Dynamic Global Vegetation Models

Humans have caused growing levels of ecosystem and diversity changes at a global scale in recent centuries but longer-term diversity trends and how they are affected by human impacts are less well understood. Analysing data from 64,305 pollen samples from 1,763 pollen records revealed substantial community changes (turnover) and reductions in diversity (richness and evenness) in the first ~1,500 to ~4,000 years of the Holocene epoch (starting 11,700 years ago). Turnover and diversity generally increased thereafter, starting ~6,000 to ~1,000 years ago, although the timings, magnitudes and even directions of these changes varied among continents, biomes and sites. Here, modelling these diversity changes, we find that most metrics of biodiversity change are associated with human impacts (anthropogenic land-cover change estimates for the last 8,000 years), often positively but the magnitudes, timings and sometimes directions of associations differed among continents and biomes and sites also varied. Once-forested parts of the world tended to exhibit biodiversity increases while open areas tended to decline. These regionally specific relationships between humans and floristic diversity highlight that human–biodiversity relationships have generated positive diversity responses in some locations and negative responses in others, for over 8,000 years.

www.frontiersinecology.org C urrent technological advances mean that we are on the verge of a fusion of ecological modeling and remote sensing that should improve our prediction of ecological responses to global change for forests over continental scales. The need for such a capability could not be greater: the planet is warming (IPCC 2014) and past changes in climate have resulted in extinctions, major shifts in species distributions, and ecosystems with novel species combinations (Shugart and Woodward 2011). Predicting the consequences of warming involves extrapolation, which is always a tricky scientific proposition. The changes that human actions are causing thus high-light the need for better model prediction capabilities. Two technological innovations have the potential to bring about improved prediction of forest-ecosystem dynamics at large scales: first, innovations in airborne and satellite remote-sensing instruments are providing increased potential for large-scale measurement of forest structure, notably forest height and biomass; second, increased computing power is permitting continentalscale implementation of forest individual-based models (IBMs), which simulate the dynamic changes originating from interactions between individual trees (Figure ) over very large areas. provided several examples of individual tests of model predictions against independent data for different forest IBMs. At the continental scale, however, independent data are still needed that can test IBM predictions; these data could be produced by new remote-sensing technology. If successful at these large scales, such tests will assess the accuracy of large-area predictions; if not, they can be used to improve the models. This predict-and-test cycle is the hypothetico-deductive paradigm -the scientific method often used by high-school physics teachers -applied to forest dynamics over large regions and under novel conditions. Critical to this evaluation is the statistical independence of the test data from the calibration data. Successful tests against spatially extensive data would provide confidence in direct scaling up of forest IBMs. n New infrastructure and technology: an opportunity for a new level of model-data synthesis The scaled-up cousins of traditional ecosystem process models -both land-surface models (LSMs), which are components of the general circulation models that are

Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 model experiments investigated the response of biogeochemical and dynamic global vegetation models (DGVMs) to differences in climate over the conterminous United States. This was accomplished by simulating ecosystem processes using historical climate and atmospheric CO2 records from 1895–1993. We evaluated the behavior of six models (Biome‐BGC, Century, GTEC, LPJ, MC1, and TEM) by comparing simulated runoff in 13 watersheds to gauged streamflow from the Hydro‐Climatic Data Network. Metrics used to assess the “goodness of fit” between simulated and observed values were: (1) Pearson's r to evaluate the overall data set, (2) Kendall's τ to gauge seasonality trends as derived from a time‐series analysis of monthly runoff, and (3) three measures of absolute and relative error.We found small differences in performance among the six models over all watersheds. However, the models yielded highly divergent results dep...

Most of interpolated climatic factors are affected by topographical environments such as elevation and distance from observation site. While Korea is not large in the land area, topography is complex. Thereby, Korea shows great variability on spatial and temporal patterns of ...

