Tropical Forest Disturbance Research Articles

Soil Microbial Community and Litter Quality Controls on Decomposition Across a Tropical Forest Disturbance Gradient

Industrial logging and agricultural expansion are driving rapid transformations of tropical ecosystems, modifying patterns in above-ground plant and below-ground microbial communities. However, the extent to which these changes in biodiversity drive modifications of ecosystem process rates such as leaf litter decomposition is poorly understood. To determine the relative effects of changes to the chemical quality of litter and shifts in microbial decomposers on leaf litter decomposition rates, we performed a controlled, reciprocal transplant, litter decomposition experiment across a tropical land-use disturbance gradient. Litter mixtures and soils were collected from old growth forest, moderately logged forest, heavily logged forest, and oil palm plantation in Sabah, Malaysia, and combined in a fully crossed, factorial microcosm experiment maintained under controlled environmental conditions. We found that whilst litter quality was the most important predictor of litter mass loss, soil origin was also significant, explaining between 5.17 and 15.43% of total variation. Microbial decomposer communities from old growth forest had greater functional breadth relative to those from logged forests and oil palm plantation as all litter types decomposed faster when combined with old growth soil. The most chemically recalcitrant litter (lowest N, highest lignin, lignin:N, and C:N ratio) from moderate logged forest decomposed faster when combined with its “home” soil (Home-Field Advantage) whilst the most labile litter from oil palm decomposed slowest when combined with its “home” soil. This was correlated with lower total soil microbial biomass. Taken together, these findings demonstrate that whilst litter quality regulated rates of litter decomposition across the disturbance gradient, soil microbial decomposer communities were functionally dissimilar between land uses and explained a significant proportion of variation. The impact of disturbance on soil, including microbial community structure, should be considered alongside changes to plant communities when assessing effects on crucial ecosystem processes such as decomposition.

Impacts of selective logging on the oxidative status of tropical understorey birds.

Selective logging is the dominant form of human disturbance in tropical forests, driving changes in the abundance of vertebrate and invertebrate populations relative to undisturbed old-growth forests. A key unresolved question is understanding which physiological mechanisms underlie different responses of species and functional groups to selective logging. Regulation of oxidative status is thought to be one major physiological mechanism underlying the capability of species to cope with environmental changes. Using a correlational cross-sectional approach, we compared a number of oxidative status markers among 15 understorey bird species in unlogged and selectively logged forest in Borneo in relation to their feeding guild. We then tested how variation of markers between forest types was associated with that in population abundance. Birds living in logged forests had a higher activity of the antioxidant enzyme superoxide dismutase and a different regulation of the glutathione cycle compared to conspecific birds in unlogged forest. However, neither oxidative damage nor oxidized glutathione differed between forest types. We also found that omnivores and insectivores differed significantly in all markers related to the key cellular antioxidant glutathione irrespective of the forest type. Species with higher levels of certain antioxidant markers in a given type of forest were less abundant in that forest type compared to the other. Our results suggest that there was little long-term effect of logging (last logging rotation occurred ~15years prior to the study) on the oxidative status of understorey bird species. However, it is unclear if this was owing to plasticity or evolutionary change. Our correlative results also point to a potential negative association between some antioxidants and population abundance irrespective of the forest type.

Anthropogenic disturbance and recovery in tropical peat swamp forests

Anthropogenic disturbance and recovery in tropical peat swamp forests

Tree species diversity and biomass carbon assessment in undisturbed and disturbed tropical forests of Dibru-Saikhowa biosphere reserve in Assam North-East India

