Thirty-two years of mangrove forest land cover change in Parita Bay, Panama

Mangrove forests have experienced a rapid decline. However, the rate of loss has decreased in recent years due to enhanced conservation and nature regeneration. The dynamics of mangrove forests in Panama have not been monitored since the year 2000, despite a significant loss during the 1980s. The objectives of our study were to quantify changes in mangrove cover and identify the dominant drivers of change in Parita Bay, Panama. Temporal changes in mangrove cover and the Normalized Difference Vegetation Index (NDVI) were determined using the supervised classification method on Landsat satellite images from 1987 to 2019. We identified a 4.7% increase in the mangrove area of Parita Bay during the 32 years; the mangrove forests were also considered healthy as reflected by high NDVI values. However, the conversion of mangroves to other land cover types resulted in a 1.26% decline in mangrove cover from 1987 to 1998. Moreover, the area of aquaculture and saltpans almost doubled during this period. During the following two decades, the conversion of other land cover classes (water, other vegetation, and bare soil) increased the mangrove area by 6%, and the annual rate of increase was greater during the second decade (0.43% year−1). From 2009 to 2019, mangroves declined at an annual rate of 0.11% in protected areas and increased at an annual rate of 0.50% in unprotected areas. Despite the regeneration potential of mangrove forests, our study highlights the need to continually manage and protect mangrove forests in order to facilitate their expansion in Parita Bay

PM2.5 reduction capacities and their relation to morphological and physiological traits in 13 landscaping tree species

© 2022 Elsevier GmbHFine particulate matter (PM2.5) is emerging as a serious environmental problem worldwide with the increase in anthropogenic emission sources, such as fossil fuels, transportation, and industries. In urban areas, where industrial complexes and human activities are concentrated, PM2.5 poses a threat to human health. Recently, because of their ability to reduce PM2.5, the introduction of landscaping trees as an environment-friendly solution has become popular; however, there remains a lack of research on the selection of species and their management. In this study, we quantified and compared the PM2.5 reduction capacities of 13 major landscaping tree species and analyzed their relationship with the morphological and physiological characteristics of each species. The results showed that the amount of PM2.5 reduction per leaf area differed among species and was the highest in Ginkgo biloba (28 165 ± 5353 # cm−2 min−1) and the lowest in Pinus strobus (1602 ± 186 # cm−2 min−1). Moreover, PM2.5 reduction by the broadleaf species (18 802 ± 1638 # cm−2 min−1) was approximately 8.6-fold higher than that of the needleleaf species (2194 ± 307 # cm−2 min−1). Correlation analysis revealed that differences in PM2.5 reduction were explained by differences in specific leaf area between species (P = 0.004) and by the length of margin per leaf area among individual trees (P < 0.05). Additionally, reduction in PM2.5 correlated with photosynthetic properties such as maximum assimilation and carboxylation rates (P < 0.001), indicating that PM2.5 is reduced not only by physical adsorption but also by physiological processes. These findings emphasize that for effective reduction in PM2.5 using landscaping trees, comprehensive consideration of the morphological and physiological characteristics of the species is essential during species selection, and that continuous management is also necessary to maintain the active physiological conditions of the trees.N

Influence of severe drought on mineral nutrient status in eastern white pine (Pinus strobus L)

AbstractThe photochemical process of photosynthesis is significantly influenced by the availability of nutrients. The purpose of this research is to ascertain how photosynthetic pigment function is affected by nutrient elemental changes caused by severe drought stress. Using elemental analysis, we looked at the changes in mineral nutrient composition in eastern white pine (Pinus strobus L) seedlings 32 days after drought treatment. According to our findings, severe drought resulted in a significant and non-significant decrease in the contents of Chl “b and a”, respectively. The elemental composition of iron (Fe), zinc (Zn), magnesium (Mg), potassium (K), phosphorus (P) and nitrogen (N) was measured. After severe drought treatment, leaf nutrient status showed a significant decline in total N (control-1.57 ± 0.1; drought-0.65 ± 0.07), P (control-959.4 ± 17; drought-645 ± 46), Mg (control-1030.4 ± 33; drought-750.7 ± 76), and K (control-3062.5 ± 32; drought-1853.3 ± 198), with a non-significant decrease in leaf Fe (control-120.3 ± 20; drought-98.9 ± 28) and increase in leaf Zn (control-33.49 ± 2; drought-39.05 ± 4). A positive correlation was found between the content of Fe, P, Mg, K, and N in leaf Chl “b”, but only a positive correlation was found between the content of Zn in leaf Chl “a” during severe drought. During severe drought, nutrient reallocation has a significant impact on leaf chlorophyll levels, as evidenced by this correlation

