An Intersection of Climate, History and Landscape Use: 3000 Years of Central Italian Environmental Change

University of Nevada, Reno

An intersection of climate, history and landscape use: 3000 years of central Italian environmental change

A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Geography

Theodore Dingemans

Dr. Scott A. Mensing/Dissertation Advisor

August 2019

THE GRADUATE SCHOOL

We recommend that the dissertation prepared under our supervision by Theodore Dingemans

Entitled An intersection of climate, history and landscape use: 3000 years of central Italian environmental change

be accepted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Scott A. Mensing, Ph.D. , Advisor

Gianluca Piovesan, Ph.D., Committee Member

Paula Noble, Ph.D., Committee Member

Adam Csank, Ph.D., Committee Member

Edward Schoolman, Ph.D. , Graduate School Representative

David W. Zeh, Ph.D., Dean, Graduate School

August-2019 i

Abstract

Both climate change and historical events affect the environmental history of a place.

Dis-entangling the two is challenging and requires independent reconstructions of climate

and landscape change, as well as a thorough local historical narrative. Understanding the

role climate and humans have played on shaping landscape is key to interpreting history

and understanding the ecological trajectory of a region. Here I present a study which

combines a climate reconstruction, a fossil pollen record of land cover change calibrated

using a study of modern vegetation-pollen relationships, and a review of the archaeological and historical narrative in order to assess drivers of environmental change in central Italy. The climate and fossil pollen records are derived from a sediment core taken from Lake Ventina and cover the last 3000 years. δ18O and δ13C measurements on

bulk carbonate produce a record which produces a semi-quantitative local climate reconstruction. Analysis of modern water samples confirm that the lake’s isotopic system today is sensitive to changes in water balance, which is driven by monthly and yearly trends in weather. The carbonate isotope record indicates a shift to more depleted δ18O

and enriched δ13C between 750 and 950 AD, suggesting positive water balance and

expanded wetland surrounding the lake. The record is compared to that from nearby Lake

Lungo and the two match well from 750 AD to present, including periods of enriched

δ18O from 1100 to 1400 AD and depleted δ18O from 1500 to 1800 AD, both of which

conform well to regional patters of climate during those times. Analysis of fossil pollen

from Lake Ventina reveals that from the beginning of the record in 1000 BC to 1400 AD,

the area was characterized by a highly anthropogenic landscape dominated by fields and ii

meadows with limited forest cover. This constrasts with findings from nearby Lake

Lungo and highlights the spatial heterogeneity of landscape use in the past, with some

sites being heavily utilized prior to and throughout the Roman period. Forest expanded

dramatically after 1400 AD as a result of population decline resulting from the Black

Death and a shift to cooler/wetter climate. Thirty modern pollen samples and paired

surveys of the surrounding vegetation were used to characterize land cover-pollen relationships and aide in the interpretation of the fossil pollen record. A key finding is that cultivates and other anthropogenic indicators are underrepresented in the pollen record relative to their presence on the landscape, suggesting the pre-1400 AD landscape

surrounding Lake Ventina must have been even more intensively utilized by humans than

the pollen percentages indicate. Analysis of the modern pollen also indicates that there

are not many modern analogs for pollen assemblages found in the Lake Ventina record, suggesting past landscapes were not similar to those of today. Overall this research represents a case study in long-term environmental history and demonstrates how records of climate and landscape change can be integrated with historical and archaeological records to greatly improve our understanding of ecological history.

iii

Dedication

To my parents, Robin and Dennis, who inspired in me a love of geography and education

from a young age.

Acknowledgements

This work would not have been possible without an incredible amount of support and mentorship from my advisor, Dr. Scott Mensing, as well as constant advice and help from my other committee members. This work covers a broad range of academic disciplines and the expertise of my committee members was invaluable to helping me traverse the

fields of history, paleolimnology, ecology, isotope geochemistry, and others. This research was funded primarily through a National Science Foundation grant to Dr.

Mensing and Dr. Paula Noble (GSS-1228126). I also thankful for the significant support

I’ve received from the UNR Department of Geography throughout my time as a PhD student in the form of numerous scholarships and teaching assistantships. Several other people have provided invaluable help to me over the years. Anna Klimaszewski-

Patterson, my colleague and fellow graduate student for many years provided an immense amount of support, advice, and technical expertise. Thank you also to Dr.

Simon Poulson for allowing me to use his lab here at UNR to process samples for isotope analysis. Finally, I am indebted to the Geography Department office managers, Prisilia

Maldonado and Margo Grubic, who have made managing all things administrative much easier and less time consuming than they otherwise would have been.

Table of Contents Abstract ...... i Introduction ...... 1 Dissertation structure ...... 4 Theoretical Underpinnings ...... 9 Citations ...... 12 Figures ...... 14 Chapter 1: Late Holocene climate reconstruction from central Italy using isotopes of lake carbonate ...... 15 Abstract ...... 15 1. Introduction ...... 16 2. Study Area ...... 18 3. Methods ...... 19 Coring and initial sediment analysis ...... 19 Age Control ...... 20 Water Sampling ...... 21 Carbonate Isotopes ...... 21 Diatoms ...... 22 4. Results ...... 23 Age Control ...... 23 Water Isotopes ...... 23 Magnetic Susceptibility, Loss on Ignition, and Carbonate Isotopes ...... 25 Diatom analysis ...... 26 5. Discussion ...... 27 Interpreting the modern water and DIC isotope record ...... 28 Interpreting the carbonate isotope record ...... 29 Climate reconstruction and lake history ...... 34 6. Conclusions ...... 39 7. Citations ...... 41 8. Figures ...... 46 9. Tables ...... 55 Chapter 2: Spatial and temporal patterns of environmental change over the last 3000 years from the Rieti Basin, central Italy ...... 57 Abstract ...... 57 vi

1. Introduction ...... 58 2. Site ...... 60 Vegetation ...... 60 3. Methods ...... 61 Pollen analysis ...... 61 Stratigraphic Analysis ...... 62 Zone 1a: 1000 BC to 760 AD ...... 62 Zone 1b: 760 to 800 AD ...... 64 Zone 1c: 800 to 1450 AD ...... 64 Zone 2: 1450 to 2014 AD ...... 65 Ordination Analysis ...... 65 5. Discussion ...... 66 Pollen taxa relationships ...... 67 Comparison with other local records ...... 69 The Lake Lungo pollen record ...... 69 Comparison with other local records ...... 71 Separating climate and human-induced environmental change ...... 72 Lake Ventina pollen interpretation ...... 74 The Pre-1450 Landscape ...... 74 Late Bronze Age, Iron Age, and Archaic Periods (1000 BC – 270 BC) ...... 76 The Roman Imperial period ...... 80 Ostrogoth & Lombard Period (Early Medieval: 500 to 750 AD) ...... 83 Carolingian conquest (750 – 800 AD) ...... 84 Medieval Warm Period (~900 – 1250 AD)...... 86 Post-1400 afforestation ...... 88 6. Conclusion ...... 90 7. Citations ...... 92 8. Figures ...... 98 9. Tables ...... 107 Chapter 3: Pollen-vegetation relationships and modern analogs from central Italy ...... 109 Abstract ...... 109 1. Introduction ...... 110 2. Study area ...... 112 3. Methods ...... 113 vii

