Climate Change Forecasts Research Articles

Resilient soybean and maize production under a varying climate in the semi-arid and sub-humid Chaco

Food security and economic stability of many developing countries rely on the resilience of major crops to climatic variability and climatic anomalies. Since climate change forecasts predict an increasing frequency and intensity of climatic disturbances, the need to increase our knowledge about the influence of climate variability on crop productivity is especially acute for areas with fragile environments such as the semi-arid and sub-humid Chaco in South America. We used climate records from recent decades and crop growth models to: (i) identify the main climatic variables that have influenced the productivity of soybean and maize which are major crops cultivated in the area and (ii) to assess the impact of inter-annual variability of climate variables on the productivity of soybean and maize. Simulated soybean and maize grain yields indicated that farmers in Chaco should be aware of the high interannual variability in the productivity of these crops. Farmers face a different risk cropping maize and soybean depending on the location. The productivity of soybean was below production costs in 10–13% of the studied years while the corresponding values for maize were 11–14%. Diversification of crop rotations is therefore key to enhance resilience and to increase the likelihood of harnessing favorable growing conditions. Management strategies intended to conserve soil water are of paramount importance, especially for soybean where anomalies in the precipitation during the first four months after sowing was the predictor that explained the highest amount of variance in grain yield (r = 0.58). To mitigate the effect of temperature, which essentially is a factor out of direct control of the farmer, the main practice that arose from our study is delaying planting dates (e.g., towards late January) to avoid the occurrence of high temperatures during the critical stages of the crop.

Adaptive potential of Coffea canephora from Uganda in response to climate change.

Understanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programmes. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long-lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defence pathways in coffee. Seventy-one single nucleotide polymorphisms (SNPs) were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB-like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, such as the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate-associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex situ conservation strategies are discussed.

Forecasting species distributions: Correlation does not equal causation

AbstractAimIdentifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects.LocationNew Hampshire and Vermont, USA.MethodsUsing causal and correlational models and new theory on range limits, we compared current (2014–2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high‐emission scenario (RCP8.5) of projected snow and forest biomass change.ResultsOur hypothesis that causal models of climate‐mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well‐supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx (Lynx canadensis) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat (Lynx rufus). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high‐elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx.Main conclusionsOur comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change.

Distinct Community-Wide Responses to Forecasted Climate Change in Afrotropical Forests

More refined knowledge of how tropical forests respond to changes in the abiotic environment is necessary to mitigate climate change, maintain biodiversity, and preserve ecosystem services. To evaluate the unique response of diverse Afrotropical forest communities to disturbances in the abiotic environment, we employ country-wide tree species inventories, remotely sensed climate data, and future climate predictions collected from 104 1-ha plots in the central African country of Gabon. We predict a 3–8% decrease in Afrotropical forest species richness by the end of the century, in contrast to the 30–50% loss of plant diversity predicted to occur with equivalent warming in the Neotropics. This work reveals that forecasts of community species composition are not generalizable across regions, and more representative studies are needed in understudied diverse biomes. This study serves as an important counterpoint to work done in the Neotropics by providing contrasting predictions for Afrotropical forests with substantially different ecological, evolutionary, and anthropogenic histories.

Mismatch between species distribution and climatic niche optima in relation to functional traits

Forecasts of climate change impacts on biodiversity often assume that the current geographical distributions of species match their niche optima. However, empirical evidence has challenged this assumption, suggesting a mismatch. We examine whether the mismatch is related to functional traits along temperature or precipitation gradients. The observed distributions of 32 tree species in northeast China were evaluated to test this mismatch. Bayesian models were used to estimate the climatic niche optima, i.e. the habitats where the highest species growth and density can be expected. The mismatch is defined as the difference between the actual species occurrence in an assumed niche optimum and the habitat with the highest probability of species occurrence. Species’ functional traits were used to explore the mechanisms that may have caused the mismatches. Contrasting these climatic niche optima with the observed species distributions, we found that the distribution–niche optima mismatch had high variability among species based on temperature and precipitation gradients. However, these mismatches depended on functional traits associated with competition and migration lags only in temperature gradients. We conclude that more relevant research is needed in the future to quantify the mismatch between species distribution and climatic niche optima, which may be crucial for future designs of forested landscapes, species conservation and dynamic forecasting of biodiversity under expected climate change.

