Short‐term responses of birds to prescribed fire in Combretum woodland in Tarangire National Park, Northern Tanzania

2021 ◽  
Author(s):  
Chacha Werema
Keyword(s):  
Prescribed Fire ◽  
National Park ◽  
Short Term ◽  
Northern Tanzania ◽  
Tarangire National Park

scholarly journals Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 95
Author(s):  
Yuan Gong ◽  
Christina L. Staudhammer ◽  
Susanne Wiesner ◽  
Gregory Starr ◽  
Yinlong Zhang
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Prescribed Fire ◽  
Water Availability ◽  
Longleaf Pine ◽  
Growing Season ◽  
Soil Water Availability ◽  
Future Climate Change ◽  
Short Term ◽  
Phenological Model

Understanding plant phenological change is of great concern in the context of global climate change. Phenological models can aid in understanding and predicting growing season changes and can be parameterized with gross primary production (GPP) estimated using the eddy covariance (EC) technique. This study used nine years of EC-derived GPP data from three mature subtropical longleaf pine forests in the southeastern United States with differing soil water holding capacity in combination with site-specific micrometeorological data to parameterize a photosynthesis-based phenological model. We evaluated how weather conditions and prescribed fire led to variation in the ecosystem phenological processes. The results suggest that soil water availability had an effect on phenology, and greater soil water availability was associated with a longer growing season (LOS). We also observed that prescribed fire, a common forest management activity in the region, had a limited impact on phenological processes. Dormant season fire had no significant effect on phenological processes by site, but we observed differences in the start of the growing season (SOS) between fire and non-fire years. Fire delayed SOS by 10 d ± 5 d (SE), and this effect was greater with higher soil water availability, extending SOS by 18 d on average. Fire was also associated with increased sensitivity of spring phenology to radiation and air temperature. We found that interannual climate change and periodic weather anomalies (flood, short-term drought, and long-term drought), controlled annual ecosystem phenological processes more than prescribed fire. When water availability increased following short-term summer drought, the growing season was extended. With future climate change, subtropical areas of the Southeastern US are expected to experience more frequent short-term droughts, which could shorten the region’s growing season and lead to a reduction in the longleaf pine ecosystem’s carbon sequestration capacity.

scholarly journals Short-term effects of herbicides and a prescribed fire on restoration of a shrub-encroached pine savanna

2015 ◽  
Vol 23 (6) ◽  
pp. 909-917 ◽  
Author(s):  
William J. Platt ◽  
Alex K. Entrup ◽  
Emily K. Babl ◽  
Cody Coryell-Turpin ◽  
Viet Dao ◽  
...  
Keyword(s):  
Prescribed Fire ◽  
Short Term ◽  
Pine Savanna ◽  
Short Term Effects

scholarly journals Carbon Source Preference in Chemosynthetic Hot Spring Communities

2015 ◽  
Vol 81 (11) ◽  
pp. 3834-3847 ◽  
Author(s):  
Matthew R. Urschel ◽  
Michael D. Kubo ◽  
Tori M. Hoehler ◽  
John W. Peters ◽  
Eric S. Boyd
Keyword(s):  
High Temperature ◽  
National Park ◽  
Hot Springs ◽  
Dissolved Inorganic Carbon ◽  
Hot Spring ◽  
Affinity Constant ◽  
Rrna Gene ◽  
Organic Substrates ◽  
Short Term ◽  
Acetate Assimilation

ABSTRACTRates of dissolved inorganic carbon (DIC), formate, and acetate mineralization and/or assimilation were determined in 13 high-temperature (>73°C) hot springs in Yellowstone National Park (YNP), Wyoming, in order to evaluate the relative importance of these substrates in supporting microbial metabolism. While 9 of the hot spring communities exhibited rates of DIC assimilation that were greater than those of formate and acetate assimilation, 2 exhibited rates of formate and/or acetate assimilation that exceeded those of DIC assimilation. Overall rates of DIC, formate, and acetate mineralization and assimilation were positively correlated with spring pH but showed little correlation with temperature. Communities sampled from hot springs with similar geochemistries generally exhibited similar rates of substrate transformation, as well as similar community compositions, as revealed by 16S rRNA gene-tagged sequencing. Amendment of microcosms with small (micromolar) amounts of formate suppressed DIC assimilation in short-term (<45-min) incubations, despite the presence of native DIC concentrations that exceeded those of added formate by 2 to 3 orders of magnitude. The concentration of added formate required to suppress DIC assimilation was similar to the affinity constant (Km) for formate transformation, as determined by community kinetic assays. These results suggest that dominant chemoautotrophs in high-temperature communities are facultatively autotrophic or mixotrophic, are adapted to fluctuating nutrient availabilities, and are capable of taking advantage of energy-rich organic substrates when they become available.