Pollen analysis ...... 113 Land-cover quantification ...... 115 Statistical analysis ...... 116 4. Results ...... 117 Structure of the pollen dataset ...... 118 Composition of the pollen dataset ...... 120 Forest land cover vs forest pollen ...... 122 5. Discussion ...... 123 Forest cover vs forest pollen from open sites ...... 123 Categorizing vegetation zones using modern pollen ...... 124 Challenges in detecting specific human impacts ...... 125 Notes on specific taxa ...... 127 Comparison with the Lake Ventina pollen record ...... 129 6. Conclusion ...... 132 7. Citations ...... 134 8. Figures ...... 138 9. Tables ...... 145 Conclusion ...... 149 Future Work ...... 152 Citations ...... 155

Introduction

Environmental history is the study of the interaction between humans and their

environment. Environmental historians seek to answer questions regarding the way

people used the land, the impacts of climate change on society, how changing culture

influenced agricultural practices, and how land-use impacted the environment. This is a

discipline in which scientists have taken both a cultural approach, through history,

anthropology, and archaeology, and a physical approach, though the geosciences and

paleoecology. As a geographer, I integrate both approaches, combining a reconstruction

of the physical geography of the environment with the history and archaeology to

produce a long-duration environmental history of the Rieit Basin, central Italy.

Environmental history throughout the Mediterranean is a topic which has seen an

expansion in scholarship over the past several decades as scientists look to better

understand how humans, from classical civilizations to modern times, interacted with and

possibly created elements of the Mediterranean environment. For example, two recent

issues of prominent paleoenvironmental journals have been dedicated to this topic;

Quaternary Science Reviews special issue titled “Mediterranean Holocene climate,

environment, and human societies” (Quaternary Science Reviews volume 136, 2016) and

the Holocene special issue titled “The changing face of the Mediterranean: land cover,

demography and environmental change” (Holocene 29, 5 (2019)). My research falls within this expanding intellectual and conceptual context and addresses two fundamental questions. I articulate these questions below, and then describe the structure of how these questions are addressed in the dissertation. 2

R1: What impacts have climate change and humans had on environmental change in

central Italy and can these effects be differentiated in the fossil record?

H1: Changes to the Lake Ventina system and the surrounding terrestrial

landscape have been driven primarily by fluctuations in climate and

extreme weather events (i.e. flooding).

H2: Environmental change during key periods has been driven primarily by

humans and landscapes in the past reflect historical changes in political

control, population, and agro-pastoral lifeways.

When we reconstruct past environmental change, we often cannot tell if that change has been driven by climatic or human activity. When humans are present,

particularly in sufficient numbers, they could have had a major influence on changing the

environment, and thus the ecological trajectory of a location. If we do not carefully

analyze the human presence, by default we give primacy to climate and natural ecological

processes as the cause of environmental change (Figure 1). This approach is typically

taken in locations and times when human impacts are known to be absent or limited (e.g.

in places like the Great Basin where human exploitation of the landscape is thought to

have been extremely low-intensity prior to the 19th century, or time periods prior to the

advent of agriculture). Such an approach can mislead scientists trying to understand the

dynamics of the modern landscape, because it assumes the largest influences on

ecological development have been non-human. In the Mediterranean, where human

impacts are known to be widespread for millennia, a more complex approach to 3

interpreting pollen records is needed. The purpose of this study is to fully integrate past

human history into environmental reconstruction to evaluate assumptions about the roles

climate and humans have played in shaping the landscape. Understanding the interaction

between humans and their environment in the past is important because it provides a

more robust context for ecological history, establishes past impacts of both human and

climatic change, and helps reconstruct how this history has created the modern landscape

(Figure 2).

R2: Are trends in the environmental history of Lake Ventina local, extralocal, or

regional, and does it shift over time?

H1: Changes seen in proxy records from Lake Ventina consistently match those from

Lake Lungo, as well as other records from central Italy and the western

Mediterranean suggesting strong regional cohesion.

H2: Changes seen in the proxy records from Lake Ventina do not consistently match

local and regional records, suggesting fine-scale variation in the region’s

environmental history, at least during some periods.

Although paleoecologists recognize landscapes are heterogeneous, current practices treat environmental change as homogeneous through the practice of single-site

studies that capture both local and regional inputs. A reconstruction from a single site

will often be used to characterize environmental change hundreds of miles away. This

tendency has arisen in part because of the time commitment and funding necessary to

create multiple records, and in some regions a lack of suitable sites (e.g. lakes and 4

wetlands with long, uninterrupted sedimentation and suitable pollen preservation).

However, this approach limits our understanding of the local spatial heterogeneity of

environmental change in the past. Developing multiple records within 10-20 km of each other can allow us to examine local variation in environmental change and provide valuable insight to environmental history. Historical records are subject to some of the same issues of scale, and historians are limited by the extent of surviving documents.

Historical documents relevant to environmental change often characterize things like land ownership, political control, or land use at one specific location or area (e.g. charters) and this forces environmental historians to extrapolate over a broad area. Records which generalize over a broad region (e.g. many books written by Romans) are also common in the historical record and force environmental historians to evaluate how well the

documentary source characterizes local conditions in any given place. Analyzing local

variability in environmental change also helps bring reconstructions in line with how

rural communities functioned prior to the last 2 centuries. For most of human history very

few people traveled more than 10-20 km from where they were born, (citation) and

culture was extremely spatially heterogeneous. By helping to determine the amount of

spatial heterogeneity in environmental change we can help calibrate historical records

and bring reconstructions more in line with the spatial patterns of human culture and

society.

Dissertation structure

This dissertation includes three main chapters, which together represent a

reconstruction of environmental change over the past 3000 years from central Italy and 5

an examination of the role climate and humans have played. Each of these chapters is

written as a stand-alone manuscript for publication, with figures and references at the end

of the text. Individual chapters address specific aspects of the two research questions previously presented, and together they address them as a whole.

Chapter one addresses Question 1 by developing an independent record of climate

using stable isotopes of carbonate which is compared against the pollen reconstruction

and historical narrative to assess drivers of environmental change. It also speaks to

question 2, because without a locally derived climate record, the question of climatic

impact on vegetation change cannot be directly addressed. Additionally, by comparing

the climate reconstruction from Lake Ventina (this study) with the record from Lake

Lungo (previous studies in the Rieti Basin), we can better understand how nearby lakes

with different limnilogical settings respond to shifts in climate.