In the present study, the tree species phytosociological attributes, tree density, basal area, and tree biomass carbon (above- and below-ground) distribution pattern was explored in the undisturbed and disturbed forest sites in Dibru-Saikhowa biosphere reserve of Assam, northeast India. The study area is globally recognized biodiversity hotspots in India and situated in the flood plain of the Brahmaputra and Lohit River. The tree species attributes like tree density, basal area, and tree biomass carbon were estimated in three undisturbed and disturbed forest sites. Principal component analysis, redundancy analysis, and correlation analyses were conducted to explore the relationship between biodiversity indices, forest stands characteristic, and tree biomass. The undisturbed forest stand showed the highest biological attributes (29–39 species and 25–33 genera) compare to disturbed forest stands (27–32 species and 21–27 genera). Combretaceae, Lauraceae, Phyllanthaceae, Salicaceae, Myrtaceae, and Moraceae has shown a higher importance value index. The biodiversity indices were significantly higher in undisturbed forest stands and the Shannon–Wiener diversity index (H′) ranged from 1.97 to 3.57, Simpson index (Cd) ranged from 0.76 to 0.88, and evenness index (e) ranged from 0.65 to 0.97 in all the stands. The mean tree density and forest basal area were significantly higher in the undisturbed forest (796.66 ha−1 and 56.56 m2 ha−1, respectively) compared to disturbed forest stands (436.66 ha−1 and 38.91 m2 ha−1, respectively). Tree biomass carbon in undisturbed forest (184–214.62 Mg C ha−1) was also more than disturbed forests (124–137.53 Mg C ha−1). Moreover, the biomass carbon was greatly affected by the tree composition, diversity, density, and the disturbances in forest stands. The present study will provide the baseline information for effective and sustainable tree species diversity conservation and evaluate tree carbon stock in the Dibru-Saikhowa biosphere reserve.

Forest resilience to fire in eastern Amazon depends on the intensity of pre-fire disturbance

Researchers and managers face the challenge of how to determine when frequency, spatial extent and magnitude of disturbances can overcome the resilience of forest ecosystems. Among the disturbances in tropical forests, the mid- and long-term impacts of fire are still poorly known, especially how fire interacts with selective logging. In this study, we approached the two following questions in relation to dense ombrophilous forests with a history of selective logging: How does fire impact forest recovery? What is the relationship between pre-fire forest conditions and post-fire dynamics? We used data for trees with DBH ≥ 5 cm from 36 permanent plots of 0.25-ha (50 m × 50 m) in an area of dense ombrophilous forest monitored over 31 years in the Tapajós National Forest, in Brazil’s eastern Amazon. The area is under forest management that includes logging, the application of post-harvesting silvicultural treatments and an accidental fire. To determine the effects of pre-fire disturbances (logging and thinning) on basal area (G), mortality rate (MR) and recruitment rate (RR), a repeated measures ANOVA was applied. The post-fire forest recovery was also assessed by looking at changes in G, MR and RR. These variables were evaluated through a Linear Mixed Effect Model. In the post-fire period, there was a combined effect of logging commercial species, thinning non-commercial species (F = 9.255; p-value < 0.01) and time (F = 20.210; p-value < 0.01) in G, with no fire effect (F = 0.710; p-value = 0.406). Our study found the dense ombrophilous forest to be resilient enough to recover from logging, thinning, and a superficial fire, and that logging intensity is a determinant factor in forest dynamics. The forest in our control area with no history of previous strong and frequent disturbances was more resistant to fire in terms of lower mortality rates than the logged and thinned areas. In the short-term, the fire affected mainly the dynamics of smaller trees (DBH < 20 cm). In the med-term (15 years after the fire), we observed no fire effects on the reduction of basal area in any of the treatments and the forest maintained a continuous recovery of its lost stocks.

A mechanistic and empirically supported lightning risk model for forest trees

AbstractTree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood.We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone‐based maps of tree crowns and censuses of all trees within a 50‐ha forest dynamics plot on Barro Colorado Island, Panama.The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent &gt; canopy &gt;&gt;&gt; subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighbouring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters.These patterns suggest that lightning influences forest structure and the global carbon budget by non‐randomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests.Synthesis. Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (&lt;15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighbouring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.

