitat types. We implement our methods as open‐source code which includes options to mask invalid or inaccessible regions, update designs to adapt to unforeseen constraints in the field, and suggest optimal numbers of sample sites for given design criteria. Using a case study landscape, we demonstrate how the approach improves on manually generated sampling designs. We also show that the methods are flexible enough to be applied to landscape studies beyond the field of habitat fragmentation. We introduce our package as a novel research tool that is able to streamline the experimental design process for biodiversity sampling and monitoring at landscape scales, leading to improved data quality and representativeness.
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Abstract Acoustic indices derived from environmental soundscape recordings are being used to monitor ecosystem health and vocal animal biodiversity. Soundscape data can quickly become very expensive and difficult to manage, so data compression or temporal down‐sampling are sometimes employed to reduce data storage and transmission costs. These parameters vary widely between experiments, with the consequences of this variation remaining mostly unknown. We analyse field recordings from North‐Eastern Borneo across a gradient of historical land use. We quantify the impact of experimental parameters (MP3 compression, recording length and temporal subsetting) on soundscape descriptors (Analytical Indices and a convolutional neural net derived AudioSet Fingerprint). Both descriptor types were tested for their robustness to parameter alteration and their usability in a soundscape classification task. We find that compression and recording length both drive considerable variation in calculated index values. However, we find that the effects of this variation and temporal subsetting on the performance of classification models is minor: performance is much more strongly determined by acoustic index choice, with Audioset fingerprinting offering substantially greater (12%–16%) levels of classifier accuracy, precision and recall. We advise using the AudioSet Fingerprint in soundscape analysis, finding superior and consistent performance even on small pools of data. If data storage is a bottleneck to a study, we recommend Variable Bit Rate encoded compression (quality = 0) to reduce file size to 23% file size without affecting most Analytical Index values. The AudioSet Fingerprint can be compressed further to a Constant Bit Rate encoding of 64 kb/s (8% file size) without any detectable effect. These recommendations allow the efficient use of restricted data storage whilst permitting comparability of results between different studies.
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Community forests (CFs) aim to improve human wellbeing and conservation effectiveness, though their performance remains contested. A recent innovation in protected area (PA) governance is to combine CFs with forest certification. We assess (1) the impact of certified CFs on wellbeing and conservation effectiveness ; (2) gender inequality and elite capture; (3) interaction effects with neighboring national PAs. We used a novel approach that integrates field data consisting of locally identified indicators representative of multidimensional wellbeing, with remotely sensed data on conservation effectiveness and statistical matching to improve causal inference. We found that CFs positively impacted wellbeing, conservation effectiveness, and reduced gender inequality, though they did not reduce elite capture. We also detected positive interaction effects between certified CFs and neighboring national PAs. Our findings suggest that locating contrasting local and national PA governance approaches next to each other may help to maximize wellbeing and conservation benefits within complex multiuse landscapes.
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Background: Understanding forest dynamics after logging is essential to define forest management cycles and intensities. In secondary forest, especially in the Atlantic Forest Domain, these studies are still scarce. Monitoring of the canopy structure after tree harvesting can be performed by hemispherical photographs, where canopy opening is commonly analyzed. This study evaluated changes in canopy opening four years after tree harvesting in a secondary Atlantic Rainforest in southern Brazil. We used hemispherical photographs to determine the Canopy Openness (CO), Leaf Area Index (LAI), and Diffuse Fraction of Photosynthetically Active Absorbed Radiation (FAPARdif) in eleven permanent plots. Results: We found that harvesting resulted in a momentary increase in canopy opening and light availability in the understory. Four years after harvesting, CO, LAI and FAPARdif recovered or even exceeded the original values of the forest. We observed a significant correlation between CO and number of trees harvested with DBH > 30 cm. Weak correlations were found between these canopy related variables and the logging intensity. Conclusion: In conclusion, we recognized that changes of CO, LAI and FAPARdif after timber harvesting presented short duration. This indicates that the applied logging intensities, 21.8 to 51.1% of the total basal area, did not exceed the resilience of the forest canopy and it’s recovering four years later. However, additional studies should be carried out to observe vegetation dynamics, such as species composition, vertical structure, productivity and community stability, in order to improve management schemes of secondary stands in the Atlantic Forest.