CDLSTM: A Novel Model for Climate Change Forecasting

Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing rainfall pattern is an essential aspect of assessing the impact of climate change on water resources planning and management. Climate change affected the entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being a climatic indicator. The water coming from Himalayan rivers is essential for 1.4 billion people living downstream. Earlier studies either modeled temperature or rainfall for the Himalayan area; however, the combined influence of both in a long-term analysis was not performed utilizing Deep Learning (DL). The present investigation attempted to analyze the time series and correlation of temperature (1796–2013) and rainfall changes (1901–2015) over the Himalayan states in India. The Climate Deep Long Short-Term Memory (CDLSTM) model was developed and optimized to forecast all Himalayan states’ temperature and rainfall values. Facebook’s Prophet (FB-Prophet) model was implemented to forecast and assess the performance of the developed CDLSTM model. The performance of both models was assessed based on various performance metrics and shown significantly higher accuracies and low error rates.

Deterministic and stochastic models of infection spread and testing in an isolated contingent

The mathematical SIR model generalisation for description of the infectious process dynamics development by adding a testing model is considered. The proposed procedure requires the expansion of states’ space dimension due to variables that cannot be measured directly, but allow you to more adequately describe the processes that occur in real situations. Further generalisation of the SIR model is considered by taking into account randomness in state estimates, forecasting, which is achieved by applying the stochastic differential equations methods associated with the application of the Fokker – Planck – Kolmogorov equations for posterior probabilities. As COVID-19 practice has shown, the widespread use of modern means of identification, diagnosis and monitoring does not guarantee the receipt of adequate information about the individual’s condition in the population. When modelling real epidemic processes in the initial stages, it is advisable to use heuristic modelling methods, and then refine the model using mathematical modelling methods using stochastic, uncertain-fuzzy methods that allow you to take into account the fact that flow, decision-making and control occurs in systems with incomplete information. To develop more realistic models, spatial kinetics must be taken into account, which, in turn, requires the use of systems models with distributed parameters (for example, models of continua mechanics). Obviously, realistic models of epidemics and their control should include models of economic, sociodynamics. The problems of forecasting epidemics and their development will be no less difficult than the problems of climate change forecasting, weather forecast and earthquake prediction.

Effect of climate change on the potential distribution of Heloderma alvarezi (Squamata, Helodermatidae)

Climate change represents a real threat to biodiversity conservation worldwide. Although the effects on several species of conservation priority are known, comprehensive information about the impact of climate change on reptile populations is lacking. In the present study, we analyze outcomes on the potential distribution of the black beaded lizard (Helodermaalvarezi Bogert & Martin del Campo, 1956) under global warming scenarios. Its potential distribution, at present and in projections for the years 2050 and 2070, under both optimistic and pessimistic climate change forecasts, were computed using current data records and seven bioclimatic variables. General results predict a shift in the future potential distribution of H.alvarezi due to temperature increase. The optimistic scenario (4.5 W/m2) for 2070 suggests an enlargement in the species’ distribution as a response to the availability of new areas of suitable habitat. On the contrary, the worst-case scenario (7 W/m2) shows a distribution decrease by 65%. Moreover, the range distribution of H.alvarezi is directly related to the human footprint, which consequently could magnify negative outcomes for this species. Our research elucidates the importance of conservation strategies to prevent the extinction of the black beaded lizard, especially considering that this species is highly threatened by aversive hunting.