Quantifying the factors affecting wood decomposition across a tropical forest disturbance gradient

Woody debris represents a substantial reservoir of carbon in forests. Disentangling the effects of factors affecting wood decomposition rates is therefore important. We examined the abiotic and biotic factors affecting wood decomposition across a disturbance gradient from mature forest to open land in a tropical montane site in Xishuangbanna, SW China. Wood logs (n = 280) of two native species with contrasting wood specific gravity (WSG), Castanopsis mekongensis (0.75) and Litsea cubeba (0.42), were exposed on the ground for three years. For each log, WSG was monitored at intervals by taking cores from top-half (up) and bottom-half (down) of the log. Mass loss was measured at the end of the experiment.WSG loss rates were similar across the disturbance gradient and the species effect varied with core position. For Castanopsis, which had higher initial WSG and wood N concentration and much thicker bark, up-cores had consistently higher WSG loss over the study period. This species also had substantially higher WSG loss for up-cores, but interspecific difference among down-cores was small.For mass loss, there was a complex interaction between species, habitat and the presence of termites. Litsea with low initial WSG experienced approximately two-fold higher mass loss in the absence of termites, but the difference between species was smaller in the presence of termites. Both species experienced higher mass loss in open habitats than in forests, but the termite effect was smaller in open habitats especially for Litsea. There was no interspecific difference in susceptibility to termite infestation, but infestation rates were higher in regenerating forests and open land than in mature forest. WSG loss explained 0% and 19% of mass loss variation in Listea and Castanopsis, respectively, in absence of termites and 0% for both in the presence of termites.Afterlife effects of wood functional traits interact with abiotic conditions and decomposition processes (microbial decomposition, macro-organisms (termites), photo-degradation) in a complex manner to determine wood decomposition rates. WSG loss is not a reliable predictor of mass loss. These results have important implications for understanding the carbon cycle in tropical landscapes that are undergoing anthropogenic disturbance.

Ecological generalism and resilience of tropical island mammals to logging: A 23 year test.

Tropical forest disturbance is a key driver of global biodiversity decline. On continents, the effects of logging are greatest on endemic species, presumably because disturbance is more likely to cover narrower distributions (the "cookie cutter" model). Islands hold disproportionate biodiversity, and are subject to accelerating biotic homogenization, where specialist endemics are lost while generalists persist. We tested responses of tropical island mammals to logging at multiple spatial scales, using a long-term experimental test in a Pacific archipelago. The most widely distributed ecological generalists did not decline after logging, and we detected no overall changes in relative abundance or species diversity. However, endemics with small ranges did decline in response to logging. The least mobile and most range-restricted species declined even at the smallest spatial scale, supporting the cookie cutter model for sedentary species, and suggesting that habitat change due to selective logging is contributing to biotic homogenization on islands.

Nutrient properties of tidal-borne alluvial sediments from a tropical mangrove ecosystem

Mangroves are inundated through tidal action, which mobilizes a large quantity of suspended and dissolved particles, including both decomposed mangrove and terrigenous materials. Sediments brought in by tidal water and trapped by mangrove roots contribute to the productivity of coastal, tropical mangrove ecosystems. They play an important role in the nutrient cycling of these ecosystems. However, there is limited information on sediment properties, inclusive of nutrients levels in tidal-borne sediments affecting mangrove ecosystems. Selected properties of sediment, including cation exchange capacity (CEC), texture, organic matter (OM) content, organic carbon (OC) content, and nutrient content (C, N, S, P, K, Ca and Mg) were studied, in a seasonal pattern, in tidal-borne sediment from Sibuti estuary mangrove. Sediment showed a high proportion of sand (range: 60%–65%) with high mean values of CEC 17 cmol/kg, a sediment OM content of 15%, and OC content of 13%. The mean average content of C was 15%, and mean concentrations of N, S, P, K, Ca, Mg and Na were 12, 10, 2, 3, 34, 18 and 16 (mg/kg), respectively. Significant positive relationships were found among nutrient concentrations in sediment and nutrient concentrations in leaf, stipule, flower, propagule, stem, bark, and root of both Rhizophora apiculata (Blume) and Xylocarpus granatum (Koenig) trees and their saplings. Seedlings are indicative of the growth, health, and productivity of the mangrove ecosystem, and are largely dependent on the phenomenon of nutritive aspects of tidal-borne sediments. The results of this study provide baseline information on the roles of nutrient productivity of a less disturbed tropical mangrove forest, adjacent to the South China Sea.

