The effects of extreme climate on the invasive plant Gutenbergia cordifolia: implications for its future management in savannah ecosystems

Nyarobi, Herieth  Andrew; Ngondya, Issakwisa B.

doi:10.1016/j.heliyon.2022.e09172

Cited by 5 publications

(5 citation statements)

References 31 publications

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“…At the same time, increased rainfall variability is expected to lead to increased variation in the abundance of many key prey species for spotted hyenas (Moehlman et al, 2020). Climate change is also expected to affect the availability of suitable forage for herbivores by facilitating the spread of unpalatable invasive weeds during heavy rain events (Ngondya and Munishi, 2021;Nyarobi et al, 2022). Spotted hyenas are flexible in both their diet and hunting strategies (Hofer and East, 1993;Höner et al, 2002;Yirga et al, 2012) which should allow them to adjust to shifts in prey communities.…”

Section: Discussionmentioning

confidence: 99%

Effects of environmental change on population growth: monitoring time-varying carrying capacity in free-ranging spotted hyenas

Bailey,

Höner,

Davidian

et al. 2024

Preprint

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Trends in population sizes influence conservation decisions, but such trends can be misleading since a population can grow even as carrying capacity falls. Population growth requires population size to be below carrying capacity but is agnostic to trends in carrying capacity. We developed an approach to estimate time-varying carrying capacity (Kt), an integrative metric to monitor all environmental variables impacting vital rates in a population. We used individual-based modelling to quantify Kt for a recovering population of spotted hyenas and investigated whether population growth could be explained by recent environmental change. Population growth occurred despite no linear trend in Kt, suggesting that the observed growth is the lingering effect of past, rather than recent, environmental improvements. This study illustrates that recovery can occur at different time scales for the environment and for a population. Considering this demographic lag matters for the effective conservation of long-lived species.

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Section: Discussionmentioning

confidence: 99%

Effects of environmental change on population growth: monitoring time-varying carrying capacity in free-ranging spotted hyenas

Bailey,

Höner,

Davidian

et al. 2024

Preprint

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“…Because KP could delay the degradation of NPPT and further reduce ammonia volatilization losses, NPPT+KP significantly increased maize yield, plant N uptake, and NUE (Table 5) (P < 0.05), and NPPT+MP was not beneficial to maize yield and NUE. Brown algal polyphenols contained in KP enhance plant stress resistance (El-Katony et al 2020), and avoid the accelerated rate of chlorophyll degradation in leaves when subjected to drought stress (Nyarobi et al 2022). Thus, NPPT+KP significantly increased chlorophyll content (Table 4), while the chlorophyll content was the determining index of yield increase (Fig.…”

Section: Effects Of Se From Different Sources and Inhibitors On Physi...mentioning

confidence: 96%

Effect of seaweed extracts from different sources combined with urease and nitrification inhibitors

Xiao

Zhang

et al. 2023

BioRes

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Urease inhibitors (UIs) and nitrification inhibitors (NIs) still have limitations in increasing crop yield. Therefore, to improve the application effect of inhibitors, the combination of seaweed extracts (SE) from different sources and inhibitors was added to urea to provide a theoretical basis for the development of a new generation of efficient stabilized urea fertilizer with both biostimulant and inhibitor technologies. The combinations were tested in outdoor pots with no N- fertilizer (CK), application of urea alone (U) as control, and kelp polysaccharide (KP), margin polysaccharide (MP), N−(n−propyl) thiophosphoric triamide (NPPT), dicyandiamide (DCD), and combinations of SE with inhibitor were added to urea to make eight fertilizer prototypes. Compared with KP, MP showed better application effect, with significantly higher grain yield and nitrogen use efficiency (NUE) (P < 0.05). Compared with the addition of inhibitor alone, the combinations of NPPT with KP and MP, respectively, had opposite effects on urea−N transformation, meanwhile NPPT+KP had a positive effect. However, NPPT+MP significantly decreased yield, plant nitrogen uptake, and NUE (P < 0.05); DCD+MP decreased plant N uptake and NUE to some extent. Therefore, the addition of NPPT with KP and DCD with KP to urea significantly improved yield when planting maize in black soil.

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“…In this study, we added a crop waterlogging identification module to the existing SWAT-MODFLOW model (Figure 3). The process of identifying and predicting crop waterlogging risk areas under different climate scenarios was: (1) The SWAT model's crop growth module was first used to simulate the growth of wheat and goji under different climatic conditions in an automatic irrigation mode, and the irrigation water consumption was recorded, which was used as the assumed optimal irrigation amount for crop growth.…”

Section: Crop Waterlogging Identification Modulementioning

confidence: 99%

“…The impact of changes in precipitation and temperature on agricultural production due to climate change has become a hot research topic [1][2][3]. Changes in precipitation and temperature may alleviate or exacerbate temperature and water stress in crops, affecting the growth period, crop growth [4], and finally the yield [5].…”

Section: Introductionmentioning

confidence: 99%

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Identification and Prediction of Crop Waterlogging Risk Areas under the Impact of Climate Change

Jin

Zhai

et al. 2022

Water

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Waterlogging refers to the damage to plants by water stress due to excess soil water in the crop’s root zone that exceeds the maximum water holding capacity of the field. It is one of the major disasters affecting agricultural production. This study aims to add a crop waterlogging identification module to the coupled SWAT (Soil and Water Assessment Tools)-MODFLOW (Modular Finite Difference Groundwater Flow Model) model and to accurately identify and predict crop waterlogging risk areas under the CMIP6 (Coupled Model Intercomparison Project 6) climate scenarios. The result showed that: (1) The SWAT-MODFLOW model, which coupled with a crop waterlogging identification module, had good simulation results for LAI (Leaf Area Index), ET (Evapotranspiration), spring wheat yield, and groundwater level in the middle and lower reaches of the Bayin River; (2) The precipitation showed an overall increasing trend in the Bayin River watersheds over the next 80 years under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. The temperature showed a clear increasing trend over the next 80 years under the SSP2-4.5 and SSP5-8.5 scenarios; (3) Under the SSP1-2.6 scenario, the mountain runoff from the upper reaches of the Bayin River was substantially higher than in other scenarios after 2041. The mountain runoff in the next 80 years will decrease substantially under the SSP2-4.5 scenario. The mountain runoff over the next 80 years showed an initial decrease and then an increasing trend under the SSP5-8.5 scenario; (4) During the historical period, the crop waterlogging risk area was 10.9 km2. In the next 80 years, the maximum crop waterlogging area will occur in 2055 under the SSP1-2.6 scenario. The minimum crop waterlogging area, 9.49 km2, occurred in 2042 under the SSP2-4.5 scenario. The changes in the area at risk of crop waterlogging under each scenario are mainly influenced by the mountain runoff from the upper reaches of the Bayin River.

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The effects of extreme climate on the invasive plant Gutenbergia cordifolia: implications for its future management in savannah ecosystems

Cited by 5 publications

References 31 publications

Effects of environmental change on population growth: monitoring time-varying carrying capacity in free-ranging spotted hyenas

Effects of environmental change on population growth: monitoring time-varying carrying capacity in free-ranging spotted hyenas

Effect of seaweed extracts from different sources combined with urease and nitrification inhibitors

Identification and Prediction of Crop Waterlogging Risk Areas under the Impact of Climate Change

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