Occurrence of Australian woody species is driven by soil moisture and available phosphorus across a climatic gradient

AbstractQuestionsWoody species are crucial biotic components in many of Earth’s terrestrial ecosystems because they support multiple ecosystem functions. The occurrence of woody species (i.e. their likelihood of being present at a single position) is driven by both climate and soil properties. However, empirical evidence is lacking on how multiple environmental factors regulate woody species occurrence across various climate regimes, limiting our ability to predict woody species distribution under different climate change scenarios.LocationWoody plant species in eastern Australia; 1,500 km gradient.MethodsWe surveyed 6,353 mature (height >4 m) woody plants from 62 woody species at 150 sites along a 1,500 km climatic (i.e. aridity) gradient in eastern Australia, and used a generalized linear mixed model to explore the impact of summer rainfall, available soil phosphorus in the surface layer (0–10 cm), subsurface (100–200 cm) soil moisture and clay content, and interactions between aridity and the three soil variables on woody species occurrence (presence/absence).ResultsThe overall occurrence of Australian woody species declined as the concentration of available soil phosphorus in the surface layer increased, with the impacts varying with increasing aridity. Subsurface soil moisture had strong positive effects on woody species occurrence in mesic areas, but the effect was attenuated with increasing aridity. Subsurface soil clay regulated the distribution of woody species, with finer soils promoting the likelihood of species occurrence in the dry subhumid zone, whereas coarser soils supported more woody species in the arid zone.ConclusionsOur study provides empirical evidence that the distribution of Australian woody species is regulated by large‐scale shifts in soil moisture and available soil phosphorus, and local‐scale heterogeneity in soil texture. Our results suggest that forecasted climate change may restrict the distribution of woody species preferring particular soils, but expand the range of woody species that occur on dry or infertile soils.

Effect of Forecast Climate Changes on Water Needs of Giant Miscanthus Cultivated in the Kuyavia Region in Poland

Giant miscanthus is a vigorously growing energy plant, popularly used for biofuels production. It is a grass with low soil and water requirements, although its productivity largely depends on complementary irrigation, especially in the first year of cultivation. The aim of the study was to assess the impact of the forecast climate changes, mainly air temperature increase, on the water needs of giant miscanthus during the growing season in 2021–2050 in the Kuyavia region (central Poland). The years 1981–2010 as the reference period were applied. The meteorological data was based on the regional climate change model RM5.1 with boundary conditions from the global ARPEGE model for the SRES A1B emission scenario. Crop evapotranspiration, calculated using the Penman-Monteith method and crop coefficients, was assumed as a measure of water needs. The study results showed that in view of the expected temperature changes, in the forecast period 2021–2050, the giant miscanthus water needs will increase by 10%. The highest monthly increase may occur in August (16%) and in September (23%). In the near future, the increase in water needs of giant miscanthus will necessitate the use of supplementary irrigation. Hence the results of this study may contribute to increasing the efficiency of water use, and thus to the rational management of irrigation treatments and plant energy resources in the Kuyavia region.

Prediction of habitat suitability for Patrinia sibirica Juss. in the Southern Urals

The paper presents the results of predictions of the habitat persistence for rare relict of the Pleistocene floristic complex Patrinia sibirica (L.) Juss. in the Southern Urals under various forecasted climate change scenarios. Climate variables from CHELSA BIOCLIM, elevation data (GMTED2010) and coarse fragment content in the top level of soil were used as predictors for modeling in the MaxEnt software. The impact of climate change on P. sibirica habitats under the RCP4.5 and RCP8.5 scenarios calculated from an ensemble of four general circulation models has been analyzed. The modeling has shown that the changes in the habitat suitability depend on the altitude. Deterioration of the habitats could be attributed to a temperature increase in mountain forest locations, and to a precipitation of driest quarter increase in mountain forest-steppe locations. In both cases, this leads to the expansion of forest and shrub vegetation. Monitoring of the habitat persistence of P. sibirica and other relict species of the Pleistocene floristic complex can play a major role in predictions, as their massive decline would constitute that climatic changes exceed the ranges of their fluctuations in the Holocene.

