Knowledge domain and emerging trends of climate-smart agriculture: a bibliometric study

Climate-smart agriculture (CSA) is a new agricultural development pattern to address future food crises. Since CSA was proposed in 2010, it has attracted the attention of scholars from all over the world. It is of great significance to scientifically summarize the overview and emerging trends of CSA research, providing ideas for scholars concerned about CSA to engage in research in this field. Based on bibliometrics and CSA-related literature data in the WOS database, this paper used CiteSpace software to draw knowledge maps to scientifically analyze publications in the field of CSA. Our study found that (1) CSA research is showing a rapid upward trend, focusing on the environmental sciences and agricultural economic management; (2) international organizations such as the FAO, World Bank, and the international agricultural research institute have made significant contributions to CSA research; (3) among the nine clusters in the CSA literature, CSA practice, conservation agriculture, smallholder farmers, and sub-Saharan Africa have been consistently given high attention; (4) CSA research can be divided into three phases, and the research hotspots have transferred from essential elements of CSA to household and carbon emissions. We believe that in future research, more attention should be paid to the trade-off and synergy of the three pillars of CSA, as well as the investment, finance, and evaluation criteria of CSA. Such strengthening is of great significance to the sustainable promotion of CSA.

Climate warming threatens the persistence of a community of disturbance-adapted native annual plants

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning 6 yr and four sites across a latitudinal gradient in the Pacific Northwest, United States, we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals' persistence, but even such efforts may prove futile under future climate regimes.

A native annual forb locally excludes a closely related introduced species that co-occurs in oak-savanna habitat remnants

Despite the ubiquity of introduced species, their long-term impacts on native plant abundance and diversity remain poorly understood. Coexistence theory offers a tool for advancing this understanding by providing a framework to link short-term individual measurements with long-term population dynamics by directly quantifying the niche and average fitness differences between species. We observed that a pair of closely related and functionally similar annual plants with different origins-native Plectritis congesta and introduced Valerianella locusta-co-occur at the community scale but rarely at the local scale of direct interaction. To test whether niche and/or fitness differences preclude local-scale long-term coexistence, we parameterized models of competitor dynamics with results from a controlled outdoor pot experiment, where we manipulated densities of each species. To evaluate the hypothesis that niche and fitness differences exhibit environmental dependency, leading to community-scale coexistence despite local competitive exclusion, we replicated this experiment with a water availability treatment to determine if this key limiting resource alters the long-term prediction. Water availability impacted population vital rates and intensities of intraspecific versus interspecific competition between P. congesta and V. locusta. Despite environmental influence on competition our model predicts that native P. congesta competitively excludes introduced V. locusta in direct competition across water availability conditions because of an absence of stabilizing niche differences combined with a difference in average fitness, although this advantage weakens in drier conditions. Further, field data demonstrated that P. congesta densities have a negative effect on V. locusta seed prediction. We conclude that native P. congesta limits abundances of introduced V. locusta at the direct-interaction scale, and we posit that V. locusta may rely on spatially dependent coexistence mechanisms to maintain coexistence at the site scale. In quantifying this competitive outcome our study demonstrates mechanistically how a native species may limit the abundance of an introduced invader.

Using a Vegetation Model and Stakeholder Input to Assess the Climate Change Vulnerability of Tribally Important Ecosystem Services

We demonstrate a generalizable approach for assessing climate change effects on tribally important ecosystem goods and services. Indigenous peoples may be highly vulnerable to the impacts of climate change because they rely on ecosystem goods and services, such as traditional foods, hunting, timber production, nontimber forest resources, and cultural resources. However, there are few assessments that have examined the potential impact of climate change on these goods and services and even less that examine ecological, socio-economic, and cultural resources in the Pacific Northwest, USA. Our approach uses four basic steps: (1) identify 78 tribally important ecosystem services (species and resources), (2) relate those ecosystem services with biologically relevant vegetation projections from a dynamic global vegetation model, (3) identify appropriate timeframes and future climate scenarios, and (4) assess future changes for vegetation types and ecosystem services. We then highlight how model uncertainty can be explored to better inform resilience building and adaptation planning. We found that more than half of the species and resources analyzed may be vulnerable to climate change due to loss of potential habitat, including aridland species and grazing quality. We further highlight our findings for tribally important species, huckleberries (genus Vaccinium) and bitterbrush (Purshia tridentate (Pursh) DC.), and show how this information can be applied to help inform resource management and adaptation planning. We have demonstrated a generalizable approach that identified tribally important ecosystem services and related them with biologically relevant vegetation projections from a Dynamic Global Vegetation Model. Although our assessment is focused in the Pacific Northwest, our approach can be applied in other regions for which model data is available. We recognize that there is some inherent uncertainty associated with using model output for future scenario planning; however, if that uncertainty is addressed and applied as demonstrated by our approach, it then can be explored to help inform resource management and adaptation planning.