Beyond addressing the two overall research questions, Chapter 1 focusses on the

potential of carbonate isotopes from Lake Ventina as a useful proxy for climate. Stable

isotopes of authigenic lake carbonate (δ18O and δ13C precipitated in the lake) is a

common tool used to reconstruct past climate (Leng and Marshall, 2004). Isotope values of carbonate can respond to changes in a variety of lake characteristics that can be linked to climate including: temperature of lake water, source area of precipitation, precipitation amount, and seasonality of precipitation (Leng, 2006; Roberts et al., 2008). In the

Mediterranean region many lakes have carbonate records which serve as proxies for water balance (Roberts et al., 2008). This is because in hot dry places evaporation during summer months causes lake water to become isotopically enriched and summer evaporation is the dominant process driving the isotopic composition of lake water. The 6

isotopic composition of lake water in turn is the primary driver of oxygen isotope value

18 18 of carbonate (δ Ocarbonte) in lake sediment. Lake water becomes enriched in δ O through

preferential evaporation of the lighter species 16O. Thus, the hotter/drier the summer, the

18 higher the δ Ocarbonate value precipitated in the lake and deposited in the sediments. This

18 mechanism of control of δ Ocarbonate can be tested by regular measurement of lake water

δ18O in different seasons. If the lake’s water is substantially more enriched than the local

meteoric water line (the δ18O/δD of rainwater in the region) and the δ18O/δD of local

streams/rivers, and shows strong enrichment in the summer months, it is likely the δ18O and δ13C of carbonate which forms in the lake is at least in part controlled by summer

water balance. Examples of studies which used modern water isotopes to assess

carbonate isotope drivers include: Roberts et al., 2008; Baroni et al., 2006; Leng et al.,

2010. While this approach has been thoroughly tested elsewhere, it has not been widely

used in Italy (Roberts et al., 2008; Giraudi et al., 2011) but has the potential to fill a

critical gap by creating the first multi-millennial climatic reconstruction from central

Italy, and provide a local high-resolution climate reconstruction. The stable isotope

record provides an opportunity to reconstruct climate (water balance), a vitally important

climate variable in the arid and semi-arid sub-tropics because water availability helps

control human habitation and biogeography

Chapter 2 addresses question 1 by reconstructing the vegetation history of a site in

central Italy (Lake Ventina) using pollen preserved in a sedimentary lake core that spans

the last 3,000 years. By comparing this reconstruction with both a local independent

record of climate (the isotope record from Chapter 1) and the historical and

archaeological record, we can evaluate the role humans and climate have played in 7

shaping the environment. Question 2 is addressed by comparing the Lake Ventina record

to the record from nearby Lake Lungo as well as other records from the region and

throughout Italy in order to evaluate spatial patterns of environmental change.

The reconstruction of vegetation change from Lake Ventina and its interpretation

is a particularly valuable addition to the field of environmental history for several

reasons. First, it is located in a region with an extensive historical and archaeological

record, beginning with the Bronze Age and spanning the periods of the Roman Empire,

Ostragoth and Lombard conquests, Invasion by Charlemagne, Medieval Period,

demographic collapse following the Black Plague, and subsequent resurgence of

population during the Renaissance. Local records come from archaeology, including a

thorough field survey extending from pre-Roman to modern times (Coccia et al., 1992);

local historical records, including from the monastery at Farfa beginning in the 7th

century; records of flooding and land reclamation efforts beginning in the 3rd century

BCE; cadastral survey data in the past 200 years; and limnilogical analysis beginning in

the 20th century. Regional records also allow the overall political control of the region to

be accurately reconstructed back to Roman times. These allow us to compare

reconstructions of climate and landscape change to discrete historical events such as

changes in political control. Furthermore, written and archaeological evidence of lifeways

(such as agricultural practices) allow us to investigate the direct mechanism for how

climate and humans interacted.

Assessing local spatial variability in environmental change can help improve our ability to separate human impacts from climate. Long-term changes in climate generally

occur on regional scales and impacts of a shift in climate would be expected to be have a 8

similar impact on sites across a region, at least among those with similar ecologies. Thus,

when two nearby sites exhibit different trends in environment during the same time period, climate can be eliminated as a primary driver.

Multiple nearby sites with different topographical settings can help detect

different kinds of environmental change. For example, we expect the record from Lake

Lungo, located in the center of the Rieti Basin, to be sensitive to changes in the

management of the broad Rieti Basin floodplain which surrounds the lake. Lake Ventina,

located outside the basin in a narrow valley would be expected to be sensitive to changes

in land-use on hillsides. By comparing the two records we get a more holistic view of the

way the landscape was being used by people. Overall, by developing records from

multiple nearby sites we are able to better understand and reconstruct the environmental

history of the Rieti region of central Italy.

Chapter 3 is a study of modern pollen from central Italy. It focusses on the

relationship between vegetation cover and pollen in order to improve the landscape reconstruction from Lake Ventina. Chapter 3 addresses research Question 1 by developing modern vegetation/pollen relationships that improve our ability to interpret shifts in the environment identified in the fossil pollen record. Particularly, this can improve our ability to assess to what extent a landscape was anthropogenic. Chapter 3 helps address Question 2 by improving our understanding of pollen source area. Knowing at what spatial scale our record is recording changes in vegetation helps us determine at what spatial scales environmental change is occurring, particularly when comparing the record from Lake Ventina to other nearby fossil pollen records. 9

This study is necessary because there are significant challenges to using fossil pollen to reconstruct land cover and analyzing modern pollen-vegetation relationships in the region can help address some of these issues. These include: first, a bias in favor of pollen from plants which are growing close to the sampling location and diminishing contribution from plants growing farther away. Eventually a distance is reached beyond which plants do not contribute significantly outside of the background pollen rain which affects all sites in a region similarly (Prentice, 1985). A better understanding of which areas are contributing significantly to the fossil pollen record from Lake Ventina can help us determine at what spatial scales changes in the environment are occurring. Second, there is not a 1:1 relationship between plant cover and representation in the pollen record

(Parsons and Prentice, 1981). How much pollen a plant produces per area, and how well that pollen is dispersed control this relationship. Calculating which plant taxa are over and under-represented in a pollen record relative to the abundance of the plants can help refine our understanding of human and climatic impacts on the landscape over time.

Third, there are pollen assemblages in the Lake Ventina pollen record that are different than pollen assemblages from the region today, and thus it can be difficult to imagine what the landscape associated with them was like. Sampling a variety of less common modern vegetation patches allows for the better understanding of these past landscapes and helps to answer the question: do modern analogs for past landscapes exist in central

Italy?

Theoretical Underpinnings 10

This research is fundamentally geographic in two ways. First, it seeks to test the

first law of Geography (Tobler 1970), which states “everything is related to everything else, but near things are more related than distant things” in a paleoecological context. In

the broadest terms, this principle is true, however in complex landscapes where humans

actively use the land, landscape change may vary across short distances. The practice

among palynologists of using a single site reconstruction to characterize a region, is

unable to capture potential spatial heterogeneity. Moreover, since pollen is transported

both aerially and fluvially, proximity to streams can significantly impact pollen

deposition. Therefore, the principle that nearby lakes will hold similar records is not

necessarily valid and one of the goals of this project is to compare the Lake Ventina record with nearby a nearby record from Lake Lungo and more remote records from across Italy and the Mediterranean.

Second, this research is deeply rooted in the fundamental geographic concept of human-environment interaction. It seeks to understand how people have used and exploited the landscape over thousands of years and the impacts climate, political, demographic, and economic change has had on the relationship between people and the land.