An Approach Concerning Climate Change and Timber Building Resilience: Araucanía Region, South Chile

This study analysed climate change effects concerning the resilience of timber buildings located in southern Chile, specifically in two cities: Collipulli and Temuco (Araucanía Region). A digital fuzzy logic method was used in a set of timber buildings declared as heritage conservation buildings by Chilean Government standards. The outcomes revealed that climate change impacts did not substantially alter the functional performance of the set of heritage timber buildings examined. This study’s results can assist in developing upcoming strategies or recommendations that can support adaptation policies for administering architectural heritage regarding climate change forecasts. These data will invaluably help stakeholders who support the conservation of timber structures located in the southern environment of Chile and under the changing climatic hazard.

Marine temperatures underestimated for past greenhouse climate

Understanding the Earth’s climate system during past periods of high atmospheric CO2 is crucial for forecasting climate change under anthropogenically-elevated CO2. The Mesozoic Era is believed to have coincided with a long-term Greenhouse climate, and many of our temperature reconstructions come from stable isotopes of marine biotic calcite, in particular from belemnites, an extinct group of molluscs with carbonate hard-parts. Yet, temperatures reconstructed from the oxygen isotope composition of belemnites are consistently colder than those derived from other temperature proxies, leading to large uncertainties around Mesozoic sea temperatures. Here we apply clumped isotope palaeothermometry to two distinct carbonate phases from exceptionally well-preserved belemnites in order to constrain their living habitat, and improve temperature reconstructions based on stable oxygen isotopes. We show that belemnites precipitated both aragonite and calcite in warm, open ocean surface waters, and demonstrate how previous low estimates of belemnite calcification temperatures has led to widespread underestimation of Mesozoic sea temperatures by ca. 12 °C, raising estimates of some of the lowest temperature estimates for the Jurassic period to values which approach modern mid-latitude sea surface temperatures. Our findings enable accurate recalculation of global Mesozoic belemnite temperatures, and will thus improve our understanding of Greenhouse climate dynamics.

Bioenvironmental characteristics of Robinia pseudoacacia steppe plantations in dependence to changes in some climatic factors

Сlimatic factors play the most important role in the plant associations formation. Sunlight is one of the leading factors that determine the appearance of a particular community and very often plays the limiting factor role. In the conditions of the Steppe Dnipro Region, its limiting role can be expressed only in its excess. The great majority of autochthonous steppe flora plant species has strongly pronounced adaptations to excessive solar insolation. With the development of forest biogeocenology and steppe forestry, more and more attention is paid to the issues of forest climatology. It is shown that climatic factors have an imperative effect on the formation of soils, plant associations, fauna and ecosystems in general. Artificial plantations consisting of fast-growing hardwoods, such as Robinia pseudoacacia, have been studied. The complex of abiotic factors in robinia plantations and in open areas has its own characteristics. The processes of reflection, transformation and accumulation of solar energy in tree plantations have a slightly different character than in forest-free areas. In the Dnipropetrovsk region, the populations of Robinia pseudoacacia are represented mainly by young plants that have already entered the phase of active fruiting. No plants older than 100 years were found in the populations. Thus, the price spectrum of the age composition of the population of Robinia pseudoacacia in the Dnipropetrovsk region has a pronounced left-sided character, ie shifted towards young individuals that are actively fruiting. This indicates that the processes of expansion of Robinia pseudoacacia to natural biogeocenoses will be actively continued. Despite the fact that this breed has a number of positive qualities (excellent medonis, root mycorrhiza with azotobacter, high gas resistance, etc.), the processes of uncontrolled active settlement of this species is a matter of serious concern. This breed is capable of rapid spread and disruption of successional processes occurring in the area. In the conditions of the forecasted climate changes towards temperature increase and precipitation decrease this breed receives more and more advantages.

Will climate changes enhance the impacts of e-waste in aquatic systems?

