Abstract

The Congo Basin is severely understudied compared to other tropical regions; this is partly due to the lack of meteorological stations and the ubiquitous cloudiness hampering the use of remote-sensing products. Clustering of small-scale agricultural deforestation events within the Basin may result in deforestation on scales that are atmospherically important. This study uses 500 m MODIS data and the Global Forest Change dataset (GFC) to detect deforestation at a monthly and sub-km scale and to quantify how deforestation impacts vegetation proxies (VPs) within the Basin, the timescales over which these changes persist, and how they’re affected by the deforestation driver.

Missing MODIS data has meant that a new method, based on two-date image differencing, was developed to detect deforestation at a monthly scale. Evaluation against the yearly GFC data shows that the highest detection rate was 79% for clearing sizes larger than 500 m². Recovery to pre-deforestation levels occurred faster than expected; analysis of post-deforestation evolution of the VPs found 66% of locations recovered within a year. Separation by land-cover type also showed unexpected regrowth as over 50% of rural complex and plantation land recovered within a year. The fallow period in the study region was typically short; by the 6^th year after the initial deforestation event, ~88% of the locations underwent a further considerable drop. These results show the importance of fine spatial and temporal information to assess Congo Basin deforestation and highlight the large differences in the impacts of land-use change compared to other rainforests.

Abstract

Drought is a recurrent natural phenomenon, but there is concern that climate change may increase the frequency or severity of drought in Alaska. Because most common drought indices were designed for lower latitudes, it is unclear how effectively they characterize drought in Alaska’s diverse high-latitude climates. Here, we compare three commonly used meteorological drought indices (the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the self-calibrating Palmer drought severity index (scPDSI) to each other and to streamflow across Alaska’s 13 climate divisions. All of the drought indices identify major droughts, but the severity of the drought varies depending on the index used. The SPI and the SPEI are more flexible and often better correlated with streamflow than the scPDSI, and we recommend using them. Although SPI and SPEI are very similar in energy-limited climates, the drought metrics do diverge in drier locations in recent years, and considering the impact of temperature on drought may grow more important in the coming decades. Hargreaves PET estimates appeared more physically realistic than the more commonly used Thornthwaite equation and are equally easy to calculate, so we suggest using the Hargreaves equation when PET is estimated from temperature. This study, one of the first to evaluate drought indices for high-latitude regions, has the potential to improve drought monitoring and representation within the United States Drought Monitor, leading to more informed decision-making during drought in Alaska, and it improves our ability to track changes in drought driven by rising temperatures.

Abstract

Air temperature and precipitation outputs from 10 CMIP6 GCMs were input to the Precipitation-Runoff Modeling System hydrologic model to evaluate water and energy responses in three headwater basins to projected climate change over the twenty-first century. The headwater basins (398–801 km²) are located within the Mataura River basin in the South Island of New Zealand. CMIP6 datasets included two emission scenarios [shared socioeconomic pathways (SSPs) SSP2-4.5 and SSP5-8.5]. Half of the 10 GCMs selected in the study have equilibrium climate sensitivity (ECS) values above 4.5°C, which has been considered the upper end of equilibrium climate sensitivity. Modeling results included increased annual air temperature, evapotranspiration, and precipitation by the end of the twenty-first century for both SSP emissions scenarios, both high- and low-ECS GCMs, and all three headwater basins. Monthly precipitation and evapotranspiration totals also increased for all or most months. Monthly streamflow changes generally corresponded with monthly precipitation changes. Snowpack decreased significantly in depth and seasonal duration in all basins. However, streamflow increased for all SSP and ECS groups and basins because increased precipitation was consistently greater than increased evapotranspiration losses. Sources of uncertainty include the GCMs, climate sensitivity, downscaling, bias adjustment, emission scenarios, and the hydrologic model. Simulated hydrologic responses based on climate data from GCMs with ECS values of greater than 4.5°C could be less plausible since previous studies have suggested true ECS ranges from 1.5° to 4.5°C.