This research is deeply reliant on a multi-disciplinary approach aimed at utilizing theories and skills from scholars outside of geography. This approach, recently termed consilience, is increasingly considered a vitally important aspect of modern paleoscience (Haldon et al., 2018). This project makes use of ideas and skills from paleoecology, history, archaeology, geochemistry, and limnology in order to better understand landscape change over thousands of years. Specifically, this research fits well 11

within the longue durée approach (Braudel and Wallerstein 2009) of history, which enhances the study of landscape evolution and facilitates analysis of its driving factors over many time-scales. It provides a framework to study the structures of human history across multiple climate oscillations and cultural phases by stressing the importance of the long-term impacts humans have on their environment.

Citations

Baroni, C., Zanchetta, G., Fallick, A. E., Longinelli, A., Maria, V. S., & Glasgow, G. (2006). Mollusca stable isotope record of a core from Lake Frassino, northern Italy : hydrological and climatic changes during the last 14 ka. The Holocene, 16(6), 827– 837.

Braudel, F., & Wallerstein, I. (2009). History and the Social Sciences. Review (Fernand Braudel Center), 32(2), 171–203.

Coccia, A. S., Mattingly, D. J., Beavitt, P., Elton, H., Foss, P., George, I., … Morton, K. (1992). Settlement History, Environment and Human the Central Apennines : the Rieti Survey. Papers of the British School at Rome, 60, 213–289.

Giraudi, C., Magny, M., Zanchetta, G., & Drysdale, R. N. (2011). The Holocene climatic evolution of Mediterranean Italy: A review of the continental geological data. The Holocene, 21(1), 105–115. https://doi.org/10.1177/0959683610377529

Haldon, J., Mordechai, L., Newfield, T. P., Chase, A. F., Izdebski, A., Guzowski, P., … Roberts, N. (2018). History meets palaeoscience: Consilience and collaboration in studying past societal responses to environmental change. Proceedings of the National Academy of Sciences, 115(13), 3210-3218. https://doi.org/10.1073/pnas.1716912115

Leng, M. J., Baneschi, I., Zanchetta, G., Jex, C. N., Wagner, B., Vogel, H., … Maria, V. S. (2010). Late Quaternary palaeoenvironmental reconstruction from Lakes Ohrid and Prespa (Macedonia / Albania border) using stable isotopes. Biogeosciences, 7, 3109–3122. https://doi.org/10.5194/bg-7-3109-2010

Leng, M. J. (Ed.). (2006). Isotopes in Paleoenvironmental Research (Vol. 10). Springer.

Leng, M. J., & Marshall, J. D. (2004). Palaeoclimate interpretation of stable isotope data from lake sediment archives. Quaternary Science Reviews, 23(7–8), 811–831. https://doi.org/10.1016/j.quascirev.2003.06.012

Parsons, R. W., & Prentice, I. C. (1981). Statistical Approaches to R-Values and the Pollen-Vegetation Relationship. Review of Paleobotany and Palynology, 32, 127– 152.

Prentice, I. C. (1985). Pollen representation, source area, and basin size: Toward a unified theory of pollen analysis. Quaternary Research, 23(1), 76–86. https://doi.org/10.1016/0033-5894(85)90073-0 13

Roberts, N., Jones, M. D., Benkaddour, A., Eastwood, W. J., Filippi, M. L., Frogley, M. R., … Zanchetta, G. (2008). Stable isotope records of Late Quaternary climate and hydrology from Mediterranean lakes: the ISOMED synthesis. Quaternary Science Reviews, 27, 2426–2441. https://doi.org/10.1016/j.quascirev.2008.09.005

Roberts, C. N., Zanchetta, G., & Jones, M. D. (2010). Oxygen isotopes as tracers of Mediterranean climate variability : An introduction. Global and Planetary Change, 71, 135–140. https://doi.org/10.1016/j.gloplacha.2010.01.024

Tobler, W. R. (1970). A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234–240.

Figures

Figure 1: Model of environmental change recorded by pollen when humans are not impacting the environment substantially and change is driven solely by climate.

Figure 2: Model of environmental change recorded by pollen when humans are impacting the environment and change is driven by changes in climate, humans, and the interaction between the two

Chapter 1: Late Holocene climate reconstruction from central Italy using isotopes of lake carbonate

Abstract

A new reconstruction of climate over the last 3000 years from Lake Ventina,

central Italy has been developed based on δ18O and δ13C measurements of carbonate.

Stable isotopes of lacustrine carbonate can be a valuable climate proxy and its use in the

Mediterranean basin is widespread. The summer-dry climate makes lakes sensitive to changes in water balance which are recorded by the isotopes of carbonate precipitated in the sediments. However, records from Italy are limited by a lack of sufficient carbonate in many lakes and issues with age control. This study is one of the first to present a high- resolution climate reconstruction of the late Holocene from central Italy. Modern water sampling of Lake Ventina suggests that the isotopic composition of water and dissolved inorganic carbon is being driven by water balance. Both variables exhibit substantial and regular isotopic enrichment throughout the summer. The outstanding signal in the paleo- record is a shift to more depleted δ18O conditions between 750 and 950 AD. This period

corresponds to a time when the North Atlantic Oscillation was more positive, which

promotes wet conditions in southern Europe. The record is compared to that from nearby

Lake Lungo and the two match well from 750 AD to present, but diverge prior to 750

AD, possibly as a result of differing legacies of human modification of the hydrology of

the two lakes.

1. Introduction

There is a paucity of high-resolution late Holocene climate records from peninsular Italy that can be suitably compared with historical data. Studies seeking to link climate and historical activities require high-resolution, continuous, well dated, multi- millennial datasets that capture local climate change at a temporal scale consistent with human land use change, and are independent from human impacts. Although there are some excellent records of climatic variation from central Italy, including records of flooding on the Tiber River back to about 200 BC (Alessandroni and Remedia 2002;

Camuffo et al., 2003; Aldrete, 2007), lake-level reconstructions using paleo-shorelines

(Ramrath et al., 2000; Magny et al., 2007; Giraudi et al., 2011), records of Apennine glaciation (Giraudi, 2005), and studies of fluvial deposits (Giraudi 2005; Giraudi 2012), flood and shoreline records are discontinuous, and glacial and fluvial deposits lack precise chronological control. For central and northern Europe, tree-ring records provide an important high-resolution climate proxy (Buntgen et al, 2011; Cook et al., 2015).

Unfortunately, partly because of a long-term human presence and Mediterranean climate which is not well suited for wood preservation, central Italy lacks long-lived trees that dendroclimatologists rely on for tree-ring based reconstruction of climate (Cook et al.,

2015). Isotope records of speleothems provide another high-resolution multi-millenial late Holocene climate record, however the closest records come from the Pyrenees of

Spain (Martín-Chivelet et al., 2011), the Austrian Alps (Frisia et al., 2005) and Scotland

(Baker et al., 2015). Travertine records of paleoclimate are known from central Italy, including the Rieti Basin, but records only exist for time periods 3000 BC and older

(Soligo et al, 2002). Finally, pollen is often used to reconstruct climate, but the long term 17

occupational history of the region and presence of agrarian cultures with the means to

manipulate the landscape going back several millennia means that pollen records respond

both to human and climatic influences, and thus cannot be used to reconstruct climate

change on their own (e.g. Mensing et al., 2015; Rull and Vegas-Vilarrubia, 2015).

