71 resultados para Semideciduous seasonal forest


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Accurate estimations of water balance are needed in semi-arid and sub-humid tropical regions, where water resources are scarce compared to water demand. Evapotranspiration plays a major role in this context, and the difficulty to quantify it precisely leads to major uncertainties in the groundwater recharge assessment, especially in forested catchments. In this paper, we propose to assess the importance of deep unsaturated regolith and water uptake by deep tree roots on the groundwater recharge process by using a lumped conceptual model (COMFORT). The model is calibrated using a 5 year hydrological monitoring of an experimental watershed under dry deciduous forest in South India (Mule Hole watershed). The model was able to simulate the stream discharge as well as the contrasted behaviour of groundwater table along the hillslope. Water balance simulated for a 32 year climatic time series displayed a large year-to-year variability, with alternance of dry and wet phases with a time period of approximately 14 years. On an average, input by the rainfall was 1090 mm year(-1) and the evapotranspiration was about 900 mm year(-1) out of which 100 mm year(-1) was uptake from the deep saprolite horizons. The stream flow was 100 mm year(-1) while the groundwater underflow was 80 mm year(-1). The simulation results suggest that (i) deciduous trees can uptake a significant amount of water from the deep regolith, (ii) this uptake, combined with the spatial variability of regolith depth, can account for the variable lag time between drainage events and groundwater rise observed for the different piezometers and (iii) water table response to recharge is buffered due to the long vertical travel time through the deep vadose zone, which constitutes a major water reservoir. This study stresses the importance of long term observations for the understanding of hydrological processes in tropical forested ecosystems. (C) 2009 Elsevier B.V. All rights reserved.

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Variability in rainfall is known to be a major influence on the dynamics of tropical forests, especially rates and patterns of tree mortality. In tropical dry forests a number of contributing factors to tree mortality, including dry season fire and herbivory by large herbivorous mammals, could be related to rainfall patterns, while loss of water potential in trees during the dry season or a wet season drought could also result in enhanced rates of death. While tree mortality as influenced by severe drought has been examined in tropical wet forests there is insufficient understanding of this process in tropical dry forests. We examined these causal factors in relation to inter-annual differences in rainfall in causing tree mortality within a 50-ha Forest Dynamics Plot located in the tropical dry deciduous forests of Mudumalai, southern India, that has been monitored annually since 1988. Over a 19-year period (1988-2007) mean annual mortality rate of all stems >1 cm dbh was 6.9 +/- 4.6% (range = 1.5-17.5%); mortality rates broadly declined from the smaller to the larger size classes with the rates in stems >30 cm dbh being among the lowest recorded in tropical forest globally. Fire was the main agent of mortality in stems 1-5 cm dbh, elephant-herbivory in stems 5-10 cm dbh, and other natural causes in stems > 10 cm dbh. Elephant-related mortality did not show any relationship to rainfall. On the other hand, fire-related mortality was significantly negatively correlated to quantity of rainfall during the preceding year. Mortality due to other causes in the larger stem sizes was significantly negatively correlated to rainfall with a 2-3-year lag, suggesting that water deficit from mild or prolonged drought enhanced the risk of death but only with a time lag that was greater than similar lags in tree mortality observed in other forest types. In this respect, tropical dry forests growing in regions of high rainfall variability may have evolved greater resistance to rainfall deficit as compared to tropical moist or temperate forests but are still vulnerable to drought-related mortality.