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The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Niño Southern Oscillation event to measure canopy height growth across 3,300 ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40 m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent.
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Significance Forest restoration has become a global conservation priority, particularly in the tropics where a significant proportion of remaining forest ecosystems are degraded. To achieve ambitious restoration targets via limited conservation funds, areas that will deliver the greatest biodiversity value must be prioritized. Here, we combine airborne laser scanning with an extensive camera trap dataset to target conservation and restoration across a degraded logged forest gradient. We demonstrate the importance of accounting for three-dimensional habitat structure when defining forest suitability and restoration potential for mammals. Consequently, we provide a robust quantitative framework to prioritize degraded forest restoration based on biodiversity considerations.
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The response of small understory trees to long‐term drought is vital in determining the future composition, carbon stocks and dynamics of tropical forests. Long‐term drought is, however, also likely to expose understory trees to increased light availability driven by drought‐induced mortality. Relatively little is known about the potential for understory trees to adjust their physiology to both decreasing water and increasing light availability. We analysed data on maximum photosynthetic capacity (J max, V cmax), leaf respiration (R leaf), leaf mass per area (LMA), leaf thickness and leaf nitrogen and phosphorus concentrations from 66 small trees across 12 common genera at the world’s longest running tropical rainfall exclusion experiment and compared responses to those from 61 surviving canopy trees. Small trees increased J max, V cmax, R leaf and LMA (71%, 29%, 32%, 15% respectively) in response to the drought treatment, but leaf thickness and leaf nutrient concentrations did not change. Small trees were significantly more responsive than large canopy trees to the drought treatment, suggesting greater phenotypic plasticity and resilience to prolonged drought, although differences among taxa were observed. Our results highlight that small tropical trees have greater capacity to respond to ecosystem level changes and have the potential to regenerate resilient forests following future droughts. This article is protected by copyright. All rights reserved.
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Biodiversity-rich tropical ultramafic areas are currently being impacted by land clearing and particularly by mine activities. The reclamation of ultramafic degraded areas requires a knowledge of pioneer plant species. The objective of this study is to highlight the functional traits of plants that colonize ultramafic areas after disturbance by fire or mining activities. This information will allow trait-assisted selection of candidate species for reclamation. Fifteen plots were established on ultramafic soils in Sabah (Borneo, Malaysia) disturbed by recurrent fires (FIRE plots) or by soil excavation and quarrying (MINE plots). In each plot, soil samples were collected and plant cover as well as species abundances were estimated. Fifteen functional traits related to revegetation, nutrient improvement, or Ni phytomining were measured in sampled plants. Vegetation of both FIRE and MINE plots was dominated by perennials with lateral spreading capacity (mainly by rhizomes). Plant communities displayed a conservative growth strategy, which is an adaptation to low nutrient availability on ultramafic soils. Plant height was higher in FIRE than in MINE plots, whereas the number of stems per plant was higher in MINE plots. Perennial plants with lateral spreading capacity and a conservative growth strategy would be the first choice for the reclamation of ultramafic degraded areas. Additional notes for increasing nutrient cycling, managing competition, and implementing of Ni-phytomining are also provided.
Chapter
Satellite remote sensing (RS) is useful to indirectly evaluate the spatial and temporal variability of land uses, land‐cover changes, aboveground biomass of vegetation, leaf‐area index of terrestrial vegetation canopies, and plant phenology. These observations allow us to gain a deeper understanding of the spatial and temporal variability of ecosystem structure, ecosystem functions, and biodiversity under climate change. However, satellite RS observations include uncertainties and other issues, and our ecological understanding of satellite RS‐observed data is still insufficient. To solve these issues and to better understand the ecological meaning, we need to collect abundant ground‐truth data from multiple field sites to validate satellite RS‐observed data and conduct integrated analyses using both types. To enhance the development of phenology observation and land‐use and land‐cover change studies, the Phenological Eyes Network (PEN) and the Site‐based dataset for Assessment of Changing Land cover by JAXA project (SACLAJ) were established. In this chapter, we first introduce some of our findings from these two projects, and then we discuss the usability, other related issues, and the outlook of integrated ecosystem studies that use both in situ and satellite RS‐observed data.