A useful proxy of regional paleoclimate is stable isotope geochemistry (δ18O and

δ13C) of authigenic carbonate in lake sediment. This proxy has been successfully used by

paleolimnologists, paleoecologists, and paleoclimatologists to reconstruct paleoclimate

variation because in general, variations relate to the temperature and isotopic variation of

the lake water in which the carbonate precipitates (Leng, 2006). Many factors that affect

the lake water composition can be linked to climate, including: water balance

(evaporation:precipitation), source area of precipitation, precipitation amount, and

seasonality of precipitation (Leng, 2006; Roberts et al., 2008). In the Mediterranean

region many lakes have carbonate records which serve as proxies for water balance

resulting from isotopic enrichment during evaporation during the hot dry months

(Roberts et al., 2008). The isotopic composition of lake water in turn is the primary driver

18 of the oxygen isotope value of authigenic sedimentary carbonate (δ Ocarbonte). Lake water

becomes enriched in δ18O through preferential evaporation of the lighter species 16O.

18 Thus, the hotter/drier the summer, the higher the δ Ocarbonate value precipitated in the

lake and deposited in the sediments. This mechanism can be tested by regular

measurement of lake water δ18O during different seasons. If lake water δ18O is

substantially more enriched than the local meteoric water line (the δ18O/δ2H of rainwater

in the region) and the δ18O/δ2H of local streams/rivers, and shows strong enrichment in

the summer months, it is likely the δ18O and δ13C of carbonate which forms in the lake is 18

at least in part controlled by summer water balance (Roberts et al., 2008; Baroni et al.,

2006; Leng et al., 2010). This approach is used to produce a 3000-year reconstruction of

hydroclimate variability from Lake Ventina.

2. Study Area

The site, Lake Ventina, (Figure 1a) is just downstream of the main Rieti Basin, located approximately 70 km north-east of Rome in the foothills of the Apennines.

Within the Rieti Basin, lakes with previously published records include Lake Lungo,

(Mensing et al., 2015, 2016, 2018; Archer et al. 2017), and Lake Ripasottile (Archer,

2017; Archer et al., 2017; Archer et al., 2019). Lake Ventina is 368 m above mean sea

level, with a surface area of 0.8 km2, a maximum depth of ~3.5 m, and a watershed area

or proximately 2.5 km2 The Velino River flows approximately 0.5 km west of Lake

Ventina at a similar elevation to Lake Ventina’s surface. Although aerial imagery show

the remnants of a small canal connecting Late Ventina to the Velino River, this feature

did not have an active connection during sampling visits, and no permanent surface

inflow is visible (personal observation). A detailed bathymetric map made ~100 years

ago (Ricardi, 2006) shows the presence of the canal, as well as several springs on the

south side of the lake, and marsh area (Figure 1b). Today, the lake appears to be fed

primarily by groundwater, although the flow direction of the groundwater is not known.

Water quality data collected by the regional environmental protection agency, ARPA

Lazio (Table 1), indicates that Ventina is a eutrophic lake, with similar Total Phosphorus

and water clarity values to Lakes Lungo and Ripasottile (Table 2), and this is supported

by observations of abundant macroalgae and periphyton growing along the lake’s 19

periphery. The Velino River, a tributary of the Tiber River, drains a large watershed to the east and south which contains mountains in the central Apennines (peaks >2000m), and is fed primarily by several large carbonate springs (Archer et al., 2017). There is no current surface water connection between the Velino River and Lake Ventina, though historic illustrative maps suggest that this may not always have been the case (Riccardi,

2006). Lake Ventina is situated in a narrow synclinal valley with hill slopes extending nearly to its shoreline. The bedrock in the watershed is dominated by Upper Triassic to

Middle Miocene marine carbonates (Cosentino et al., 2010), and the syncline in which

Ventina sits is composed of argillaceous marine limestone of Late Jurassic (Tithonian) age (Riccardi, 2006). The Climate of the Rieti region is characterized by a transitional

Mediterranean climate, with hot mostly dry summers and wet seasons in the fall and spring. Average daily temperatures range from 4 ˚C in the winter to 21 ˚C in the summer and average annual precipitation is 1117 mm (Leon, 2004).

3. Methods

Coring and initial sediment analysis

Two parallel cores, VEN14-A (11.5 m in length) and VEN14-B (12.7 m), and one surface core (1.5 m) were recovered from Lake Ventina in July 2014 using a modified

Livingston piston corer. The cores were shipped to LacCore (the National Lake-Core

Repository) at the University of Minnesota, Duluth where they were opened, split, imaged, described, sampled for pollen and isotopes, measured for magnetic susceptibility, and had loss on ignition (Dean 1974) performed. Based on observation of the core 20

imagery and notes taken in the field a master composite core using sections from all 3 cores was created (Figure 2).

Age Control

The age model for the Lake Ventina master core is based on paleomagnetic secular variation (PSV). This dating technique involves measuring magnetic properties of the core through time and then correlating them with a reconstruction of the strength and directional variation in Earth’s magnetic field (Gallet et al., 2002). This approach to age control was taken instead of the more common utilization of radiocarbon because 14C dates from terrestrial macrofossils found in lakes in this region, including Lake Ventina, have consistently returned radiocarbon ages much too old to be considered reliable

(Mensing et al., 2015). In Lake Lungo, >20 radiocarbon ages were obtained on multiple different types of organic materials, including macrofossils, pollen, charcoal and bulk sediments, and when rigorously compared with other age indicators, including PSV, were consistently older by hundreds to thousands of years (Mensing et al., 2015). Macrofossils were extremely rare in the Lake Ventina sediments, but one sample was found and dated, and similar to Lungo, the date was thousands of years older than expected based on the

PSV chronology and comparison of the different lake records. This suggests that plants growing in the area are taking up old carbon from the bedrock. A PSV-based age model was used to date the core from Lake Lungo, and the methods used to create the core chronology for Lake Ventina are very similar to those presented in Mensing et al. (2015).

Additional age control is provided by several tie points in the top 200 cm of the core between the magnetic susceptibility of the Ventina sediments and those of Lake Lungo. 21

Water Sampling

Eleven samples of water were taken from Lake Ventina between 2016 and 2018

and five samples water were taken from the Velino River between 2014 and 2017 in

order to determine seasonal variation, and in particular establish the effects of

evaporation on the isotopic composition of the lake water. These samples were filtered on

shore using a 0.45µm Millipore filter to remove particulate matter, stored in a 10 ml glass

18 2 vial, and shipped to UNR under refrigeration, and measured for δ Owater and δ Hwater using a Picaro Cavity Ring-Down Mass Spectrometer in Dr. Simon Poulson’s Laboratory for Isotope Geochemistry. Water isotope results are presented relative to the VSMOW

18 2 standard (δ OVSMOW (‰) and δ HVSMOW (‰)). Seven of the filtered Lake Ventina water

samples and four of the Velino River samples were also sampled for δ13C of dissolved

inorganic carbon (DIC) and stored and in high density polyethylene, and run in the UNR

Laboratory for Isotope Geochemistry.

