Mangrove litter fall: Extrapolation from traps to a large tropical macrotidal harbour

Mangrove litter is a major source of organic matter for detrital food chains in many tropical coastal ecosystems, but scant attention has been paid to the substantial challenges in sampling and extrapolation of rates of litter fall. The challenges arise due to within-stand heterogeneity including incomplete canopy cover, and canopy that is below the high tide mark. We sampled litter monthly for three years at 35 sites across eight mapped communities in the macrotidal Darwin Harbour, northern Australia. Totals were adjusted for mean community canopy cover and the occurrence of canopy below the high tide mark. The mangroves of Darwin Harbour generate an estimated average of 5.0 t ha⁻¹ yr⁻¹ of litter. This amount would have been overestimated by 32% had we not corrected for limited canopy cover and underestimated by 11% had we not corrected for foliage that is below the high tide mark. Had we made neither correction, we would have overestimated litter fall by 17%. Among communities, rates varied 2.6-fold per unit area of canopy, and 3.9-fold among unit area of community. Seaward fringe mangroves were the most productive per unit of canopy area but the canopy was relatively open; Tidal creek forest was the most productive per unit area of community. Litter fall varied 1.1-fold among years and 2.0-fold among months though communities exhibited a range of seasonalities. Our study may be the most extensively stratified and sampled evaluation of mangrove litter fall in a tropical estuary. We believe our study is also the first such assessment to explicitly deal with canopy discontinuities and demonstrates that failure to do so can result in considerable overestimation of mangrove productivity.     

Photosynthetic response to different light intensities, water status and leaf age of two Berberis species (Berberidaceae) of Patagonian steppe, Argentina

Net photosynthetic rate (A) and stomatal conductance (gs) from leaves of Berberis buxifolia and Berberis heterophylla saplings were measured under different conditions of radiation and water availability and for leaves of different ages. Comparative studies of basic physiological performance would give insight how these shrubs survive and grow under this austral extreme ecosystem. B. buxifolia had higher A values than B. heterophylla for all light intensities measured. Values of gs for both Berberis species also declined as light intensity decreased. There was a negative relationship between A and water stress expressed as pre-dawn leaf water potential (ψ_lp) where the reduction in gs was the main factor that reduced A in both species. Also, A and gs of Berberis plants increased rapidly during the first days after leaf unfolding, reached a maximum value when the leaf was completely expanded, and then declined. These results could be used to estimate the responses of saplings to environmental conditions under the dynamic of natural stands in this austral extreme ecosystem and for restoration plans.     

Vegetation-groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data

Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well-suited for long-term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep-rooted, non-native tamarisk shrubs (Tamarix sp.). After the introduction of the tamarisk beetle (Diorhabda sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape-scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000–2009) and after (2010–2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% (p < .001), while ET decreased 26% from the pre- to post-beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 (r² = .71; p = .009). Tamarisk greenness (a proxy for health) was significantly affected by Diorhabda but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period.     

福建铁观音茶园生态地球化学特征

东南沿海是铅等重金属的地球化学高背景区。该地区广泛分布酸性红壤,酸雨沉降、不适当施肥导致土壤酸化以及由此引发土壤重金属生态风险令人关注。以福建省铁观音主产区为研究区,采集了79个茶园的表层和亚表层土壤样、茶叶样品,测定了重金属元素以及土壤常量元素和理化指标。研究表明,福建铁观音茶园土壤中Hg、Pb、Se、Zn高含量主要由地质背景所引起,土壤常量组分、有机质、酸碱度等理化条件对土壤元素含量有一定的影响;铁观音茶树老叶中As、Cd、Cr、Hg、Se、Pb、F等非植物营养元素含量明显高于嫩叶,显示这些元素随植物生长逐渐累积的特征,而嫩叶中植物生长必需的营养元素Cu、(Ni)、Zn则高于老叶,反映出微量营养元素在茶叶生长部位相对富集的特征;多数情况下土壤与茶叶间元素含量相关性差,说明茶树对土壤元素的吸收累积受到多种复杂因素的影响。研究表明茶叶与土壤Pb、Cr具有显著正相关性,为建立铅污染土壤生态效应预测评价模型提供了基础依据。     