MAPPING DISTURBANCE FROM SELECTIVE LOGGING IN TROPICAL FORESTS OF THE YUCATAN PENINSULA, MEXICO

&lt;p&gt;&lt;strong&gt;Background. &lt;/strong&gt;Mapping selective logging impacts on the Yucatan Peninsula is important to pursuing carbon emissions reduction and biodiversity conservation goals. &lt;strong&gt;Objective.&lt;/strong&gt; To evaluate the effectiveness of applying remote sensing techniques using LANDSAT 8 OLI imagery to detect tropical forest disturbance from timber harvesting in four communally managed forests (&lt;em&gt;ejidos&lt;/em&gt;). We further assess differences among them in terms of implementing improved forest management (IFM) and reduced impact logging (RIL). &lt;strong&gt;Methodology. &lt;/strong&gt;Vegetation indices were calculated, and forest cover classification was performed to map logged and unlogged forest and specific harvest disturbances (e.g. felling gaps, skid trails, logging roads and log landings) in annual cutting areas of 2014. Accuracy assessments were conducted based on validation points collected in the field after logging. &lt;strong&gt;Results.&lt;/strong&gt; We found that 75% of the binary classifications (logged and unlogged forest) had mean overall accuracies greater than 60%, representing a fair (40 to 70%) accuracy, although mapping of specific harvesting disturbances had poor accuracy (&amp;lt;40%). Vegetation indices that performed the best were normalized vegetation index (NDVI), Tasseled Cap Greenness and Tasseled Cap Wetness. Ejidos that applied IFM and RIL impacted a smaller percentage of their cutting areas and less area of forest per cubic meter of timber extracted, despite similar or higher logging intensities than ejidos without improved practices. &lt;strong&gt;Implication.&lt;/strong&gt; Monitoring selective logging disturbance is important to improved forest management and certification of sustainability. &lt;strong&gt;Conclusion.&lt;/strong&gt; Mapping and monitoring impacts from selective logging by forest managers and technicians can be performed in a cost-efficient manner using LANDSAT 8 images, although accuracy could be improved with higher resolution imagery.&lt;/p&gt;

Use of SAR and Optical Time Series for Tropical Forest Disturbance Mapping

Frequent cloud cover and fast regrowth often hamper topical forest disturbance monitoring with optical data. This study aims at overcoming these limitations by combining dense time series of optical (Sentinel-2 and Landsat 8) and SAR data (Sentinel-1) for forest disturbance mapping at test sites in Peru and Gabon. We compare the accuracies of the individual disturbance maps from optical and SAR time series with the accuracies of the combined map. We further evaluate the detection accuracies by disturbance patch size and by an area-based sampling approach. The results show that the individual optical and SAR based forest disturbance detections are highly complementary, and their combination improves all accuracy measures. The overall accuracies increase by about 3% in both areas, producer accuracies of the disturbed forest class increase by up to 25% in Peru when compared to only using one sensor type. The assessment by disturbance patch size shows that the amount of detections of very small disturbances (&lt; 0.2 ha) can almost be doubled by using both data sets: for Gabon 30% as compared to 15.7–17.5%, for Peru 80% as compared to 48.6–65.7%.

Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin

Given the impact of tropical forest disturbances on atmospheric carbon emissions, biodiversity, and ecosystem productivity, accurate long-term reporting of Land-Use and Land-Cover (LULC) change in the pre-satellite era (&lt;1972) is an imperative. Here, we used a combination of historical (1958) aerial photography and contemporary remote sensing data to map long-term changes in the extent and structure of the tropical forest surrounding Yangambi (DR Congo) in the central Congo Basin. Our study leveraged structure-from-motion and a convolutional neural network-based LULC classifier, using synthetic landscape-based image augmentation to map historical forest cover across a large orthomosaic (~93,431 ha) geo-referenced to ~4.7 ± 4.3 m at submeter resolution. A comparison with contemporary LULC data showed a shift from previously highly regular industrial deforestation of large areas to discrete smallholder farming clearing, increasing landscape fragmentation and providing opportunties for substantial forest regrowth. We estimated aboveground carbon gains through reforestation to range from 811 to 1592 Gg C, partially offsetting historical deforestation (2416 Gg C), in our study area. Efforts to quantify long-term canopy texture changes and their link to aboveground carbon had limited to no success. Our analysis provides methods and insights into key spatial and temporal patterns of deforestation and reforestation at a multi-decadal scale, providing a historical context for past and ongoing forest research in the area.