Chapter
Since their early stages of development, Geographic Information Systems (GIS) were utilized in a variety of ways to support analytical models in the field of location science. The interactions between the two disciplines soon became so evident that one can safely argue that GIS and location science are influencing each other in multiple ways. The rapid technological advances in the field of GIS and the ever increasing availability of geographically referenced information create even more possibilities for interconnections between GIS and location science. This chapter highlights these new possibilities and the new directions that emerge within academic research as well as in practical applications. We also attempt to point out further possibilities that may emerge in the future for linking these two disciplines.
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ABSTRACT Sustainable forest management promotes financial revenues while keeping the forest cover and environmental services. Nevertheless, the logging operation causes changes in the forest and canopy horizontal and vertical structure. Our objective is to evaluate the changes in the forest canopy and its consequences to the forest management, following logging in a secondary Atlantic Rainforest. We used hemispherical photography to determine the Canopy Openness (CO), Leaf Area Index (LAI) and the radiation absorption (fAPAR) in nine experimental plots before and after logging. We did not find a clear correlation between the forest horizontal structure and the canopy architecture. Despite this, there was an increase in CO and decrease in LAI and fAPAR after logging. The variation in CO and fAPAR were affected by logging intensity, but LAI did not show the same pattern. We suggest a conservative maximum logging intensity of 30% of the basal area and tree density.
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Half of Borneo's forest has been logged and oil palm plantations have replaced millions of hectares of forest since the 1970's. While this extensive land-use change has been shown to reduce species richness across landscapes, there is limited current knowledge on how deforestation affects the spatial arrangement of ecological communities. Identifying responses of beta-diversity to land-use change may reveal processes which could mitigate total biodiversity loss. We sampled weevils (superfamily: Curculionoidea) at multiple spatial scales across a land-use gradient at the Stability of Altered Forest Ecosystems (SAFE) Project in Sabah, Malaysia, in 2011-2012. We caught 160 taxa of weevil and calculated the response of alpha-diversity (1-ha scale) and beta-diversity (10-, 100-, and 1000-ha scales) to disturbance. Alpha-diversity of weevils was greatest in unlogged forest but landscape level beta-diversity (100-and 1000-ha scale) was maintained across logged and unlogged due to high rates of spatial turnover. Turnover at smallest spatial scales (10-ha) in unlogged forest was highest in rough, flat terrain but smooth, sloping terrain had highest turnover in logged forest. Logging of flat terrain at small spatial scales has potential to decrease beta-diversity at greater scales. Beta-diversity at landscape-level in oil palm plantation remained high but was propagated by abundance shifts of few species instead of spatial turnover of many species. High temporal beta-diversity in unlogged forest was evident through periodic fluxes in abundance of many weevil species. We conclude that unlogged forest is irreplaceable for high beetle biodiversity but increased spatial turnover in some terrains may help conserve beetle communities in heavily-degraded landscapes.
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Biodiversity-rich forests in tropical Southeast Asia are being extensively logged and converted to oil palm monocultures. In addition, extreme climatic events such as droughts are becoming more common. Land-use change and extreme climatic events are thought to have synergistic impacts on aquatic biodiversity, but few studies have directly tested this. A severe El Niño drought in Southeast Asia in early 2016 caused 16 low-order hill streams across a land-use gradient encompassing primary forest, logged forest and oil palm plantations in Sabah, Malaysia, to dry up into series of disconnected pools. The resulting disturbance (specifically, increased water temperature and decreased dissolved oxygen concentration) tolerated by the fish during the drought exceeded any worst-case scenario for climate change-induced warming. We quantified the biomass, density and movement of the dominant freshwater fish species, Nematabramis everetti (Cyprinidae), in these streams across this land-use gradient before, during, and after the 2016 El Niño drought period. Density of N. everetti was significantly lower in logged forest streams than primary forest or oil palm streams, and the biomass of individuals captured was lower during drought than prior to the drought; however, there was no change in the biomass density of individuals during drought. The distance moved by N. everetti was significantly lower during and after the drought compared to before the drought. We detected a significant antagonistic interaction on biomass of captured fish, with the magnitude of the drought impact reduced land-use intensified. Populations of N. everetti were surprisingly resilient to drought and seem most affected instead by land-use. Despite this resilience, it is important to monitor how this widespread and abundant species, which provides an important ecosystem service to local human communities, is affected by future land-use and climate change, as logging, deforestation and conversion to plantation monocultures continue across Southeast Asia.
