Himalayan ‘Ecotone’ temperate conifer forest is the cradle of life for human survival and wildlife existence. Human intervention and climate change are rapidly degrading and declining this transitional zone. This study aimed to quantify the floristic structure, important value index (IVI), topographic and edaphic variables between 2019 and 2020 utilizing circular quadrant method (10m × 10m). The upper-storey layer consisted of 17 tree species from 12 families and 9 orders. Middle-storey shrubs comprise 23 species representing 14 families and 12 orders. A total of 43 species of herbs, grasses, and ferns were identified from the ground-storey layer, representing 25 families and 21 orders. Upper-storey vegetation structure was dominated by Pinus roxburghii (22.45%), while middle-storey vegetation structure was dominated by Dodonaea viscosa (7.69%). However, the ground layer vegetation was diverse in species composition and distribution. By using Ward’s agglomerative clustering technique, the floral vegetation structure was divided into three floral communities. Ailanthus altissima, Pinus wallichiana, and P. roxburghii had the highest IVI values in Piro–Aial (Group 2), Piwa–Quin (Group 3) and Aial–Qugal (Group 2). The IVI values for Aesculus indica, Celtis australis, and Quercus incana in Aial-Qugal (Group 2) were not determined. Nevertheless, eleven of these species had 0 IVI values in Piro–Aial (Group 2) and Piwa–Quin (Group 3). Based on the CCA ordination biplot, significant differences were observed in floral characteristics and distribution depending on temperature, rainfall, soil pH, altitude, and topographic features. Based on Ward’s agglomerative clustering, it was found that Himalayan ‘Ecotone’ temperate conifer forests exhibit a rich and diverse floristic structure.

Globalization and economic integration have an impact on increasing trade volume and economic growth in various countries, especially those that are open in their economies. This situation also provides ease of capital mobility between countries, which makes investment not only rely on domestic investment but also on foreign direct investment. Exchange rates and inflation also affect export growth, imports, and economic growth. The purpose of this study is to determine the effect of exchange rate, inflation, foreign direct investment, government expenditure, and economic openness on export and import growth.  This study used time series data during the period 1980–2021, sourced from UNCTAD, ASYB, and Indonesian Central Bank (BI). The analysis model used is multiple linear regression with the help of EViews software, which first tests classical assumptions so that the regression results are Best Linier Unbiased Estimator (BLUE). The results show that foreign direct investment and government spending can significantly increase the rate of exports and imports. Meanwhile, the depreciating rupiah against the US dollar cannot encourage an increase in both exports and imports. Furthermore, foreign direct investment, government spending, and economic openness can significantly increase economic growth. The other variables, net exports and inflation, have no effect on Indonesia’s economic growth rate.