scholarly journals Effect of burning on the numbers of questing ticks collected by dragging

2006 ◽  
Vol 73 (3) ◽  
Author(s):  
I.G. Horak ◽  
G.J. Gallivan ◽  
A.M. Spickett ◽  
A.L.F. Potgieter
Keyword(s):  
Tick Species ◽  
National Park ◽  
Host Preference ◽  
Term Effect ◽  
Kruger National Park ◽  
Ixodid Ticks ◽  
Short Term ◽  
Experimental Burn ◽  
Major Species ◽  
Questing Ticks

Sixteen experimental burn plot replicates, in groups of four, in four landscape zones of the Kruger National Park, South Africa, and from which wildlife are not excluded, have been subjected to fixed, regular burning regimens since 1954. In 1999, a study to determine the effect of burning on ixodid ticks questing for hosts from the vegetation of the plots was initiated, and six sub-plots, with identical histories, within each of two of the burn plot replicates in Combretum collinum / Combretum zeyheyri woodland on granite, were selected. With few exceptions these 12 sub-plots, as well as unburned vegetation adjacent to each of the replicates, were sampled for ticks at monthly intervals for a period of 39 months by dragging with flannel strips. The existing regimen of burning during August or during October on individual sub-plots was continued during this time. A total of 14 tick species was recovered from the plots of which nine could be considered major species. Sufficient numbers for statistical analysis of only eight species were, however, collected. Burning appeared to have little short-term effect on the number of ticks recovered. In the longer term, the response varied from no change, an increase, or a decrease in the numbers of ticks collected each year after burning. Tick species, life cycle, seasonality, questing strategy, host preference and host utilization of the habitat were important determinants of the effect of burning.

scholarly journals Prediksi Kunjungan Wisatawan Taman Nasional Gunung Merbabu dengan Time Series Forecasting dan LSTM

2020 ◽  
Vol 11 (2) ◽  
pp. 131
Author(s):  
Josua Manullang ◽  
Albertus Joko Santoso ◽  
Andi Wahju Rahardjo Emanuel
Keyword(s):  
Time Series ◽  
National Park ◽  
Short Term Memory ◽  
Lag Time ◽  
Time Series Forecasting ◽  
Mean Square ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

Abstract. Prediction of tourist visits of Mount Merbabu National Park (TNGMb) needs to be done to control the number of visitors and to preserve the national park. The combination of time series forecasting (TSF) and deep learning methods has become a new alternative for prediction. This case study was conducted to implement several methods combination of TSF and Long-Short Term Memory (LSTM) to predict the visits. In this case study, there are 18 modelling scenarios as research objects to determine the best model by utilizing tourist visits data from 2013 to 2018. The results show that the model applying the lag time method can improve the model's ability to capture patterns on time series data. The error value is measured using the root mean square error (RMSE), with the smallest value of 3.7 in the LSTM architecture, using seven lags as a feature and one lag as a label.Keywords: Tourist Visit, Taman Nasional Gunung Merbabu, Prediction, Recurrent Neural Network, Long-Short Term MemoryAbstrak. Prediksi kunjungan wisatawan Taman Nasional Gunung Merbabu (TNGMb) perlu dilakukan untul pengendalian jumlah pengunjung dan menjaga kelestarian taman nasional. Gabungan metode antara time series forecasting (TSF) dan deep learning telah menjadi alternatif baru untuk melakukan prediksi. Studi kasus ini dilakukan untuk mengimplementasi gabungan dari beberapa macam metode antara TSF dan Long-Short Term Memory (LSTM) untuk memprediksi kunjungan pada TNGMb. Pada studi kasus ini, terdapat 18 skenario pemodelan sebagai objek penelitian untuk menentukan model terbaik, dengan memanfaatkan data jumlah kunjungan wisatawan di TNGMb mulai dari tahun 2013 sampai dengan tahun 2018. Hasil prediksi menunjukkan pemodelan dengan menerapkan metode lag time dapat meningkatakan kemampuan model untuk menangkap pola pada data deret waktu. Besar nilai kesalahan diukur menggunakan root mean square error (RMSE), dengan nilai terkecil sebesar 3,7 pada arsitektur LSTM, menggunakan tujuh lag sebagai feature dan satu lag sebagai label. Kata Kunci: Kunjungan Wisatawan, Taman Nasional Gunung Merbabu, Prediksi, Recurrent Neural Network, Long-Short Term Memory

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