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Extreme warming events can profoundly alter the transmission dynamics of mosquito-borne diseases by affecting mosquito life-history traits (e.g. survival, growth and reproduction). At local scales, temperatures are determined largely by vegetation structure and can be dramatically altered by drivers of land-use change (e.g. forest conversion). Disturbance activities can also hinder the buffering capacity of natural habitats, making them more susceptible to seasonal climate variation and extreme weather events (e.g. droughts). In experiments spanning three years, we investigated the interactive effects of tropical forest conversion and climate on fine-scale temperature, and the consequences for mosquito larval development. This study was conducted in the northern Malaysian Bornean state of Sabah using local Aedes albopictus mosquitoes; important vectors of dengue, chikungunya and Zika viruses. We demonstrate that variation in temperatures due to forest conversion dramatically increases development rates in Ae. albopictus mosquitoes. However, this effect was mediated by an El Niño Southern Oscillation (ENSO) drought event. In normal years, mean temperatures did not differ between land-use types, however mosquitoes reared in oil palm plantations typically emerged 2–3 days faster than in logged forests. During an ENSO drought, mean temperatures did differ between land-use types, but surprisingly this did not result in different mosquito development rates. Driving this idiosyncratic response may be the differences in daily temperature fluctuations between the land-use types that either push mosquito larvae towards optimal development, or over the thermal optimum, thereby reducing fitness. This work highlights the importance of considering the synergistic effects of land-use and seasonal climate variations for predicting the thermal response of a key mosquito life-history trait driving disease transmission dynamics.
Chapter
In the context of present environmental changes, human society is continuously looking for ways to evaluate the status of ecosystems and determine human-induced modifications on their structure and functionality. A clear overview of ecosystems is fundamental in choosing the appropriate measures in our search for sustainability and improving the quality of life. The aim of the chapter is therefore to underline how geography can respond to the need of mapping the distribution and quality of ecosystems. This is easily done by using geospatial technologies, helping to a better understanding of the relation between the spatial distribution and management of ecosystems. The chapter presents the main types of data required by geospatial technologies and the data sources for mapping ecosystems. Challenges in gathering reliable data are also presented besides various methods of overcoming the difficulties. There is a strong emphasis on differentiating the available geospatial technologies for mapping the distribution of ecosystems and for representing their quality. The use of different geospatial technologies in mapping the distribution and quality of specific ecosystems was highlighted through case studies of urban ecosystems, water bodies and forests. We also aimed to identify the causes that determined certain ecosystem approaches, and the potential of geospatial technologies in providing to geographers and other scholars the possibility to explore processes from the past, present, or modeling the future. As geographical assessments require a “cause and effect” approach, we aimed to emphasize how geospatial technologies are used in identifying the causes that determined certain planning policies, shaping the current geographical landscape, the effects of these policies, and the future outcomes of newly implemented or proposed planning policies. The current potential of geospatial technologies gives access to complex diachronic analysis, providing the geographers and other scholars the possibility to explore the various processes that occur in the geographical landscape. The chapter demonstrates how geography and geospatial technologies can help policy and decision makers, local administrations, or stakeholders evaluate the distribution and quality of specific ecosystems.
Article
Plant functional traits regulate ecosystem functions but little is known about how co‐occurring gradients of land use and edaphic conditions influence their expression. We test how gradients of logging disturbance and soil properties relate to community‐weighted mean traits in logged and old‐growth tropical forests in Borneo. We studied 32 physical, chemical and physiological traits from 284 tree species in eight 1 ha plots and measured long‐term soil nutrient supplies and plant‐available nutrients. Logged plots had greater values for traits that drive carbon capture and growth, whilst old‐growth forests had greater values for structural and persistence traits. Although disturbance was the primary driver of trait expression, soil nutrients explained a statistically independent axis of variation linked to leaf size and nutrient concentration. Soil characteristics influenced trait expression via nutrient availability, nutrient pools, and pH. Our finding, that traits have dissimilar responses to land use and soil resource availability, provides robust evidence for the need to consider the abiotic context of logging when predicting plant functional diversity across human‐modified tropical forests. The detection of two independent axes was facilitated by the measurement of many more functional traits than have been examined in previous studies.