Monthly temperature and precipitation data were extracted from the Colli Sul

Velino weather station (retrieved from: http://www.idrografico.roma.it/annali/) and

compared with lake water isotope data to assess the responsiveness of the isotopic system

to weather. Lake water temperature and alkalinity measurements taken in 2011 and 2012

by the regional environmental protection agency, ARPA Lazio, were also compared with

weather data to evaluate how sensitive the lake’s chemistry is to fluctuations in precipitation and temperature.

Carbonate Isotopes

One cm thick sediment samples from discrete depths throughout the core were prepared for analysis of δ18O and δ13C of bulk carbonate. Samples were dried in a 50˚ C 22

oven overnight, then heated to 250˚ C for 1 hour on a vacuum rig to remove volatile organic compounds. Ten pilot samples were analyzed at the stable isotope laboratory at

the University of Northern Illinois, which uses a Gas Bench directly coupled to a Thermo

Finnigan MAT 253 Isotope Ratio Mass Spectometer. Another 31 samples were analyzed

at the Center for Stable Isotope Biogeochemistry at the University of California,

Berkeley, useing a MultiCarb system in line with a GV IsoPrime mass spectrometer in

Dual Inlet. Results of analysis of carbonate and DIC are presented relative to the VPDB

18 13 18 13 standard for both δ O and δ C (δ OVPDB (‰) and δ CVPDB (‰)).

Diatoms

Approximately 100 smear slides were made during initial core sampling at 10 cm

intervals during initial core description to identify which parts of the core contained

diatoms. In banded intervals where the sediment composition varied, smear slides were

made from representative bands as a spot check so as not to overlook thin layers where

diatoms may be present. Samples were then taken from the diatom-bearing intervals and

processed at the University of Nevada, Reno. Approximately 100 mg of sample was

heated to boiling in a 15% solution of hydrogen peroxide for 1 hour to remove organic

material. Several ml of hydrochloric acid were added to each sample to remove any

carbonate and then samples were decanted 6 times using deionized water, producing a

siliceous slurry with a pH of ~6. Permanent mount strewn slides were made from slurries

and air dried, taking care to produce homogenous distributions of material on cover-slips,

and using Slides were mounted using Zrax mountant (refractive index = 1.7). Diatoms

were identified to the lowest possible level of identification, usually the species level, 23

using Hofmann et al. (2013) and Krammer (2000-2016) as principal references for the

benthic species, and Houk et al. (2010, 2014, 2017) for the phytoplankton.

4. Results

Age Control

Fifteen tie points based on PSV were identified between Ventina and both the regional paleomagnetic sequence (Gallet et al., 2002; Pavon-Carrasco et al., 2009) and the paleomagnetic sequence from nearby Lake Lungo (Mensing et al., 2015).

Additionally, four tie points between the magnetic susceptibility of lakes Ventina and

Lungo were identified, and dates in Ventina were assigned based on the dating of those events in Lake Lungo. An age model (Figure 3) was developed using linear interpolation between tie points. The Ventina age model suggests the bottom of the master core dates to approximately 1000 BC. Sedimentation rate is relatively consistent, with an average sediment accumulation rate of 0.42 cm yr-1. Comparison of the pollen sequence from

Ventina and Lungo helps confirm the validity of the age model. Several substantial shifts

in the pollen assemblage, most notably at around 1450 AD, occur with nearly identical

timing in both records (see Chapter 2 Figure 7).

Water Isotopes

18 2 δ Owater and δ Hwater values for the eleven samples from Lake Ventina and five

samples from the Velino River (Table 3) are plotted (Figure 4) along with the

Mediterranean Meteoric Water Line (MMWL; Roberts et al., 2008), the Global Meteoric

Water Line (GMWL; Craig, 1961), and the Local Meteoric Water Line (LMWL; Spadori

et al., 2010). The Ventina water samples plot to the right of all three MWLs and fit a 24

linear regression line with an R2 value of 0.99 and a formula of: δ2H = 4.939δ18O +

10.379. A line intercepts the LMWL at roughly δ18O = -6 and δ2H = -40, which is similar

to the amount-weighted average values of precipitation from a nearby rain gauge (-5.96, -

36.8) for the period 1951-2007 (Spadori et al., 2010). The slightly more depleted values

2 for δ Hwater from Ventina may in part be a result of the disproportionate contributions of

isotopically depleted winter precipitation to groundwater and thus lake-water recharge

(e.g. Winograd et al., 1998).

The strong linear trend in the data indicates that all samples likely originated from

the same source water and have undergone different levels of evaporative enrichment

based on the time of year of sampling and inter-annual variability in weather (Figure 5).

Samples taken over the course of the same year get progressively more enriched as evaporation continues to concentrate heavier isotopes in the lake water. This is true for all samples in both 2017 and 2018 except for the May 2018 sample, which is slightly more depleted than the sample taken in March 2018. In Figure 5, lake temperature tracks air temperature almost perfectly, while alkalinity does show large seasonal variation but does not correlate well to weather parameters measured. Water isotopes appear to be responding to medium-term (i.e. seasonal or annual) weather conditions: samples from

2016/2017 are more enriched because those years were drier. The year of 2018 was wetter and the samples are more depleted.

Four of the five samples taken from the Velino River are nearly identical in both

18 2 th δ Owater and δ Hwater, and the 5 (taken February 2015) only differs by approximately

0.5‰/5‰ in δ18O/δ2H, respectively. All river samples are substantially depleted

compared to the samples from Lake Ventina. This is likely a result of the Ventina 25

samples having undergone substantial evaporative enrichment, and the Velino River

watershed including high-elevation mountains where the precipitation has starting values

that are more depleted (Clark and Fritz, 1997; Leng, 2006).

The seven samples from Lake Ventina and four samples from the Velino River

13 that were measured for δ CDIC have their values listed in Table 3 and are plotted in

18 13 Figure 6, with δ Owater on the x-axis and δ CDIC on the y-axis. The samples from Lake

Ventina fit a linear regression line with an R2 value of 0.81, which indicates that both

variables are responding to changes in the lake’s water balance throughout the year (Horn

18 et al., 2016). The samples from the Velino River are more depleted in δ Owater and

13 enriched in δ CDIC compared to those from Lake Ventina and do not exhibit a strong

seasonal water-balance signal.

Magnetic Susceptibility, Loss on Ignition, and Carbonate Isotopes

The MS curve reaches its highest and lowest points in the top 120 cm of the

record (Figure 7). Below 120 cm the signal generally exhibits a frequency in the 4-15

year range and the long-term trend is stable at between 20 and 30 SI. The organic (TOC) and inorganic carbon (TIC) records are similar with several important exceptions. TIC is a much higher magnitude throughout the core. TOC is highest in the top 3m of the core, leveling off below that, and displays remarkable consistency throughout. TIC is also relatively stable long-term, but has more short-term variability. In particular, TIC peaks between 520 and 550 cm depth which corresponds to approximately 750 to 800 AD.