Correction to: Soil erosion as a resilience drain in disturbed tropical forests

In the original version of this article, the following text must be added in the acknowledgement. M.H., B.M.F. and R.S.O. acknowledge the project grant from Instituto Serrapilheira/Serra-1709–18983.

Detecting Forest Changes Using Dense Landsat 8 and Sentinel-1 Time Series Data in Tropical Seasonal Forests

The accurate and timely detection of forest disturbances can provide valuable information for effective forest management. Combining dense time series observations from optical and synthetic aperture radar satellites has the potential to improve large-area forest monitoring. For various disturbances, machine learning algorithms might accurately characterize forest changes. However, there is limited knowledge especially on the use of machine learning algorithms to detect forest disturbances through hybrid approaches that combine different data sources. This study investigated the use of dense Landsat 8 and Sentinel-1 time series data for detecting disturbances in tropical seasonal forests based on a machine learning algorithm. The random forest algorithm was used to predict the disturbance probability of each Landsat 8 and Sentinel-1 observation using variables derived from a harmonic regression model, which characterized seasonality and disturbance-related changes. The time series disturbance probabilities of both sensors were then combined to detect forest disturbances in each pixel. The results showed that the combination of Landsat 8 and Sentinel-1 achieved an overall accuracy of 83.6% for disturbance detection, which was higher than the disturbance detection using only Landsat 8 (78.3%) or Sentinel-1 (75.5%). Additionally, more timely disturbance detection was achieved by combining Landsat 8 and Sentinel-1. Small-scale disturbances caused by logging led to large omissions of disturbances; however, other disturbances were detected with relatively high accuracy. Although disturbance detection using only Sentinel-1 data had low accuracy in this study, the combination with Landsat 8 data improved the accuracy of detection, indicating the value of dense Landsat 8 and Sentinel-1 time series data for timely and accurate disturbance detection.

Rapid recovery of thermal environment after selective logging in the Amazon

Selective logging is one of the most widespread pattern of disturbance in tropical forests but has a much lower detrimental impact on forest structure than wildfires and conversion to farmland. Thus, logged tropical forest represents critical strongholds of global biodiversity. The ability of these forests to rapidly recover their baseline thermal environmental conditions will markedly influence their conservation value, particularly under global climate change. We investigated the impacts of commercial selective logging on the forest thermal environment in the Brazilian Amazon by relating canopy disturbance from logging to ambient understorey and ground surface temperatures. Specifically, we assessed the impact of selective logging on the forest thermal heterogeneity; how much post-harvest time is required for the thermal environment of logging gaps and logging roads return to unlogged primary forest levels; and the spatial availability of surface microclimates considering time of recovery since logging. Logging gaps following 1 year of recovery had a hotter understorey ambient than all other environments, especially during peak midday temperatures. Compared to the unlogged understorey, logging gaps after 3 years of recovery were only marginally warmer, and logging gaps after 5 years of recovery were slightly cooler. Older wide roads (5 years; 6 m) experienced very similar understorey thermal conditions than both narrow roads (3 m) after 1-5 years of recovery, and unlogged forest. Ground surface temperatures exhibited the largest discrepancies among all environments. The temperature range spanned by surface microclimates notably increased during peak midday heat in logging gaps following 1 year of recovery. Additionally, the proportion of cool area was smaller in younger logging gaps, but the average size of cool patches and their spatial aggregation was similar to that in unlogged forest. Although commercial selective logging can severely damage tropical forest structure, we found that the forest can fairly rapidly regain its thermal environment. Post-logging forest management should carefully focus on preventing fire incursions and illegal activities with special attention to those 3-5 years post-harvest. Thermal homeostasis in selectively logged tropical forests can be vital for long-term maintenance of global biodiversity under contemporary scenarios of climate change.