The increase of the worlds' population is being accompanied by the exponential growth in waste of electrical and electronic equipment (e-waste) generation as a result of the rapid technological implementations. The inappropriate processing and disposal of this e-waste, containing rare-earth elements (REEs) such as gadolinium (Gd), may enhance its occurrence in the environment. In particular, the presence of Gd in marine systems may lead to environmental risks which are still unknown, especially considering foreseen climate modifications such as water salinity shifts due to extreme weather events. Within this context, the present study intended to assess the combined effects of Gd at variable salinities. For that, biochemical modifications were assessed in mussels, Mytilus galloprovincialis, exposed to Gd (0 and 10 μg/L) and different salinity levels (20, 30 and 40), acting individually and in combination. A decrease in salinity, induced an array of biochemical effects associated to hypotonic stress in non-contaminated and contaminated mussels, including metabolism, antioxidant and biotransformation defenses activation. Moreover, in Gd-contaminated organisms, the increase in salinity was responsible for a significant reduction of metabolic and defense mechanisms, possibly associated with a mussels’ physiological response to the stress caused by the combination of both factors. In particular, Gd caused cellular damage at all salinities, but mussels adopted different strategies under each salinity to limit the extent of oxidative stress. That is, an increase in metabolism was associated to hypotonic stress and Gd exposure, an activation of defense enzymes was revealed at the control salinity (30) and a decrease in metabolism and non-activation of defenses, associated with a possible physiological defense trait, was evidenced at the highest salinity. The different strategies adopted highlight the need to investigate the risk of emerging contaminants such as REEs at present and forecasted climate change scenarios, thus providing a more realistic environmental risk assessment.

Identifying Metocean Drivers of Turbidity Using 18 Years of MODIS Satellite Data: Implications for Marine Ecosystems under Climate Change

Turbidity impacts the growth and productivity of marine benthic habitats due to light limitation. Daily/monthly synoptic and tidal influences often drive turbidity fluctuations, however, our understanding of what drives turbidity across seasonal/interannual timescales is often limited, thus impeding our ability to forecast climate change impacts to ecologically significant habitats. Here, we analysed long term (18-year) MODIS-aqua data to derive turbidity and the associated meteorological and oceanographic (metocean) processes in an arid tropical embayment (Exmouth Gulf in Western Australia) within the eastern Indian Ocean. We found turbidity was associated with El Niño Southern Oscillation (ENSO) cycles as well as Indian Ocean Dipole (IOD) events. Winds from the adjacent terrestrial region were also associated with turbidity and an upward trend in turbidity was evident in the body of the gulf over the 18 years. Our results identify hydrological processes that could be affected by global climate cycles undergoing change and reveal opportunities for managers to reduce impacts to ecologically important ecosystems.

Long-term Central Waikato summer-autumn rainfall and pasture growth trends. Are conditions for pasture growth changing over time?

Farmers in the upper North Island are concerned about the poor productivity of their perennial ryegrass pastures beyond 3 years and suggest this is linked to a trend towards drier conditions for pasture growth during summer and autumn. To explore how conditions for pasture growth and survival have changed, trends in rainfall (measured and interpolated; c. 1954 to 2020), frequency of soil moisture deficit stress on pasture growth (1972-2020), and pasture growth rates (simulated 1977-2020, and measured c. 1979-2020) were compiled for summer-autumn months (November to April) for two Waikato locations: DairyNZ Ruakura/Scott Farm near Hamilton; and a commercial farm at Paratu Road between Morrinsville and Matamata. Significant negative linear trends were observed for interpolated rainfall (Paratu Road only), total stress days (both sites) and simulated pasture growth (both sites). No significant trend in measured pasture growth was observed for either site, suggesting adaptive management has cushioned the physical effects of harsher climatic conditions. The suite of adaptive management practices adopted on the Paratu Road farm is described. Analysis of decadal patterns indicated greater variability in rainfall in the decade 2011-2020 (coefficient of variation ranging from 32% to 36% depending on site and data source, versus ~ 22% in earlier decades) and a significantly higher number of stress days in the decade 2011-2020 compared with the 1970s and 1980s at Paratu Road. Further adaptation strategies will be needed to mitigate these most-recent trends, should they continue as predicted by climate change forecasts.