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Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above - ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature ( Thermal ground ) and ground vegetation greenness ( NDVI down ) as potentially suitable metrics of habitat quality. We measure both across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both habitat quality metrics decline linearly as a function of increasing canopy closure ( FCover , %) and canopy leaf area index ( LAI ). Opening canopies by about 20% or reducing canopy leaf area by 1% would result in an increase of temperatures on the ground by more than 1°C, and an increase in ground vegetation greenness by 0.2 and 0.14 respectively. Upscaling LAI and FCover to develop maps from Landsat imagery using random forest models allowed us to map Thermal ground and NDVI down using the linear relationships. However, map accuracy was constrained by the predictive capacity of the random forest models predicting canopy attributes and the linear models linking canopy attributes to the habitat quality metrics. Accounting for micro-scale variation in temperature is seen as essential to improve biodiversity impact predictions. Our upscaling approach suggests that mapping ground surface temperature based on radiation and vegetation properties might be possible, and that canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, we need to increase sampling of surface temperature spatially and temporally to improve and validate upscaled models. We also need to link surface temperature maps to demographic traits of species of different threat status or functions in landscapes with different disturbance and management histories testing for generalities in relationships. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation and food security sustainably at the landscape scale.
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The aim of this article is to evaluate current achievements of remote sensing technologies in forest and plantation monitoring. Despite considerable efforts having been dedicated to monitor tropical forest, some issues remain open for further exploration, including forest type mapping, biomass estimation, change detection, and the detection of invasive species. Large-scale forest conversion to plantations makes it necessary to assess applications and methodologies currently published with the aim to provide an outlook for future research. Multispectral datasets have been favored in this domain, largely because of their long-term availability. Remote sensing applications in plantation forests are often perceived as less problematic than natural forests, perhaps due to their relatively homogenous cover. We present evidence that assumptions of homogeneity in canopy cover may not be fully satisfied. Vital aspects of plantation for management such as stand age mapping, detecting disturbance and productivity measurement have been understudied, which therefore warrant further investigation.
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[1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data. Abstract [1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data.
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Aim - Large trees (d.b.h. ≥ 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location - Pan-tropical. Methods - Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICc-wi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results - Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) ± 105.0 (SD) Mg ha−1] versus Palaeotropical forests (Africa 418.3 ± 91.8 Mg ha−1; Asia 393.3 ± 109.3 Mg ha−1). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions - Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees
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Physically-based approaches for estimating Leaf Area Index (LAI) using remote sensing data rely on radiative transfer (RT) models. Currently, many RT models are freely available, but determining the appropriate RT model for LAI retrieval is still problematic. This study aims to evaluate the necessity of RT model selection for LAI retrieval and to propose a retrieval methodology using different RT models for different vegetation types. Both actual experimental observations and RT model simulations were used to conduct the evaluation. Each of them includes needleleaf forests and croplands, which have contrasting structural attributes. The scattering from arbitrarily inclined leaves (SAIL) model and the four-scale model, which are 1D and 3D RT models, respectively, were used to simulate the synthetic test datasets. The experimental test dataset was established through two field campaigns conducted in the Heihe River Basin. The results show that the realistic representation of canopy structure in RT models is very important for LAI retrieval. If an unsuitable RT model is used, then the root mean squared error (RMSE) will increase from 0.43 to 0.60 in croplands and from 0.52 to 0.63 in forests. In addition, an RT model's potential to retrieve LAI is limited by the availability of a priori information on RT model parameters. 3D RT models require more a priori information, which makes them have poorer generalization capability than 1D models. Therefore, physically-based retrieval algorithms should embed more than one RT model to account for the availability of a priori information and variations in structural attributes among different vegetation types.