Sediments may contain high-frequency variation in carbonates that are not measured by the LOI analysis. There are narrow white bands less than 1cm thick throughout the core which are high in carbonate but are not captured by our discrete sampling scheme. 26

13 18 Forty-one depths were measured for δ C/ δ O of carbonate. Overall sampling

18 resolution was one sample approximately every 70 years. δ Ocarbonate values range from -

13 2.99 to -6.58‰ VPDB and δ Ccarbonate values range from -0.60 to -2.54‰ VPDB.

18 13 13 δ Ocarbonate exhibits greater variation than does δ Ccarbonate (Figure 7). δ Ccarbonate values

are relatively stable, particularly below 700 AD. The sample at the top of the core

13 (approximately 2010 AD) is the most depleted in the record in terms of δ Ccarbonate by

more than 0.5‰. The most distinct period in the dataset is from 750 to 950 AD and is

13 18 characterized by enriched δ Ccarbonate and depleted δ Ocarbonate values.

A scatterplot of isotope data (Figure 8) reveals a lack of strong correlation

13 18 13 18 between δ C and δ O measurements. The overall correlation between δ C and δ O is -

0.18. The weak correlation in the dataset is driven in large part by samples which fall within the 750-950 AD period and are enriched in δ13Ccarbonateonate and depleted in

18 δ Ocarbonate. These samples lie in the top-left quadrant of Figure 8.

Diatom analysis

Diatoms were found to be abundant throughout the top 20 cm (~70 years) of the

record, as well as common in a 25 cm section between 512 and 537 cm run depth which

dates to 750-800 AD (Figure 7). Additionally, rare diatoms were found in a narrow

(<1cm) band of oxidized material at 651 cm run depth which dates to around 550 AD. It

should be noted that diatoms were not searched for exhaustively, as described in the

methods, and it is quite possible that additional layers containing rare diatoms occur in

other thin bands in the lower parts of the core.

Samples from the top of the core are dominated by phytoplankton, chiefly

cyclotelloid species (abundant Lindavia ocellata, fewer L. comta-radiosa complex). 27

Aulacoseira ambigua is also abundant, and Asterionella formosa is present. Asterionella formosa was the dominant phytoplankton species in water samples collected from Lake

Ventina during the summer 2013. Of lesser abundance are periphyton associated with marshy areas growing in and around macrophytes like Phragmites. Of this fraction, the most common forms are the motile epipelic species Gyrosigma acuminatum, chains of the araphid fragilarioid Staurosira construens, and the stalked species Amphora copulata.

Also common are Pseudostaurosira elliptica, Staurosirella leptostauron, Synedra spp.

(including S. dilatata and a long form identified as S. ulna var. chaseana), Cymbella spp.,

Mastogloia lacustris, Navicula spp. (incuding N. radiosa), Pinularia spp., Sellaphora

pupula, Eunotia arcus, and Rhopalodia gibba.

The samples from 750-800 AD all are dominated by phytoplankton with L.

ocellata being the most abundant species. Also present are periphyton, including G.

acuminatum and epiphytes including species of Cymbella, Gomphonema, Cocconeis.

Specimens of Mastogloia, Surirella, Amphora, Synedra, and rare Aulacoseira were also

observed.

The single sample from 550 AD contains sparse cyclotelloids, many of which are

abraded. Most of the specimens appear to be assignable to the Lindavia comensis species

complex. These taxa occur rarely in layers of the banded material in Lake Lungo, and

may represent flood layers from the Velino River. This diatom species is not indigenous

to the lakes and specimens are likely washed in.

5. Discussion 28

Interpreting the modern water and DIC isotope record

Modern water sampling of Lake Ventina supports a model where carbonate

precipitated in the lake has an isotopic composition controlled primarily by lake water

balance. The strong co-variation between the isotopes of water, the annual progression

from more depleted in the spring to more enriched in the fall, and a trend line which

intersects the local meteoric water line at a point which nearly perfectly matches local

13 water measurements (Figure 4) all support this claim. Additionally, δ CDIC also exhibits

13 progressive enrichment over the year (Figure 6). δ CDIC measurements from Lake

Ventina are substantially depleted (average -9.5‰) compared to the surrounding bedrock

(about 3‰), suggesting dissolution of carbonate bedrock is not the primary driver of

inorganic carbon in the lake. Water and DIC isotopes from Lake Ventina are substantially

18 2 13 more enriched in δ Owater and δ Hwater and depleted in δ CDIC than the Velino River,

which suggests minimal river input into Lake Ventina. Overall the modern data suggests

Lake Ventina should be sensitive to variation in climate, although several caveats apply.

First, the percentage organic/inorganic carbon and magnetic susceptibility records (Figure

7) as well as the general appearance of the sediments from Lake Ventina (Figure 2)

indicate that modern lake conditions are different from those down-core, meaning that the

modern lake may not be a good analog for conditions prior to the 20th century. Second, the duration and extent to which Lake Ventina and the Velino River has been connected in the past is not well documented. Third, temperature and alkalinity were not measured during water sampling for δ18O/δ2H. Thus, a saturation index for carbonate cannot be

calculated and our understanding of the annual timing of carbonate precipitation in the

lake is limited. Analysis of Lake Lungo suggests carbonate precipitation throughout 29

much of the year (Archer et al., 2017), and given the similar geochemistry of the two

lakes there is little reason to suspect Lake Ventina is substantially different. Because

18 temperature is an important control on δ Ocarbonate, shifts in the seasonality of carbonate

precipitation in the past may have influenced long term trends in isotopic composition.

Analysis of the diatoms from Lake Ventina can help alleviate some of these concerns. Samples from 750-800 AD are similar in terms of diatom assemblage to those from the top 20 cm of the core, which suggests lake conditions, at least during this brief period, were not substantially different than today. The lack of a significant number of river-type diatoms during this period indicates that the Velino River was likely not a significant contributor of carbonate or sediments to Lake Ventina. The presence of river diatoms in the oxidized band from 550 AD helps to confirm one of the things noted by

Riccardi (2006), that during flood events Lake Ventina and the Velino River become hydrologically connected. This is important because the two are rarely if ever connected on the surface today.

Interpreting the carbonate isotope record

Modern Lake Ventina water samples taken from a variety of seasons plot below

the local meteoric water line and define a local evaporation line (Figure 4). This indicates

that at present evaporative enrichment is likely the primary control of the isotopic

18 composition of δ Owater in the modern system. These values are quite distinct from

Velino river water (Figure 4), indicating groundwater flow direction is likely from the

lake to the river, rather than the converse. Furthermore, the crossplot of inorganic carbon

versus oxygen from the carbonate fraction shows a seasonal progression of values, with

more enriched values in the late fall, becoming increasingly depleted in the spring and 30

summer (Figure 6). Such a pattern is typical for carbonate precipitated in-lake in a

hydrologically closed seepage-type system fed by groundwater (Leng, 2006). This

interpretation is consistent with several other studies that have found the dominant driver

18 of δ OCarbonate in nearly every record from Mediterranean lakes is water balance (i.e.

relationship between P-E; Roberts et al., 2008; Jones and Imbers, 2010). This effect is particularly pronounced in closed-basin lakes, which only lose water though evaporation.