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Societal Impact StatementUnderstanding of tropical forests has been revolutionized by monitoring in permanent plots. Data from global plot networks have transformed our knowledge of forests’ diversity, function, contribution to global biogeochemical cycles, and sensitivity to climate change. Monitoring has thus far been concentrated in rain forests. Despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical dry forests is still in its infancy. We provide a protocol for permanent monitoring plots in tropical dry forests. Expanding monitoring into dry biomes is critical for overcoming the linked challenges of climate change, land use change, and the biodiversity crisis.

Societal Impact StatementUnderstanding of tropical forests has been revolutionized by monitoring in permanent plots. Data from global plot networks have transformed our knowledge of forests’ diversity, function, contribution to global biogeochemical cycles, and sensitivity to climate change. Monitoring has thus far been concentrated in rain forests. Despite increasing appreciation of their threatened status, biodiversity, and importance to the global carbon cycle, monitoring in tropical dry forests is still in its infancy. We provide a protocol for permanent monitoring plots in tropical dry forests. Expanding monitoring into dry biomes is critical for overcoming the linked challenges of climate change, land use change, and the biodiversity crisis.

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. ...

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

Aim Water availability is the major driver of tropical-forest structure and dynamics. While most research has focused on the impacts of climatic water availability, remarkably little is known about the influence of water-table depth and excess soil water on forest processes. Nevertheless, since plants take-up water from the soil, the impacts of climatic water supply on plants are likely to be modulated by soil water, through groundwater. Location Lowland Amazonian forests Time period 1971 to 2019 Methods We use 344 long-term inventory plots distributed across Amazonia to analyse the effects of long-term climatic and edaphic water supply on forest functioning. We modelled forest structure and dynamics as a function of climatic, soil-water, and edaphic properties. Results Water supplied by both climate and soils affect forest structure and dynamics, but in different ways. Forests with shallow water table (depth <5 m) had 18% less aboveground-woody productivity and 23% less biomass stock than deep-water-table forests, while forests in drier climates (maximum cumulative water deficit <-160 mm) had 21% less productivity and 24% less biomass than those in wetter climates. Productivity was affected by interactions between climatic water deficit and water-table depth, in which in drier climates, shallow-water-table forests had lower productivity than deep-water-table forests, with this difference decreasing in wet climates. Main conclusions We show that the two opposites of "water availability" (excess and deficit) decrease productivity in terra-firme forests. The landscape-scale patterns of Amazonian forest structure and dynamics are affected by water table and its interactions with climatic conditions. Our study disentangles the relative contribution of those, improving understanding of tropical-ecosystem functioning and responses to climate change.

SummaryOver recent decades, biomass gains in remaining old-growth Amazonia forests have declined due to environmental change. Amazonia’s huge size and complexity makes understanding these changes, drivers, and consequences very challenging. Here, using a network of permanent monitoring plots at the Amazon–Cerrado transition, we quantify recent biomass carbon changes and explore their environmental drivers. Our study area covers 30 plots of upland and riparian forests sampled at least twice between 1996 and 2016 and subject to various levels of fire and drought. Using these plots, we aimed to: (1) estimate the long-term biomass change rate; (2) determine the extent to which forest changes are influenced by forest type; and (3) assess the threat to forests from ongoing environmental change. Overall, there was no net change in biomass, but there was clear variation among different forest types. Burning occurred at least once in 8 of the 12 riparian forests, while only 1 of the 18 uplan...