Climate changes, paleogeography and geological development of the northern part of Bulgarian Black Sea shelf and coast during the Quaternary

The article represents a synthesized reconstruction of the geological development of the northern part of Bulgarian Black Sea shelf and coast during the Quaternary. Marine Quaternary sediments are considered as a component of the marine ecosystem that is strongly affected by the climate changes. As a result, changes in the stratigraphic and sedimentological characteristics of the Pleistocene sediments and in particular the Holocene deposits were recorded. During the Quaternary, which is characterized by short-term, cyclic climatic fluctuations, marine shelf sediments have sealed traces of the alternation of glacial and interglacial phases. Based on detailed lithostratigraphic and biostratigraphic analysis of mollusk fauna and pollen, not only are the complex dynamics of the transgressiveregressive cycles traced, but also their relationship to global and regional changes of climate and sea level is confirmed. As a result of an integrated lithofacies, biostratigraphic, and geomorphological analysis, the stratigraphic sequence of the Quaternary sediments is established as well paleogeographic conclusions are reached. Today, knowledge of natural processes such as coastal abrasion, landslides, storms, tsunami waves, etc., are directly linked to the geological risk forecast and correlate with the geoecology and sustainability of the environment in which we live. In this sense, the reconstruction of the components of the geological environment from the closest geological past – Pleistocene and Holocene, is key to forecast climate change and sea level today.

Regional-scale vegetation-climate interactions on the Qinghai-Tibet Plateau

Response and feedback of vegetation growth to climate change are a series biogeophysical processes from local to regional scales. Revealing the vegetation-climate interaction is fundamental to understand the evolution of earth surface system in the context of global climate change. Due to the low temperature and vulnerable biotic and abiotic settings, the alpine ecosystems are sensitive to climate change, peculiarly in the Qinghai-Tibet Plateau (QTP). By combining the climate factors (precipitation and temperature) and vegetation state indicated by the Enhanced Vegetation Index (EVI) data we try to reveal the pertinent temporal reaction mode of vegetation to climate change on the QTP. The vegetation-climate interactions were investigated by using the Granger causality test technique. The prime findings of this study are: (1) vegetation showed a strong sensitivity to warming-wetting climate in most arid and semi-arid areas of the QTP; (2) the reaction patterns of EVI to precipitation show a temporal lag of 0–1 months, which was strongest to the cumulative precipitation within 1–2 months; (3) The time lag effect and cumulative effect of temperature on vegetation both occurred within 1 to 2 months; (4) The unidirectional Granger causes of precipitation and temperature to vegetation accounted for 17.65% and 8.66% of the entire QTP, respectively. This study emphasizes a sensitive response of the vegetation to climate change (precipitation and temperature) in the QTP. Vegetation feedback makes the fluctuations and effects of climate more complicated. The results indicated that more insights into the future forecasting of climate change and vegetation dynamics can be acquired by a specific and comprehensive analysis of vegetation-climate coupled feedback.

Exploring the Ecology of Establishing Oak Trees in Urban Settings of the Northeast

Urban forests notoriously lack diversity in the biological communities that inhabit them, from the age and species composition of street trees to wildlife populations. In reaction to invasions of nonnative insects and diseases as well as predicted response to climate change, an emerging number of community foresters and tree wardens are expanding their urban tree planting practices to include a broader assemblage of tree species. These include oaks, among other species able to tolerate and adapt to urban conditions. Oaks are potentially favorable in regions like the northeastern U.S., where they grow extensively in rural forests and demonstrate potential resistance to specific urban pests that have caused challenges for other historically popular and extensively planted street trees. Additionally, they are known to feature a number of wildlife benefits, and their ranges in the Northeast are predicted to expand under many future climate change forecast models. We examine the role of oaks in the urban environment through the lens of the urban forest diversity deficit, reviewing topics that include diversity recommendations, threats by nonnative insects and diseases, and the human-wildlife interface. The goal of this work is to encourage careful consideration of where and when to plant oak trees to help professionals address issues of uniformity, while achieving benefits for urban forest ecosystems and residents.