Effect of leaf distribution pattern on the interception storage capacity of leaf litter under simulated rainfall conditions

Rainwater interception by leaf litter is an important part of forest hydrological processes. The objective of this study was to investigate the interception storage capacity (ISC) of woodland leaf litter for three leaf distribution patterns, one flow path, two flow paths, and three flow paths, manually simulated via one-by-one leaf connection in the top leaf litter layer. A random pattern served as the control. Three different slopes (0°, 5° and 25°, representing flat, gentle and steep slopes, respectively) and two contrasting leaf litters (needle-leaf litter, represented by P. massoniana leaves, and broad-leaf litter, represented by C. camphora leaves) with a biomass of 0.5 kg/m² per unit area were applied, at a rainfall intensity of 50 mm/h. Results suggested that leaf distribution pattern greatly impacts litter drainage and hence affects leaf litter ISC. The delaying capacity of litter drainage initiation and ISC of broad-leaf litter were higher than those of needle-leaf litter under the same slope conditions. The maximum ISC (C_max) and minimum ISC (C_min) of leaf litter at flat and gentle slopes were higher than those at steep slope. C_min of the broad-leaf litter was two times higher than that of needle-leaf litter on average. When raindrops reached the litter layer, some were temporarily intercepted by the top litter layer while others infiltrated leaf litter sublayer along leaf edges, and in the process, some rainwater flowed through litter layer and contributed to lateral litter drainage along the potential flow path formed by leaves. The lateral litter drainage of broad-leaf litter was higher than that of needle-leaf litter, and the partitioning of rainwater into lateral litter drainage increased with increases in slope. The difference in leaf litter C_max among different slopes and leaf shapes decreased with flow path increasing. Therefore, leaf distribution pattern notably impact leaf litter ISC, which is similar to leaf shape and slope impacts. On inclined slopes, avoiding leaf accumulation to form flow path is helpful for improving ISC.     

Assessing community vulnerability: A study of the mountain pine beetle outbreak in British Columbia, Canada

Arguing that community-based assessments of vulnerability to climate change are congruent with the scale at which policy action takes place, this paper presents an assessment of vulnerability conducted in forest-based communities surrounded by a catastrophic outbreak of forest disease. Our assessment includes measures of several dimensions of vulnerability, developed using an interdisciplinary and participatory research process. We find that for some communities vulnerability represents a high level of economic risk, while for others risk is exacerbated by institutional limitations. We also find that community perceptions of risk and bio-physical assessments differ widely for communities anticipating future outbreaks of disease.     

Estimation of evapotranspiration and its components from an apple orchard in northwest China using sap flow and water balance methods

Field experiments were conducted to investigate the effects of leaf area index and soil moisture content on evapotranspiration and its components within an apple orchard in northwest China for 2 years. Evapotranspiration in the non‐rainfall period was estimated using two approaches: the soil water balance method based on tube‐type time‐domain reflection measurements, and sap flow plus micro‐lysimeter methods. The two methods were in good agreement, with differences usually less than 10%. The components of evapotranspiration varied with canopy development. During spring and autumn, soil evaporation was dominating as result of low leaf area index. In summer, plant transpiration became significant, with an average transpiration to evapotranspiration ratio of 0·87. The crop coefficient K_c showed a strong linear dependence on leaf area index. The water stress coefficient K_s was around 1·0 when soil moisture was above 23% and started to decrease linearly after that. This study demonstrates that prediction of evapotranspiration in apple orchards can be made using the Food and Agriculture Organization's crop coefficient method from commonly available meteorological data in the area. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation of potential evapotranspiration in the mountainous Panama Canal watershed