Repeated long-term censuses have revealed largescale spatial patterns in Amazon basin forest structure and dynamism, with some forests in the west of the basin having up to a twice as high rate of aboveground biomass production and tree recruitment as forests in the east. Possible causes for this variation could be the climatic and edaphic gradients across the basin and/or the spatial distribution of tree species composition. To help understand causes of this variation a new individual-based model of tropical forest growth, designed to take full advantage of the forest census data available from the Amazonian Forest Inventory Network (RAIN-FOR), has been developed. The model allows for withinstand variations in tree size distribution and key functional traits and between-stand differences in climate and soil physical and chemical properties. It runs at the stand level with four functional traits-leaf dry mass per area (M a), leaf nitrogen (N L) and phosphorus (P L) content and wood density (D W) varying from tree to tree-in a way that replicates the observed continua found within each stand. We first applied the model to validate canopy-level water fluxes at three eddy covariance flux measurement sites. For all three sites the canopy-level water fluxes were adequately simulated. We then applied the model at seven plots, where intensive measurements of carbon allocation are available. Treeby-tree multi-annual growth rates generally agreed well with observations for small trees, but with deviations identified for larger trees. At the stand level, simulations at 40 plots were used to explore the influence of climate and soil nutrient availability on the gross (G) and net (N) primary production rates as well as the carbon use efficiency (C U). Simulated G , N and C U were not associated with temperature. On the other hand, all three measures of stand level Published by Copernicus Publications on behalf of the European Geosciences Union. 1252 N. M. Fyllas et al.: Analysing Amazonian forest productivity using a new individual and trait-based model productivity were positively related to both mean annual precipitation and soil nutrient status. Sensitivity studies showed a clear importance of an accurate parameterisation of withinand between-stand trait variability on the fidelity of model predictions. For example, when functional tree diversity was not included in the model (i.e. with just a single plant functional type with mean basin-wide trait values) the predictive ability of the model was reduced. This was also the case when basin-wide (as opposed to site-specific) trait distributions were applied within each stand. We conclude that models of tropical forest carbon, energy and water cycling should strive to accurately represent observed variations in functionally important traits across the range of relevant scales.

Droughts are a natural, recurrent climate extreme that can inflict longlasting devastation on natural ecosystems and socioeconomic sectors. Unlike other natural hazards, drought onset is insidious and often affects a greater spatial extent and prolonged temporal scale. The evolution of drought and its impacts are typically region specific; the West and Southwest U.S. have experienced severe droughts at a higher frequency than the East and parts of the Midwest. While these regions do experience drought, intensified precipitation variability also obscures how drought may be changing in these locations. To better understand these trends, we examine the spatiotemporal trends of drought using self-organizing maps (SOM). SOMs are a novel, competitive learning subset of artificial neural networks (ANN), requiring unsupervised training of inputs. We introduced monthly Palmer Drought Severity Index (PDSI) values to the SOM to identify existing clusters of wetting and drying patterns from 1895-2016. After training, we created cartographic visualizations of the SOM output and conducted a subsequent time-This work would not have been able to reach completion without the unwavering support of my research advisors, Dr. Margaret Sugg, and Dr. Johnathan Sugg, who have both played integral roles in my success as a master's thesis student. Dr. Maggie Sugg has been an especially wonderful mentor as we both navigated through completing a thesis virtually. Her encouragement and attentiveness provided me the tools I needed to succeed during uncertain times, and for this I am sincerely grateful. Dr. Johnathan Sugg has also been a dedicated advisor, whose guidance in my methods was an essential component to the completion of my thesis. I am thankful for his contributions during this process. I would like to acknowledge, and thank fellow committee member, Dr. Baker Perry, whom without I would not have found my passion for research and climatology and embark on the journey of obtaining a masters in Geography. I would also like to recognize and thank Ronnie Leeper with the North Carolina Cooperative Institute for Climate and Satellites (NCICS) for providing the data used to complete this work. Given the unusual circumstances, I was unable to present this work at the Association of American Geographers (AAG) 2021. Regardless, I would still like to recognize the Office of Student Research, an on-campus organization which offered to provide funding for an opportunity to present at the AAG. I would also like to offer special recognition to the Department of Geography and Planning at Appalachian State University for providing a safe, and open environment where students and faculty support each other, both morally and vii academically. Despite the challenges the department has been faced with, our department has shown admirable resilience. A special thanks to our program director Dr. Derek Martin, and our department chair Dr. Saskia Van de Gevel whose devotion to students and higher education have made my experience welcoming and enjoyable. Finally, I would like to acknowledge my family, and my husband who have been patient and caring throughout this entire journey. My mother and father Cristina and Beto, who have only shown me to persevere and challenge myself, I am grateful for their ongoing inspiration. A special thanks to my husband, Brandon Cox, for always encouraging me to pursue all my academic dreams.