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Despite a large increase in the area of selectively logged tropical forest worldwide, the carbon stored in deadwood across a tropical forest degradation gradient at the landscape scale remains poorly documented. Many carbon stock studies have either focused exclusively on live standing biomass or have been carried out in primary forests that are unaffected by logging, despite the fact that coarse woody debris (deadwood with ⩾10 cm diameter) can contain significant portions of a forest's carbon stock. We used a field-based assessment to quantify how the relative contribution of deadwood to total above-ground carbon stock changes across a disturbance gradient, from unlogged old-growth forest to severely degraded twice-logged forest, to oil palm plantation. We measured in 193 vegetation plots (25 × 25 m), equating to a survey area of >12 ha of tropical humid forest located within the Stability of Altered Forest Ecosystems Project area, in Sabah, Malaysia. Our results indicate that significant amounts of carbon are stored in deadwood across forest stands. Live tree carbon storage decreased exponentially with increasing forest degradation 7–10 years after logging while deadwood accounted for >50% of above-ground carbon stocks in salvage-logged forest stands, more than twice the proportion commonly assumed in the literature. This carbon will be released as decomposition proceeds. Given the high rates of deforestation and degradation presently occurring in Southeast Asia, our findings have important implications for the calculation of current carbon stocks and sources as a result of human-modification of tropical forests. Assuming similar patterns are prevalent throughout the tropics, our data may indicate a significant global challenge to calculating global carbon fluxes, as selectively-logged forests now represent more than one third of all standing tropical humid forests worldwide.
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Invertebrates are dominant species in primary tropical rainforests, where their abundance and diversity contributes to the functioning and resilience of these globally important ecosystems. However, more than one-third of tropical forests have been logged, with dramatic impacts on rainforest biodiversity that may disrupt key ecosystem processes. We find that the contribution of invertebrates to three ecosystem processes operating at three trophic levels (litter decomposition, seed predation and removal, and invertebrate predation) is reduced by up to one-half following logging. These changes are associated with decreased abundance of key functional groups of termites, ants, beetles and earthworms, and an increase in the abundance of small mammals, amphibians and insectivorous birds in logged relative to primary forest. Our results suggest that ecosystem processes themselves have considerable resilience to logging, but the consistent decline of invertebrate functional importance is indicative of a human-induced shift in how these ecological processes operate in tropical rainforests.
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Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial and temporal proximity. In the study area in Madre de Dios, Peru, 2.3% of land was found to be disturbed over three years, with a false positive rate of 0.3% of area. A low, but significant, detection rate of degradation from sparse and small-scale selective logging was achieved. Disturbances were most common along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter, and backscatter decrease, suggested that large-scale deforestation was likely in areas with initially low biomass, either naturally or since already under anthropogenic use. Further, backscatter increases following disturbance suggested that radar can be used to characterize successional disturbance dynamics, such as biomass accumulation in lands post-abandonment. The presented radar-based detection algorithm is spatially and temporally scalable, and can support monitoring degradation and deforestation in tropical rainforests with the use of products from ALOS-2 and the future SAOCOM and BIOMASS missions.
Article
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Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial and temporal proximity. In the study area in Madre de Dios, Peru, 2.3% of land was found to be disturbed over three years, with a false positive rate of 0.3% of area. A low, but significant, detection rate of degradation from sparse and small-scale selective logging was achieved. Disturbances were most common along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter, and backscatter decrease, suggested that large-scale deforestation was likely in areas with initially low biomass, either naturally or since already under anthropogenic use. Further, backscatter increases following disturbance suggested that radar can be used to characterize successional disturbance dynamics, such as biomass accumulation in lands post-abandonment. The presented radar-based detection algorithm is spatially and temporally scalable, and can support monitoring degradation and deforestation in tropical rainforests with the use of products from ALOS-2 and the future SAOCOM and BIOMASS missions.
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Global concern over rising atmospheric concentrations of carbon dioxide is stimulating development and implementation of policies aimed at reducing net greenhouse gas emissions by enhancing carbon sinks. One option for reducing net emissions is to lessen damage to residual forests during selective logging, thereby retaining additional carbon in biomass. A pilot carbon offset project was initiated in Sabah, Malaysia, in 1992 in which a power company provided funds to a timber concessionaire to implement guidelines aimed at reducing logging damage; in doing so, the utility gained potential credit towards future emissions reduction requirements. To quantify the carbon retained due to this effort, we compared dipterocarp forests logged according to reduced-impact logging guidelines with forests logged by conventional methods in terms of the above- and below-ground biomass both before and after logging. Prior to logging, the forest stored approximately 400 Mg biomass ha-1, 17 percent of which was belowground. High volumes of timber were removed from both of the logging areas (mean CNV = 154, RIL = 104 m3ha-1). Forty-one percent of the unharvested trees
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Significance Although tropical forests absorb more carbon dioxide as biomass than any other terrestrial ecosystem, biomass estimates disagree substantially at landscape-to-regional scales. Current biomass maps rely upon field plots for extrapolations to larger scales, yet whether field plots accurately represent landscape-scale variables has not been assessed. To our knowledge, this is the first study to compare forest structural variables and aboveground biomass derived from field plots to those derived from their host landscapes using airborne 3D remote sensing. We found that typical field plots can produce substantially biased estimates and the number of plots needed to reduce this bias is impractical, positioning airborne remote sensing as a core tool for mapping forest structure and biomass across tropical landscapes.