Abstract

In this paper we introduce a novel strategy to robustly diagnose the onset and demise of the rainy season using daily observed rainfall over seven specific regions across Australia, as demarcated by the Natural Resource Management (NRM) of Australia. The methodology lies in developing an ensemble spread of the diagnosed onset/demise from randomly perturbing the observed daily timeseries of rainfall at synoptic scales to obtain a measure of the uncertainty of the diagnosis. Our results indicate that the spread of the ensemble in the diagnosis of the onset and demise dates of the rainy season is higher in the subtropical compared to the tropical regions. Secular change of earlier onset, later demise, longer length, and wetter season are also identified in many of these regions. The influence of PDO at decadal, ENSO, and Indian Ocean Dipole at interannual, and MJO at intraseasonal scales also reveal significant influence on the evolution of the rainy season over these regions in Australia. Most importantly, the co-variability of the onset date with the length of the season and seasonal rainfall anomaly of the season is highlighted as a valuable relationship that can be exploited for real time monitoring and providing an outlook of the forthcoming rainy season, which could serve some of the NRM regions.

Abstract

Strategies that demonstrate renewed potential to enhance both social and ecological systems are crucial in today’s era of rapid urbanization. However, the approaches used to understand the impacts of such strategies sometimes favor social over environmental theory, or the opposite, but do not always consider both equally. Our study addresses this disconnect by exploring the role of urban agriculture (UA) as an alleviation and land management strategy in Mexico City (MC), Mexico. Our integrated design combined the ecosystem services framework, which was primarily used to assess material and non-material benefits MC residents obtain from UA spaces and its associated vegetation, and the livelihoods framework, which was used to evaluate the relationship between UA and societal impacts. We used a mixed-method approach to quantify the amount of food produced, assess crop diversity, assess six distinct ecological processes linked to UA, identify cultural benefits, and conduct an evaluation of contributions to livelihood capitals. Our study documented the role of UA in supporting ecological processes, connecting humans to nature, and providing a supplemental source of income. However, a multitude of unintended outcomes are identified, such as tradeoffs between different ecological processes, constraints in promoting formal education beyond agroecological knowledge, and an inability to fully elevate families out of poverty. Our integrated approach demonstrated how the ecosystem services and livelihoods frameworks can be used simultaneously to provide thorough assessments of socio-ecological systems, identifying outcomes that could go unnoticed without an interdisciplinary lens.

Abstract

Carbon dioxide flux from the Earth’s surface is a critical component of the global carbon budget, and the ocean surface is a significant CO₂ source and sink. The tropical coast absorbs CO₂ due to phytoplankton abundance and the all-year availability of photosynthetically active radiation. However, the role of the tropical coastal ocean in the global carbon budget is uncertain because of its under-representation in the literature. This study is the first to describe the variations of long-term CO₂ flux in the tropical coast on monthly and annual scales using the eddy covariance method and remote sensing data. The five-year average of the CO₂ flux is −0.089 ± 0.024 mmol m⁻² d⁻¹, which indicate that it is a moderate carbon sink. The results show that the CO₂ flux varied seasonally: the Fall Transitional, Southwest, Spring Transitional, and Northeast Monsoons partitioned the flux into three phases, which were the increasing, stable, and decreasing phases. The rising and falling stages can be identified by the erratic behavior of the flux, while the stable phase’s fluxes were relatively constant. The environmental parameters that regulated CO₂ flux were chlorophyll-α, sea surface temperatures, wind, and atmospheric stability, which modulated the CO₂ flux on the monthly timescale. Wavelet analysis corroborated the finding and revealed the role of PAR on CO₂ flux through the El-Niño-Southern Oscillation. On the monthly timescale, sea surface temperature only slightly affected the fluxes unlike chlorophyll-α, but temperature’s control on the flux became more apparent on the yearly timescale. These findings help understand the monthly and yearly controls of CO₂ flux and could contribute to developing models in predicting the flux on the tropical coast.

Abstract

Despite prompting persistent meteorological changes, severe defoliation following a tropical cyclone (TC) landfall has received relatively little attention and is largely overlooked within hurricane preparedness and recovery planning. Changes to near-track vegetation can modify evapotranspiration for months after tropical cyclone passage, thereby altering boundary layer moisture and energy fluxes that drive the local water cycle. This study seeks to understand potential spatial and temporal changes in defoliation-driven meteorological conditions using Hurricane Michael (2018) as a testbed. In this sensitivity study, two Weather Research and Forecasting (WRF) Model simulations, a normal-landscape and a post-TC scenario, are compared to determine how a defoliation scar placed along Michael’s path alters surface heat fluxes, temperature, relative humidity, and precipitation near the storm’s track. In the month following the foliage reduction, WRF resolves a 0.7°C 2-m temperature increase, with the greatest changes occurring at night. Meanwhile, the simulations produce changes to the sensible and latent heat fluxes of +8.3 and −13.9 W m⁻², respectively, while average relative humidity decreases from 73% to 70.1%. Although the accumulated precipitation in the defoliated simulation was larger along a narrow corridor paralleling and downwind of the hurricane track, neither simulation satisfactorily replicated post-Michael precipitation patterns as recorded by NCEP Stage IV QPE, casting doubt as to whether the downwind enhancement was exclusively due to the defoliation scar. This sensitivity analysis provides insight into the types of changes that may be possible following rapid and widespread defoliation during a TC landfall.