Identifying and extracting bark key features of 42 tree species using convolutional neural networks and class activation mapping

© 2022, The Author(s).The significance of automatic plant identification has already been recognized by academia and industry. There were several attempts to utilize leaves and flowers for identification; however, bark also could be beneficial, especially for trees, due to its consistency throughout the seasons and its easy accessibility, even in high crown conditions. Previous studies regarding bark identification have mostly contributed quantitatively to increasing classification accuracy. However, ever since computer vision algorithms surpassed the identification ability of humans, an open question arises as to how machines successfully interpret and unravel the complicated patterns of barks. Here, we trained two convolutional neural networks (CNNs) with distinct architectures using a large-scale bark image dataset and applied class activation mapping (CAM) aggregation to investigate diagnostic keys for identifying each species. CNNs could identify the barks of 42 species with > 90% accuracy, and the overall accuracies showed a small difference between the two models. Diagnostic keys matched with salient shapes, which were also easily recognized by human eyes, and were typified as blisters, horizontal and vertical stripes, lenticels of various shapes, and vertical crevices and clefts. The two models exhibited disparate quality in the diagnostic features: the old and less complex model showed more general and well-matching patterns, while the better-performing model with much deeper layers indicated local patterns less relevant to barks. CNNs were also capable of predicting untrained species by 41.98% and 48.67% within the correct genus and family, respectively. Our methodologies and findings are potentially applicable to identify and visualize crucial traits of other plant organs.Y

Down-Regulation of Photosynthesis to Elevated CO2 and N Fertilization in Understory Fraxinus rhynchophylla Seedlings

(1) Background: Down-regulation of photosynthesis has been commonly reported in elevated CO2 (eCO2) experiments and is accompanied by a reduction of leaf nitrogen (N) concentration. Decreased N concentrations in plant tissues under eCO2 can be attributed to an increase in nonstructural carbohydrate (NSC) and are possibly related to N availability. (2) Methods: To examine whether the reduction of leaf N concentration under eCO2 is related to N availability, we investigated understory Fraxinus rhynchophylla seedlings grown under three different CO2 conditions (ambient, 400 ppm [aCO2]; ambient × 1.4, 560 ppm [eCO21.4]; and ambient × 1.8, 720 ppm [eCO21.8]) and three different N concentrations for 2 years. (3) Results: Leaf and stem biomass did not change under eCO2 conditions, whereas leaf production and stem and branch biomass were increased by N fertilization. Unlike biomass, the light-saturated photosynthetic rate and photosynthetic N-use efficiency (PNUE) increased under eCO2 conditions. However, leaf N, Rubisco, and chlorophyll decreased under eCO2 conditions in both N-fertilized and unfertilized treatments. Contrary to the previous studies, leaf NSC decreased under eCO2 conditions. Unlike leaf N concentration, N concentration of the stem under eCO2 conditions was higher than that under ambient CO2 (4). Conclusions: Leaf N concentration was not reduced by NSC under eCO2 conditions in the understory, and unlike other organs, leaf N concentration might be reduced due to increased PNUE

Short-term severe drought influences root volatile biosynthesis in eastern white pine (Pinus strobus L)

Climate change-related drought stress is expected to shift carbon partitioning toward volatile organic compound (VOC) biosynthesis. The effect of drought stress on VOC synthesis remains unknown in several tree species. Therefore, we exposed eastern white pine (Pinus strobus) plants to severe drought for 32 days and performed physiological analysis (chlorophyll content, leaf water content, and root/shoot index), biochemical analysis (non-structural carbohydrates, proline, lipid peroxidation, and antioxidant assay), and total root VOC analysis. Drought stress decreased the relative water and soil moisture contents. Root proline accumulation and antioxidant activity increased significantly, whereas leaf chlorophyll synthesis and fresh weight decreased significantly in drought-treated plants. A non-significant increase in sugar accumulation (leaves and roots), proline accumulation (leaves), antioxidant activity (leaves), and lipid peroxidation (leaves and roots) was observed in drought-treated plants. Drought stress caused a non-significant decline in root/shoot ratio and starch accumulation (leaves and roots) and caused a significant increase in root abscisic acid content. Drought-treated plants showed an increase in overall monoterpene synthesis (16%) and decline in total sesquiterpene synthesis (3%). Our findings provide an overall assessment of the different responses of VOC synthesis to severe water deficit that may help unravel the molecular mechanisms underlying drought tolerance in P. strobus.Y