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Reproduction of plants in fragmented habitats may be limited because of lower diversity or abundance of pollinators, and/or variation in local plant density. We assessed natural fruit set and pollinator limitation in ten species of woody plants in natural and restored fragments in the Pondicherry region of southern India, to see whether breeding system of plants (self-compatible and self-incompatible) affected fruit set. We tested whether the number of flowering individuals in the fragments affected the fruit set and further examined the adult and sapling densities of self-compatible (SC) and self-incompatible (SI) species. We measured the natural level of fruit set and pollinator limitation (calculated as the difference in fruit set between hand cross-pollinated and naturally pollinated flowers). Our results demonstrate that there was a higher level of pollinator limitation and hence lower levels of natural fruit set in self-incompatible species as compared to self-compatible species. However, the hand cross-pollinated flowers in SC and SI species produced similar levels of fruit set,further indicating that lower fruit set was due to pollinator limitation and not due to lack of cross-compatible individuals in the fragments. There was no significant relation between number of flowering individuals and the levels of natural fruit set, except for two species Derris ovalifolia, Ixora pavetta. In these species the natural fruit set decreased with increasing population size, again indicating pollinator limitation. The adult and sapling densities in self-compatible species were significantly higher than inself-incompatible species. These findings indicate that the low reproductive output in self-incompatible species may eventually lead to lower population sizes. Restoration of pollinator services along with plant species in fragmented habitats is important for the long-term conservation of biodiversity. (C) 2009 Elsevier Masson SAS. All rights reserved.

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A permanent 2 ha (200 m x 100 m) plot was established for long-term monitoring of plant diversity and dynamics in a tropical dry deciduous forest of Bhadra Wildlife Sanctuary, Karnataka, southern India. Enumeration of all woody plants >= 1 cm DBH (diameter at breast height) yielded a total of 1766 individuals that belonged to 46 species, 37 genera and 24 families. Combretaceae was the most abundant family in the forest with a family importance value of 68.3. Plant density varied from 20 - 90 individuals with an average 35 individuals/quadrat (20 m x 20 m). Randia dumetorum, with 466 individuals (representing 26.7 % of the total density 2 ha(-1)) with species importance value of 36.25, was the dominant species in the plot. The total basal area of the plot was 18.09 m(2) ha(-1) with a mean of 0.72 m(2) quadrat(-1). The highest basal area of the plot was contributed by Combretaceae (12.93 m(2) 2 ha(-1)) at family level and Terminalia tomentosa (5.58 m(2) 2 ha(-1)) at species level. The lowest diameter class (1-10 cm) had the highest density (1054 individuals 2 ha(-1)), but basal area was highest in the 80 - 90 cm diameter class (5.03m(2) 2 ha(-1)). Most of the species exhibited random or aggregated distribution over the plot. This study provides a baseline information on the dry forests of Bhadra Wildlife Sanctuary.

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Foliage density and leaf area index are important vegetation structure variables. They can be measured by several methods but few have been tested in tropical forests which have high structural heterogeneity. In this study, foliage density estimates by two indirect methods, the point quadrat and photographic methods, were compared with those obtained by direct leaf counts in the understorey of a wet evergreen forest in southern India. The point quadrat method has a tendency to overestimate, whereas the photographic method consistently and ignificantly underestimates foliage density. There was stratification within the understorey, with areas close to the ground having higher foliage densities.

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While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

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When freshly eclosed females of the primitively eusocial wasp, Rapalidia marginata are isolated into individual cages, only about half of them build nests and lay eggs and those that do so take a long and variable amount of time (Mean +/- SD = 66 +/- 37 days) before they lay their first egg. Part of the reason for this delay is because, when kept in isolation, no wasp begins to lay eggs during a period of approximately 82 days from mid - October to early January. Wasps maintained at a constant temperature of 26 +/- 1-degrees-C however initiate egg laying throughout the year, suggesting that the low temperatures during mid - October to early January may be at least one factor that makes this period unfavourable for wasps maintained at room temperature. Egg laying continues more or less normally throughout October-January however, in all natural and laboratory colonies studied. Natural colonies of R. marginata are initiated throughout the year and often by groups of females. Huddling together is a striking feature of the wasps especially on cold mornings. We therefore suggest that the isolated animals in our experiment are unable to lay eggs during the coldest part of the year because of their inability to huddle together, share metabolic heat and perform "co-operative thermoregulation". Such "co-operative thermoregulation" may thus be another factor that facilitates the evolution of socialitly.

