Impact of climatic parameters on the extent of mangrove forests of southern Iran

Mangrove forests play a valuable role in maintaining the coastal ecosystem. Global warming alongside human activities has caused reduced extent and health of these ecosystems in recent years. This study aimed to examine the variability of the extent of mangrove forests and the sea surface area in response to changes in climatic parameters in the south of Iran. To achieve this, the climatic data recorded at Bandar Abbas Synoptic Weather Station and Landsat series of satellite images were used. To detect the trends of meteorological parameters during 1987-2017, the modified Man-Kendall test and the Sen’s slope estimator were employed. We investigated the regression relationship between climatic parameters as well as the sea surface area and the mangrove forest extent. The results showed that mangrove forest extent was about 73.08 km2 in the first year of study (1987), which increased to 88.73 km2 (21%) in 2017. The minimum temperature (Z = 2.77, β = 0.0186), maximum temperature (Z = 2.066, β = 0.0362), and the extent of the mangrove forests (Z = 2.58, β = 0.0405) displayed significantly growing trends. In contrast, the mean temperature, precipitation, relative humidity, and the sea surface area had no significant trends during the study period. The minimum temperature presented the highest correlation coefficient with the mangrove forest extent (61%). It is expected, therefore, along with global warming and increasing minimum temperature, the extent of mangrove forests would have a growing trend in the south of Iran in the future. The results of this study can be used by natural resources and forest managers to determine the best place for afforestation in order to perform better protection of these forests

Throughfall Nutrients in a Degraded Indigenous Fagus Orientalis Forest and a Picea Abies Plantation in the of North of Iran

Aim of study: The objective of this study was to compare the quantity and quality of TF (throughfall) in an indigenous, but degraded, stand of Fagus orientalis and Picea abies plantation. Area of study: Forests of Kelar-Dasht region located in Mazandaran province, northern Iran. Material and Methods: TF measured by twenty collectors that were distributed randomly underneath each stand. For 21 storms sampled in 2012 (August-December) and 2013 (April-June), we analyzed pH, EC, Ca2+, Mg2+, K+, NO3-, and P of gross rainfall (GR) and TF. Main results: Cumulative interception (I) for F. orientalis and P. abies were 114.2 mm and 194.8 mm of the total GR, respectively. The amount of K+ (13.4 mg L-1) and Ca2+ (0.9 mg L-1) were higher (for both elements, p = 0.001) in the TF of P. abies compared to those of F. orientalis (6.8 and 0.5, mg L-1, respectively) and GR (3.2 and 0.37 mg L-1, respectively). Conversely, mean P concentration was doubled (p = 0.022) in the TF of F. orientalis (11.1 mg L-1) compared to GR (5.8 mg L-1). Research highlights: P. abies plantations may provide a solution for reforestation of degraded F. orientalis forests of northern Iran, yet how P. abies plantations differentially affect the quality and quantity of rainfall reaching subcanopy soils (TF) compared to F. orientalis is unknown. Understanding the connection between hydrological processes and nutrient cycling in forest ecosystems is crucial for choosing the appropriate species to rehabilitate the degraded indigenous forests with nonindigenous species

Seasonal variations of throughfall chemistry in pure and mixed stands of Oriental beech (Fagus orientalis Lipsky) in Hyrcanian forests (Iran)

International audienceAbstractKey messageThroughfall nutrient fluxes were generally higher in a mixed stand than in a pure stand of Oriental beech. Throughfall fluxes were higher than bulk precipitation fluxes except for nitrogen and indicate higher canopy uptake of this element in the pure stand compared to the mixed stand.ContextOriental beech is an economically relevant tree species for Iran and adjacent countries. Yet little is known about nutrient cycling in Oriental beech stands and the influence of the degree of mixture with other species.AimsWe assessed the effect of seasons on nutrient fluxes in precipitation and whether throughfall chemistry differed between pure and mixed stands.MethodsBulk precipitation in the open field and throughfall were sampled during one whole month within each season from August 2013 to May 2014 in a pure (81 % of beech trees on average) and a mixed stand (57 % of beech trees) of Oriental beech. Samples were analysed for pH, nitrate (NO3−), ammonium (NH4+), phosphorus (P), calcium (Ca2+), magnesium (Mg2+) and potassium (K+).ResultsNutrient concentrations were generally higher in the growing season than in the dormant season, both in bulk precipitation and in throughfall. Nutrient fluxes were higher in fall and these peaks coincided with higher amounts of precipitation. The concentrations and fluxes of NH4+, NO3−, P, Ca2+, Mg2+ and K+ were generally higher in the mixed stand than in the pure stand in all seasons. Compared to the open field, throughfall fluxes were usually higher, except for NO3− and NH4+, indicating direct canopy uptake of nitrogen.ConclusionCanopy composition in Oriental beech stands (owing to differences in foliage chemistry) and seasons (owing to differences in precipitation regime and phenological stages) have a significant effect on throughfall nutrient fluxes