A novel approach involving the use of Odonata as indicators of tropical forest degradation: When family matters

• Odonata can be effective and cost-efficient indicators of habitat status. • Coenagrionidae and Libellulidae as indicator groups. • Odonata adult-based bioassessment method is reliable. • The method may be easily applied in any tropical forest habitat worldwide. Odonata have proven to be good indicators of freshwater as well as terrestrial habitat conditions. Several studies have shown changes in odonate species richness and/or community composition in response to deforestation, suggesting their potential as bioassessment tools in the tropics. However, former approaches using Odonata as an indicator group required comparative samples from differently disturbed sites and/or knowledge of the focal species environmental specificity. Here, we tested a robust, adult-based bioassessment method assuming that the level of tropical forest degradation reflects the proportional representation of the taxa above species. Based on Web of Science, ScienceDirect, and Scopus databases, we used data from previously published studies linking odonate assemblages to human-mediated disturbances in tropical forests. We hypothesized that along a disturbance gradient (from primary forest to non-forest), (i) the proportion of the suborder Zygoptera (mostly habitat specialists sensitive to deforestation) will decrease in favor of the suborder Anisoptera (high proportion of generalists); and (ii) the proportions of largely generalist families Coenagrionidae and Libellulidae will increase at the expense of other Zygoptera and Anisoptera, respectively. Our results revealed that a ratio of Zygoptera/Anisoptera is a poor indicator of tropical forest conditions, probably because of ecological diversity within these groups. However, the proportions of Coenagrionidae/other Zygoptera and Libellulidae/other Anisoptera significantly increased along a disturbance gradient, suggesting their potential to be a good indicator of well-preserved, altered, and heavily degraded forest habitats. Therefore, our results are in line with studies presenting the usefulness of adult Odonata as versatile indicators for assessing human-mediated changes in tropical forest environments, supporting the practical use of this group in biological monitoring.

Soil erosion as a resilience drain in disturbed tropical forests

Tropical forests are threatened by intensifying natural and anthropogenic disturbance regimes. Disturbances reduce tree cover and leave the organic topsoil vulnerable to erosion processes, but when resources are still abundant forests usually recover. Across the tropics, variation in rainfall erosivity – a measure of potential soil exposure to water erosion – indicates that soils in the wetter regions would experience high erosion rates if they were not protected by tree cover. However, twenty-first-century global land cover data reveal that in wet South America tropical tree cover is decreasing and bare soil area is increasing. Here we address the role of soil erosion in a positive feedback mechanism that may persistently alter the functioning of disturbed tropical forests. Based on an extensive literature review, we propose a conceptual model in which soil erosion reinforces disturbance effects on tropical forests, reducing their resilience with time and increasing their likelihood of being trapped in an alternative vegetation state that is persistently vulnerable to erosion. We present supporting field evidence from two distinct forests in central Amazonia that have been repeatedly disturbed. Overall, the strength of the erosion feedback depends on disturbance types and regimes, as well as on local environmental conditions, such as topography, flooding, and soil fertility. As disturbances intensify in tropical landscapes, we argue that the erosion feedback may help to explain why certain forests persist in a degraded state and often undergo critical functional shifts.