Prairie plant phenology driven more by temperature than moisture in climate manipulations across a latitudinal gradient in the Pacific Northwest, USA

Plant phenology will likely shift with climate change, but how temperature and/or moisture regimes will control phenological responses is not well understood. This is particularly true in Mediterranean climate ecosystems where the warmest temperatures and greatest moisture availability are seasonally asynchronous. We examined plant phenological responses at both the population and community levels to four climate treatments (control, warming, drought, and warming plus additional precipitation) embedded within three prairies across a 520 km latitudinal Mediterranean climate gradient within the Pacific Northwest, USA. At the population level, we monitored flowering and abundances in spring 2017 of eight range-restricted focal species planted both within and north of their current ranges. At the community level, we used normalized difference vegetation index (NDVI) measured from fall 2016 to summer 2018 to estimate peak live biomass, senescence, seasonal patterns, and growing season length. We found that warming exerted a stronger control than our moisture manipulations on phenology at both the population and community levels. Warming advanced flowering regardless of whether a species was within or beyond its current range. Importantly, many of our focal species had low abundances, particularly in the south, suggesting that establishment, in addition to phenological shifts, may be a strong constraint on their future viability. At the community level, warming advanced the date of peak biomass regardless of site or year. The date of senescence advanced regardless of year for the southern and central sites but only in 2018 for the northern site. Growing season length contracted due to warming at the southern and central sites (~3 weeks) but was unaffected at the northern site. Our results emphasize that future temperature changes may exert strong influence on the timing of a variety of plant phenological events, especially those events that occur when temperature is most limiting, even in seasonally water-limited Mediterranean ecosystems.

Changes in urban plant phenology in the Pacific Northwest from 1959 to 2016: anthropogenic warming and natural oscillation

In the Pacific Northwest of the USA, winter and spring temperature vary with the Pacific Decadal Oscillation, making effects of anthropogenic warming difficult to detect. We sought to detect community-level signals of anthropogenic change in a legacy plant phenology dataset. We analyzed both incomplete data from 1959 to 2016 on spring phenology of 115 species and more complete 1996-2016 data on spring and fall events for 607 plant species. We used ordination of the long-term dataset to identify two major axes of community-level change in phenology among years, with the first being a trend toward earlier spring phenology in more recent years. In contrast, for the short-term dataset, variation in spring phenology was mostly PDO-driven and did not reveal a strong trend over time. At both time scales, a second axis of phenological variation reflected summer and fall events, especially earlier appearance of fall color in recent years. In univariate analysis, more than 80% of individual species' leaf out dates and first flower dates occurred earlier over time, for an average advance across all species of 2.5 days per decade from 1959 to 2016. While most events did not advance in the period 1996-2016, fall color advanced by 10.6 days per decade, suggesting that intensification of summer drought has continued regardless of the PDO cycle. While estimates of slope over time depended strongly on the time window chosen for the analysis, estimates of slope versus temperature were consistently negative regardless of time window, averaging 5-7 days per 1 °C for spring events.

A new model to simulate climate-change impacts on forest succession for local land management

We developed a new climate-sensitive vegetation state-and-transition simulation model (CV-STSM) to simulate future vegetation at a fine spatial grain commensurate with the scales of human land-use decisions, and under the joint influences of changing climate, site productivity, and disturbance. CV-STSM integrates outputs from four different modeling systems. Successional changes in tree species composition and stand structure were represented as transition probabilities and organized into a state-and-transition simulation model. States were characterized based on assessments of both current vegetation and of projected future vegetation from a dynamic global vegetation model (DGVM). State definitions included sufficient detail to support the integration of CV-STSM with an agent-based model of land-use decisions and a mechanistic model of fire behavior and spread. Transition probabilities were parameterized using output from a stand biometric model run across a wide range of site productivities. Biogeographic and biogeochemical projections from the DGVM were used to adjust the transition probabilities to account for the impacts of climate change on site productivity and potential vegetation type. We conducted experimental simulations in the Willamette Valley, Oregon, USA. Our simulation landscape incorporated detailed new assessments of critically imperiled Oregon white oak (Quercus garryana) savanna and prairie habitats among the suite of existing and future vegetation types. The experimental design fully crossed four future climate scenarios with three disturbance scenarios. CV-STSM showed strong interactions between climate and disturbance scenarios. All disturbance scenarios increased the abundance of oak savanna habitat, but an interaction between the most intense disturbance and climate-change scenarios also increased the abundance of subtropical tree species. Even so, subtropical tree species were far less abundant at the end of simulations in CV-STSM than in the dynamic global vegetation model simulations. Our results indicate that dynamic global vegetation models may overestimate future rates of vegetation change, especially in the absence of stand-replacing disturbances. Modeling tools such as CV-STSM that simulate rates and direction of vegetation change affected by interactions and feedbacks between climate and land-use change can help policy makers, land managers, and society as a whole develop effective plans to adapt to rapidly changing climate.

Tools for Assessing Climate Impacts on Fish and Wildlife

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we provide a broad overview of the types of models available for forecasting the effects of climate change on key processes that affect fish and wildlife habitat (hydrology, fire, and vegetation), as well as on individual species distributions and populations. We present a framework for how climate-impacts modeling can be used to address management concerns, providing examples of model-based assessments of climate impacts on salmon populations in the Pacific Northwest, fire regimes in the boreal region of Canada, prairies and savannas in the Willamette Valley-Puget Sound Trough-Georgia Basin ecoregion, and marten Martes americana populations in the northeastern United States and southeastern Canada. We also highlight some key limitations of these models and discuss how such limitations should be managed. We conclude with a general discussion of how these models can be integrated into fish and wildlife management.