Abstract

The Mississippi River basin drains nearly one-half of the contiguous United States, and its rivers serve as economic corridors that facilitate trade and transportation. Flooding remains a perennial hazard on the major tributaries of the Mississippi River basin, and reducing the economic and humanitarian consequences of these events depends on improving their seasonal predictability. Here, we use climate reanalysis and river gauge data to document the evolution of floods on the Missouri and Ohio Rivers—the two largest tributaries of the Mississippi River—and how they are influenced by major modes of climate variability centered in the Pacific and Atlantic Oceans. We show that the largest floods on these tributaries are preceded by the advection and convergence of moisture from the Gulf of Mexico following distinct atmospheric mechanisms, where Missouri River floods are associated with heavy spring and summer precipitation events delivered by the Great Plains low-level jet, whereas Ohio River floods are associated with frontal precipitation events in winter when the North Atlantic subtropical high is anomalously strong. Further, we demonstrate that the El Niño–Southern Oscillation can serve as a precursor for floods on these rivers by mediating antecedent soil moisture, with Missouri River floods often preceded by a warm eastern tropical Pacific (El Niño) and Ohio River floods often preceded by a cool eastern tropical Pacific (La Niña) in the months leading up peak discharge. We also use recent floods in 2019 and 2021 to demonstrate how linking flood hazard to sea surface temperature anomalies holds potential to improve seasonal predictability of hydrologic extremes on these rivers.

Abstract

Large expanses of snow leopard habitat overlap with extensively used areas for livestock grazing. A fundamental question for conservationists is to determine whether livestock production can be reconciled with the conservation of rare and threatened large carnivores. Therefore, numerous studies focus on the relationship between carnivore densities and space use and environmental, anthropogenic, and topographic variables. Using snow leopard sign surveys in areas with high and low grazing disturbance, Hong et al. posit that livestock grazing directly impacts fine-scale habitat selection by snow leopards. The authors recommend controlling livestock grazing to help restore habitat complexity and alpine environment diversity. However, the approach by which Hong et al. have reached this conclusion is inadequate and is based on a methodology that fails to address the research question appropriately. We argue that 1) identification of a biologically relevant scale of study is the first essential step toward inferring carnivore–habitat relationships, 2) the authors draw inconsistent conclusions from their data on sign densities in high and low grazing disturbance areas, 3) ideally, the snow leopard–livestock relationship needs to be examined across a gradient of livestock grazing intensities and at multiple spatial scales, and 4) it is inappropriate to draw conclusions for landscape/regional scales from a study conducted at a finer and undefined scale. We suggest that future studies should clearly define the scale of the study, identify appropriate habitat variables of interest, and use meaningful measurement instruments to serve as proxies for variables of interest.

Abstract

We thank Luxom and Sharma for their attention to and comments on our study. In recent years, livestock have been expanding into snow leopard habitat, and we conducted this study to examine the effects of that encroachment on snow leopard habitat within Wolong Nature Reserve. Specific responses to Luxom and Sharma’s comments include the following: 1) Many habitat factors influence carnivore–habitat relationships at varying spatial scales, and it is difficult for any single study to address the full suite of factors acting across all scales of selection. Given this fact and the limited spatial scale of our snow leopard sign survey, we mainly focused on snow leopard space use and microhabitat selection. 2) Our results are not necessarily conflicting, but more research is required to further explain how high sign densities, concentrated space use, and weak habitat selection behaviors might relate to each other. 3) We agree that examining a gradient of grazing intensities would be preferable, but because of the difficulty in collecting sufficient field data and the nature of livestock grazing patterns in our study area, we think that dividing our survey area into high- and low-grazing-disturbance areas was appropriate. 4) The original intent of this study was to examine habitat factors and response to livestock within our study area in Wolong Nature Reserve, and we did not intend for our specific results to be used for management recommendations beyond Wolong but instead encourage similar studies to be conducted in other areas.