Canopy water storage capacity and it`s effect on rainfall interception in a Pinus eldarica plantation in a semi-arid climate zone

Forest canopy rainfall interception loss (I) and canopy water storage capacity (S) are important components of the water balance in arid and semi-arid climate zones. The goal of this research was to quantify S and free throughfall (p) in a mature Pinus eldarica Medw. afforestation planted in the Chitgar Forest plantation near Tehran, Iran. Measurements of gross precipitation (GR (n=6)) and throughfall (TF (n=45)) were recorded on an event basis from September 2009 to April 2010. I was calculated as the difference between GR and TF. For the measurement period, GR totaled 164.8 mm and rainfall interception loss (I) was 61.2 mm. In this study S was estimated as 1.7 mm, 1.4 mm and 1.8 mm by methods of Leyton, Gash and Morton, and Pypker- Jackson, respectively. Free throughfall (p) was estimated 0.1422. I was estimated 44% and 91.3% of total GR for rainfall events sufficient to saturate the canopy (GR>1.6 mm) and insufficient to saturate the canopy (GR>1.6 mm), respectively. The results demonstrate that canopy storage capacity represents a considerable portion of intercepted rainfall from GR in P. eldarica plantation regions of the semi-arid climate zone of Iran where soil moisture is a limiting factor on plant growth and productivity

Chemical composition of throughfall in Pinus eldarica and Cupressus arizonica plantations in a polluted area (Case study: Chitgar forest park)

This research was carried out to compare the chemical composition of throughfall (TF), i.e., lead (Pb) and cadmium (Cd) as well as electrical conductivity (EC) and acidity (pH) beneath Pinus eldarica and Cupressus arizonica plantations with open field rainfall in the Chitgar Forest Park. The open field rainfall and TF were collected by 10 and 60 manual cylindrical plastic collectors, respectively. ICP was used in order to measure the concentrations of Pb and Cd. Three rainfall events were measured for chemical analysis. Pb and Cd concentrations as well as EC of TF were significantly different among Pinus eldarica, Cupressus arizonica, and the open field rainfall (P. eldarica: 74.07 ppb, 13.25 ppb, and 298 mµ; C. arizonica: 49.98 ppb, 10.75 ppb, and 251 mµ; open field rainfall: 27.22 ppb, 8.55 ppb, and 90.5 mµ). pH showed a significant difference between Pinus eldarica and the open field rainfall. Concerning the efficiency of plantation canopy for cleaning Pb and Cd concentrations of the atmosphere, changes in the amount of chemical compositions will provide an insight into the multiple criteria of selecting species for plantation projects in polluted urban areas

National assessment of throughfall sensitivity to changes in storm magnitude for the forests of Iran

Aim of study: To understand throughfall (TF) sensitivity to variability in rainfall amount (Pg) for typical forest sites across the main climate types of Iran. Area of study: Nine forest stands of several common native and introduced tree species situated in all common Iranian climate types, but located primarily in northern Iran. Material and methods: A nondimensional relative sensitivity coefficient was employed to predict responses of TF to Pg changes. Projected Pg changes over the measurement sites for the period 2020-50 were estimated using one of the Coupled Model Intercomparison Project phase 5 (CMIP5) known as HadGEM2-ES under low and high emission scenarios (RCP 2.6 and 8.5). Main results: TF displayed strong positive linear relationships with Pg at all sites [TF=0.66 Pg -0.16; R2=0.91]. The sensitivity coefficient ranged from 0.96-2.35 across the nine forest sites and large sensitivity coefficientdifferences were found between small ( mean annual Pg) storms for arid and Mediterranean plantations. Shifts in Pg and increased small storm frequency are predicted for these regions (2020-50) under low and high emission scenarios. Research highlights: TF sensitivity may be a useful variable when selecting tree species for afforestation to buffer expected shifts in Pg due to climate change. Keywords: climate change; forest ecosystems; precipitation projection; throughfall sensitivity

National assessment of throughfall sensitivity to changes in storm magnitude for the forests of Iran