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Land use change is a major threat to biodiversity. One mechanism by which land use change influences biodiversity and ecological processes is through changes in the local climate. Here, the relationships between leaf area index and five climate variables – air temperature, relative humidity, vapour pressure deficit, specific humidity and soil temperature – are investigated across a range of land use types in Borneo, including primary tropical forest, logged forest and oil palm plantation. Strong correlations with the leaf area index are found for the mean daily maximum air and soil temperatures, the mean daily maximum vapour pressure deficit and the mean daily minimum relative humidity. Air beneath canopies with high leaf area index is cooler and has higher relative humidity during the day. Forest microclimate is also found to be less variable for sites with higher leaf area indices. Primary forest is found to be up to 2.5 °C cooler than logged forest and up to 6.5 °C cooler than oil palm plantations. Our results indicate that leaf area index is a useful parameter for predicting the effects of vegetation upon microclimate, which could be used to make small scale climate predictions based on remotely sensed data.
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The recent Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g product provides a 30-year global times-series of remotely sensed leaf area index (LAI), an essential variable in models of ecosystem process and productivity. In this study, we use a new dataset of field-based LAITrue to indirectly validate the GIMMS LAI3g product, LAIavhrr, in East Africa, comparing the distribution properties of LAIavhrr across biomes and environmental gradients with those properties derived for LAITrue. We show that the increase in LAI with vegetation height in natural biomes is captured by both LAIavhrr and LAITrue, but that LAIavhrr overestimates LAI for all biomes except shrubland and cropland. Non-linear responses of LAI to precipitation and moisture indices, whereby leaf area peaks at intermediate values and declines thereafter, are apparent in both LAITrue and LAIavhrr, although LAITrue reaches its maximum at lower values of the respective environmental driver. Socio-economic variables such as governance (protected areas) and population affect both LAI responses, although cause and effect are not always obvious: a positive relationship with human population pressure was detected, but shown to be an artefact of both LAI and human settlement covarying with precipitation. Despite these complexities, targeted field measurements, stratified according to both environmental and socio-economic gradients, could provide crucial data for improving satellite-derived LAI estimates, especially in the human-modified landscapes of tropical Africa.
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Forests in Flux Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Hansen et al. (p. 850 ) examined global Landsat data at a 30-meter spatial resolution to characterize forest extent, loss, and gain from 2000 to 2012. Globally, 2.3 million square kilometers of forest were lost during the 12-year study period and 0.8 million square kilometers of new forest were gained. The tropics exhibited both the greatest losses and the greatest gains (through regrowth and plantation), with losses outstripping gains.
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a b s t r a c t The choice of an appropriate allometric model is a critical step in reducing uncertainties in forest biomass stock estimates. With large greenhouse gases emissions due to deforestation, a systematic assessment and comparison of the models available in Indonesia is crucial for accurate assessments of forest carbon stocks and implementing REDD+ projects. In the present study, we compared the ability of two regional and two generic (pantropical) allometric models to estimate biomass at both tree and plot levels. We showed that regional models had lower performance in estimating tree biomass, with greater bias (À31–8%) and higher AIC (177–204), compared to generic models (bias: À2–2%; AIC: 57–67). At the plot level, the regional models underestimated biomass stocks by 0–40% compared to the best generic model. The error in plot biomass stocks associated to models relying solely upon DBH ranged between À5 and +15%. The integration of tree height estimated regionally resulted in an overestimate of 5–10% in unman-aged forests. Despite the difficulty to accurately assess tree heights in tropical forests, integrating all or part of them in biomass assessment can reduce uncertainties. Ó 2013 The Authors. Published by Elsevier B.V. All rights reserved.