Near real-time monitoring of tropical forest disturbance: New algorithms and assessment framework

Near real-time monitoring systems of forest disturbance are essential to reduce illegal logging and global deforestation, but the assessment of their performance varies greatly and rarely adheres to recommended assessment practices. Current assessment protocols recommended in the published literature focus on sample-based estimation of area and accuracy of features in remote sensing-based maps, which is less relevant for assessing the performance of near real-time monitoring systems. Rather than area bias and accuracy of mapped features, the objective of near real-time monitoring is fast detection of forest disturbance events. Here we present a new assessment framework as well as two new algorithms for near real-time monitoring of tropical forest disturbance. The first algorithm (NRT-CCDC) fits time series models based on MODIS data to predict future observations. Detections of forest disturbance are labeled as “low-probability”, “high-probability”, and “confirmed” based on the number of consecutive observations that deviate substantially from the prediction. The second algorithm (Fusion2) predicts MODIS observations at a high temporal frequency by building a model based on a time series of Landsat observations. Fusion2 utilizes daily MODIS observations from both Terra and Aqua to achieve rapid detection of disturbance events. A framework for assessing the performance of near real-time monitoring is presented that focuses on the timing and minimum detectable size of forest disturbance events while still being based on probability sampling and design-based inference. Central to the framework is a new metric we refer to as the “alert-lag relationship”, which characterizes the frequency of omitted disturbance events as a function of the time lag between the dates of disturbance and detection. When applied to three different near-real monitoring systems representing three levels of operational readiness (Fusion2, NRT-CCDC and Terra-i), we found that Fusion2 achieved an alert accuracy (event-based agreement) of 50% after 82 days and NRT-CCDC achieved 50% after 126 days. Terra-i never achieved an alert accuracy of 50% but achieved 30% after 109 days. In terms of event size, all three systems showed better performance in detecting large events compared to small events. The smallest event detected by the three systems was 6.5 ha. Conventional accuracy assessment (pixel-based agreement) showed that the user's accuracy, which characterizes commission errors, of the disturbance class for Fusion2, NRT-CCDC, and Terra-i were 87%, 79%, and 30% respectively. The two more complex systems, Fusion2 and NRT-CCDC were consistently more accurate than the operational Terra-i system. In general, the higher the cost of implementing the system corresponded to a higher accuracy of the detection system. A primary objective moving forward is to make the NRT-CCDC and Fusion2 more operational over larger areas.

Effect of disturbance on plant species diversity in moist tropical forest of eastern Nepal

Species diversity is a key factor for the stability of ecosystems but the increasing disturbances in tropical forests resulted in the shrinkage of biological diversity. This study was conducted in undisturbed and disturbed stands of Sal (Shorea robusta Gaertn.) dominated moist tropical forest of Sunsari district, eastern Nepal in order to understand the herb, shrub and tree diversity. Present study reported the 47, 16 and 60 species of herbs, shrubs and trees, respectively. The species richness and the Shannon–Wiener index for tree species were higher in undisturbed forest (9.11 and 3.08, respectively), while the Simpson’s index (index of dominance) was higher in disturbed forest (0.11). On the other hand, reverse case was found for shrubs and herbs where species richness and Shannon–Wiener index were higher but index of dominance was lower in disturbed forest. Changes in species diversity pattern reflect the effect of disturbance.

Low-intensity logging and hunting have long-term effects on seed dispersal but not fecundity in Afrotropical forests.

Hunting and logging, ubiquitous human disturbances in tropical forests, have the potential to alter the ecological processes that govern population recruitment and community composition. Hunting-induced declines in populations of seed-dispersing animals are expected to reduce dispersal of the tree species that rely on them, resulting in potentially greater distance- and density-dependent mortality. At the same time, selective logging may alter competitive interactions among tree species, releasing remaining trees from light, nutrient or space limitations. Taken together, these disturbances may alter the community composition of tropical forests, with implications for carbon storage, biodiversity conservation and ecosystem function. To evaluate the effects of hunting and logging on tree fecundity and seed dispersal, we use 3 years of seed rain data from a large-scale observational experiment in previously logged, hunted and protected forests in northern Republic of Congo (Brazzaville). We find that low-intensity logging had a meaningful long-term effect on species-specific seed dispersal distances, though the direction and magnitude varied and was not congruent within dispersal vector. Tree fecundity increased with tree diameter, but did not differ appreciably across disturbance regimes. The species-specific dispersal responses to logging in this study point towards the long-lasting toll of disturbance on ecological function and highlight the necessity of conserving intact forest.