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Due to large scale afforestation programs and forest conservation legislations, India's total forest area seems to have stabilized or even increased. In spite of such efforts, forest fragmentation and degradation continues, with forests being subject to increased pressure due to anthropogenic factors. Such fragmentation and degradation is leading to the forest cover to change from very dense to moderately dense and open forest and 253 km(2) of very dense forest has been converted to moderately dense forest, open forest, scrub and non-forest (during 2005-2007). Similarly, there has been a degradation of 4,120 km(2) of moderately dense forest to open forest, scrub and non-forest resulting in a net loss of 936 km(2) of moderately dense forest. Additionally, 4,335 km(2) of open forest have degraded to scrub and non-forest. Coupled with pressure due to anthropogenic factors, climate change is likely to be an added stress on forests. Forest sector programs and policies are major factors that determine the status of forests and potentially resilience to projected impacts of climate change. An attempt is made to review the forest policies and programs and their implications for the status of forests and for vulnerability of forests to projected climate change. The study concludes that forest conservation and development policies and programs need to be oriented to incorporate climate change impacts, vulnerability and adaptation.

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Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m(2)/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (-5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (-2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS-a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.

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This paper reviews integrated economic and ecological models that address impacts and adaptation to climate change in the forest sector. Early economic model studies considered forests as one out of many possible impacts of climate change, while ecological model studies tended to limit the economic impacts to fixed price-assumptions. More recent studies include broader representations of both systems, but there are still few studies which can be regarded fully integrated. Full integration of ecological and economic models is needed to address forest management under climate change appropriately. The conclusion so far is that there are vast uncertainties about how climate change affects forests. This is partly due to the limited knowledge about the global implications of the social and economical adaptation to the effects of climate change on forests.

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Under the project `Seasonal Prediction of the Indian Monsoon' (SPIM), the prediction of Indian summer monsoon rainfall by five atmospheric general circulation models (AGCMs) during 1985-2004 was assessed. The project was a collaborative effort of the coordinators and scientists from the different modelling groups across the country. All the runs were made at the Centre for Development of Advanced Computing (CDAC) at Bangalore on the PARAM Padma supercomputing system. Two sets of simulations were made for this purpose. In the first set, the AGCMs were forced by the observed sea surface temperature (SST) for May-September during 1985-2004. In the second set, runs were made for 1987, 1988, 1994, 1997 and 2002 forced by SST which was obtained by assuming that the April anomalies persist during May-September. The results of the first set of runs show, as expected from earlier studies, that none of the models were able to simulate the correct sign of the anomaly of the Indian summer monsoon rainfall for all the years. However, among the five models, one simulated the correct sign in the largest number of years and the second model showed maximum skill in the simulation of the extremes (i.e. droughts or excess rainfall years). The first set of runs showed some common bias which could arise either from an excessive sensitivity of the models to El Nino Southern Oscillation (ENSO) or an inability of the models to simulate the link of the Indian monsoon rainfall to Equatorial Indian Ocean Oscillation (EQUINOO), or both. Analysis of the second set of runs showed that with a weaker ENSO forcing, some models could simulate the link with EQUINOO, suggesting that the errors in the monsoon simulations with observed SST by these models could be attributed to unrealistically high sensitivity to ENSO.

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We have examined the monthly variations in sperm output and attempted to correlate the profiles of endocrine hormones secreted with the sperm counts throughout the ,year in the adult male bonnet monkey. As previously reported, there was a distinct spurt in sperm output beginning September through December months. A concomitant increase in serum testosterone and prolactin concentrations were also noted during September through November (mid and post-monsoon season). Although there was a marked increase in gonadotropin releasing hormone stimulated testosterone secretion, the peak testosterone concentrations post gonadotropin releasing hormone injection did not vary significantly (P>0.05) throughout the year. Basal serum follicle stimulating hormone concentrations did not vary significantly (P>0.05) during April to June months compared to September-November months. Serum inhibin concentration remained unaltered throughout the year, except in the month of March. The results of this study provide evidence for annual rhythms in prolactin and testosterone secretion and a distinct seasonality in the sperm output of the adult male bonnet monkey, but the pituitary responsiveness to exogenous gonadotropin releasing hormone remains unaltered throughout the year. Because of the existence of seasonality as noted in the present study, future studies which utilize the adult male bonnet monkey as an experimental model need to take into consideration the seasonal effects on reproductive function in this species.