Aim of study: To understand throughfall (TF) sensitivity to variability in rainfall amount (Pg) for typical forest sites across the main climate types of Iran.Area of study: Nine forest stands of several common native and introduced tree species situated in all common Iranian climate types, but located primarily in northern Iran.Material and methods: A nondimensional relative sensitivity coefficient was employed to predict responses of TF to Pg changes. Projected Pg changes over the measurement sites for the period 2020-50 were estimated using one of the Coupled Model Intercomparison Project phase 5 (CMIP5) known as HadGEM2-ES under low and high emission scenarios (RCP 2.6 and 8.5).Main results: TF displayed strong positive linear relationships with Pg at all sites [TF=0.66 Pg -0.16; R2=0.91]. The sensitivity coefficient ranged from 0.96-2.35 across the nine forest sites and large sensitivity coefficientdifferences were found between small ( mean annual Pg) storms for arid and Mediterranean plantations. Shifts in Pg and increased small storm frequency are predicted for these regions (2020-50) under low and high emission scenarios.Research highlights: TF sensitivity may be a useful variable when selecting tree species for afforestation to buffer expected shifts in Pg due to climate change.Keywords: climate change; forest ecosystems; precipitation projection; throughfall sensitivity

Tree-based estimation of canopy water storage capacity and direct throughfall coefficient of Cupressus arizonica Green.

The aim of this study was to estimate the individual tree-based 1) canopy water storage capacity (S), 2)  ratio of mean evaporation rate from the wet canopy to the mean rainfall intensity () by the Pereira method, and 3) direct throughfall coefficient (p) for Cupressus arizonica trees. The trees wereafforested in the Chitgar forest park in Tehran which is classified as a semiarid region. Measurements were carried out from February 2011 to February 2012. To measure the gross rainfall (GR), six rain-gauges were installed in an open space adjacent to the trees. Throughfall  (TF) was measured using a number of twenty rain-gauges located under the crown of five individual trees. Rainfall interception (I) was calculated as the difference between GR and TF. During the measurement period, 55 rainfall events were recorded with a cumulative depth of 234 mm. The C. arizonica trees intercepted 21.8% and 32.1% of the incident rainfall on cumulative-based and event-based (each GR) manner, respectively. Positive and negative power correlations were observed between I and GR (r = 0.89)as well as between(I: GR) % and GR (r = 0.69) for the mean value of five individual trees. Mean values of S,, and p were estimated as 0.38 mm, 0.14, and 0.46, respectively. I and its elements (), S, and p as well as transpiration of trees are, therefore concluded as necessary parameters to be considered when selecting suitable species for afforestation projects in the arid and semiarid zone. In addition and as a key parameter for calculating I, S can be optimally estimated by Pereira method which is exclusively proposed for tree-based measurements

Improving Princeton Forcing Dataset over Iran Using the Delta-Ratio Method

In this study, we corrected the bias in the Princeton forcing dataset, i.e., precipitation, maximum and minimum temperatures, and wind speed, by adjusting its long-term mean monthly climatology to match observations for the period 1988–2012 using the delta-ratio method. To this end, we collected meteorological data from 97 stations covering the domain of Iran. We divided Iran into three climatic zones based on the De Martonne classification, i.e., Arid, Humid, and Per-Humid zones, and then applied the delta-ratio method for each climatic zone separately to adjust the bias. After adjustment, the new datasets were compared to the observations in 1958–1987. Results based on four skill scores, including the Nash Sutcliffe efficiency (NSE), percent bias (PBIAS), root-mean-square error (RMSE), and R2, indicate that the adjustment greatly improved the quality of the gridded dataset, specifically, precipitation, maximum temperature, and wind speed. For example, NSE for annual precipitation during the validation time period increased from −0.03 to 0.72, PBIAS reduced from 29.2% to 6.6%, RMSE decreased by 182.44 mm, and R2 increased from 0.06 to 0.75. Assessing the results in different climatic zones of Iran reveals that precipitation improved more significantly in the Per-Humid zone followed by the Humid zone, while maximum temperature improved better in the Arid areas. For wind speed, the values improved comparably in the three climate zones. However, the delta values for monthly minimum temperature calculated during the adjustment time period cannot be applied in the validation time period, due to the fact that the Princeton climate data cannot follow the behavior of minimum temperature during the validation phase. In short, we showed that a simple bias adjustment approach, along with minimum observed station data, can significantly improve the performance of global gridded datasets