Spatially distributed hydrometeorological and plant information within the mountainous tropical Panama Canal watershed is used to estimate parameters of the Penman–Monteith evapotranspiration formulation. Hydrometeorological data from a few surface climate stations located at low elevations in the watershed are complemented by (a) typical wet‐ and dry‐season fields of temperature, wind, water vapour and pressure produced by a mesoscale atmospheric model with a 3 × 3 km² spatial and hourly temporal resolution, and (b) leaf area index fields estimated over the watershed during a few years using satellite data with two different spatial and temporal resolutions. The mesoscale model estimates of spatially distributed surface hydrometeorological variables provide the basis for the extrapolation of the surface climate station data to produce input for the Penman–Monteith equation. The satellite information and existing digital spatial databases of land use and land cover form the basis for the estimation of Penman–Monteith spatially distributed parameter values. Spatially distributed 3 × 3 km² potential evapotranspiration estimates are obtained for the 3300 km² Panama Canal watershed. Estimates for Gatun Lake within the watershed are found to reproduce well the monthly and annual lake evaporation obtained from submerged pans. Sensitivity analysis results of potential evapotranspiration estimates with respect to cloud cover, dew formation, leaf area index distribution and mesoscale model estimates of surface climate are presented and discussed. The main conclusion is that even the limited spatially distributed hydrometeorological and plant information used in this study contributes significantly toward explaining the substantial spatial variability of potential evapotranspiration in the watershed. These results also allow the determination of key locations within the watershed where additional surface stations may be profitably placed. Copyright © 2006 John Wiley & Sons, Ltd.     

A conceptual model of water yield effects from beetle‐induced tree death in snow‐dominated lodgepole pine forests

In regions of western North America with snow‐dominated hydrology, the presence of forested watersheds can significantly influence streamflow compared to areas with other vegetation cover types. Widespread tree death in these watersheds can thus dramatically alter many ecohydrologic processes including transpiration, canopy solar transmission and snow interception, subcanopy wind regimes, soil infiltration, forest energy storage and snow surface albedo. One of the more important causes of conifer tree death is bark beetle infestation, which in some instances will kill nearly all of the canopy trees within forest stands. Since 1996, an ongoing outbreak of bark beetles (Coleoptera: Scolytidae) has caused widespread mortality across more than 600,000 km² of coniferous forests in western North America, including numerous Rocky Mountain headwaters catchments with high rates of lodgepole pine (Pinus contorta) mortality from mountain pin beetle (Dendroctonous ponderosae) infestations. Few empirical studies have documented the effects of MPB infestations on hydrologic processes, and little is known about the direction and magnitude of changes in water yield and timing of runoff due to insect‐induced tree death. Here, we review and synthesize existing research and provide new results quantifying the effects of beetle infestations on canopy structure, snow interception and transmission to create a conceptual model of the hydrologic effects of MPB‐induced lodgepole pine death during different stages of mortality. We identify the primary hydrologic processes operating in living forest stands, stands in multiple stages of death and long‐dead stands undergoing regeneration and estimate the direction of change in new water yield. This conceptual model is intended to identify avenues for future research efforts. Copyright © 2012 John Wiley & Sons, Ltd.     

A fusion-based neural network methodology for monthly reservoir inflow prediction using MODIS products

ABSTRACT

A model fusion approach was developed based on five artificial neural networks (ANNs) and MODIS products. Static and dynamic ANNs – the multi-layer perceptron (MLP) with one and two hidden layers, general regression neural network (GRNN), radial basis function (RBF) and nonlinear autoregressive network with exogenous inputs (NARX) – were used to predict the monthly reservoir inflow in Mollasadra Dam, Fars Province, Iran. Leaf area index and snow cover from MODIS, and rainfall and runoff data were used to identify eight different combinations to train the models. Statistical error indices and the Borda count method were used to verify and rank the identified combinations. The best results for individual ANNs were combined with MODIS products in a fusion model. The results show that using MODIS products increased the accuracy of predictions, with the MLP with two hidden layers giving the best performance. Also, the fusion model was found to be superior to the best individual ANNs.