However, in semi-arid/arid environments like the Mediterranean even open-basin lake

systems can lose significant water to evaporation and thus show evaporative enrichment

tied to changes in P-E (e. g. Jones and Roberts, 2008). An added result of this process is

18 18 that δ OLakewater and δ OCarbonate values are typically significantly more enriched than

values of local and regional precipitation. Figure 5 shows the relationship between

18 18 precipitation, temperature and δ OLakewater, and supports that δ OLakewater in Ventina can

serve as a rough proxy for air and lake water temperature.

A common way to evaluate the impact of evaporative enrichment as a primary

18 18 13 driver of δ OCarbonate is to evaluate the correlation between δ OCarbonate and δ Ccarbonate

(Leng et al., 2010). The two isotopes tend to correlate in systems that are strongly

influenced by water balance (e.g. Dean et al., 2015; Sadori et al., 2016). This is because

during periods of negative water balance δ18O is enriched due to preferential evaporation

13 of lighter isotopes and δ CDIC is enriched due to greater exchange with less depleted

atmospheric CO2 (Leng, 2006). The opposite is true during periods of positive water

18 13 balance. The δ OCarbonate and δ Ccarbonate from the Lake Ventina core do not correlate (R

= -0.18; Figure 8). However, correlation between isotopes does not necessarily indicate

an isotopic system is not dominated by changes in water balance (Horn et al., 2016). 31

13 Changes in the source of DIC and shifts in lake productivity can affect δ CDIC

18 13 (Leng et al., 2010) and cause δ OCarbonate and δ Ccarbonate to be poorly correlated without

18 impacting the relationship between lake δ OCarbonate and water balance (Horn et al.,

2016). Changing human land-use practices are an example of something that can impact

13 δ CDIC by affecting lake productivity through runoff of fertilizer and other nutrients, and

is a plausible explanation in this system given the lengthy history of intensive agricultural

land-use in central Italy (Archer, 2017). The pollen record from Lake Ventina confirms

that the watershed has been managed for agriculture for at least the last 3000 years.

Castanea makes up >3% of the pollen sum in the oldest part of the record, and Cannabis

and cereals are present throughout.

13 Two periods with substantial deviations in δ Ccarbonate stand out in the Lake

Ventina record and both can be tied to changing human impacts. The first is the most

recent 100-150 years, where values are depleted by 1-1.5‰ compared to the remainder of

the record. This period is associated with eutrophication tied to the use of Nitrogen

fertilizer use and is indicated in the Lake Ventina record by high % organic carbon and

CaCO3 and the presence of diatoms, and anthropogenic eutrophication has been shown to

13 drive depletion of δ Ccarbonate (Hollander and Smith, 2001). The second is the period

13 from 750 to 950 AD which is characterized by two peaks in δ Ccarbonate values. The

beginning of this period is associated with an expansion in forest and wetland (primarily

Salix; see Chapter 2) as well as the presence of diatoms, suggesting an expanded wetland

surrounding the lake. Expanded biological activity in the lake would be expected to

13 12 enrich δ Ccarbonate as plants preferentially utilize lighter C. 32

Inwash of detrital carbonate can affect the isotopic composition of bulk

carbonates in lake sediment and is a common problem in regions such as Rieti that have

bedrock made up of marine carbonates. The influence of detrital carbonate may be

determined in several ways, including looking at the isotopic values relative to bedrock

values, comparing with other detrital proxy signals, and through smear slide analysis.

Carbonate bedrock in the Rieti region has δ18O values between -2 and 0‰ and δ13C

values between 2 and 4 ‰ (Morettini et al., 2002; Archer, 2017). These are both more enriched than the values associated with the carbonate from Lake Ventina sediments, supporting that at least a fraction of the carbonate is not detrital but authigenic. Secondly,

18 detrital carbonate may be discerned by comparing δ Ocarbonate with MS because the same

process that drives increased carbonate bedrock contribution (increased erosion/surface

runoff) also causes more material high in ferric minerals to be washed into the lake.

Records with substantial detrital inwash often have high correlation (>0.6) between MS

18 and δ Ocarbonate (Leng et al., 2010). In the Lake Ventina sediments, those two variables

have a correlation of R = .38. This value suggests some influence on the record from

detrital carbonate, a finding that is also supported by examination of sediments under a

light microscope, which reveals some detrital grains. However, the correlation between

18 MS and δ Ocarbonate is not strong, suggesting that detrital carbonate is not the primary

18 driver of δ Ocarbonate. Several other sedimentological and site characteristics also provide

18 evidence to support that detrital inwash is not a dominant influence on δ Ocarbonate. First,

based on the age model, sedimentation rates do not fluctuate substantially, something that

would be expected during periods of elevated detrital inwash. Secondly, there are few

major shifts in CaCO3 concentration, which is a characteristic signature of lakes with 33

high detrital inwash components. Third, high-resolution imaging of the sediment core and

qualitative evaluation during sampling has not revealed any significant variation in

grain/clast size. Periods of increased detrital inwash may be expected to be associated

with increased grain size. Finally, the Lake Ventina site today has no surface inflows,

making it a low energy system that is unlikely to transport substantial detrital carbonate

to the coring location at the depocenter of the lake. Overall the evidence suggests that

while detrital carbonate is likely to have impacted the isotope record, water balance

appears to exert a stronger influence.

Another possible non-climatic influence on the Lake Ventina isotope record is

human or natural modifications of the hydrological connection between Lake Ventina

and the Velino River. In the Mediterranean, human modification of inputs into a

lake/estuary have been invoked as a potential driver of isotopic change (Ariztegui et al.,

2010; Zanchetta et al., 2012). It has also been established that human-driven reduction in

fluvial input into lakes can impact the isotope geochemistry of a lake (Poraj-Górska et al.,

2017). One example is from Walker Lake, in the Great Basin where Yuan et al. (2006)

interpreted shifts in the δ18O/δ13C of carbonate record to be in part controlled by changes in the amount of water in the Walker River that was diverted north into the Carson Sink.

Today, the hydrological connection between the Velino River and Lake Ventina is only through groundwater flow, and the radically different isotopic compositions of water between the two water sources suggest a limited connection. However, a detailed

bathymetric map published in the 1920’s shows a canal connecting the two, and historical

maps from 1620 and 1649 AD, while not drawn with geographic accuracy (Riccardi

2006), clearly indicate that in the past that there was a natural connection. There is a 34

negligible difference in elevation between the lake surface and the river which makes

determining the direction of flow in that connection difficult (i.e. would the Velino be flowing into Lake Ventina or vis versa). However, in the modern system the distinct

isotopic values between the two indicate groundwater is flowing from the lake to the

river.

Climate reconstruction and lake history

The most visible feature in the Ventina isotope data is the period of depleted

18 13 δ Ocarbonate and enriched δ Ccarbonate from about 750 to 950 AD (Figure 7). This interval

consists or 2 excursions separated by one or two data points close to the baseline values

above and below. There are two possible drivers behind this feature, which may have

been working collectively. The first is a wetter climate leading to positive water balance

18 which resulted in less enriched values of δ Ocarbonate. Secondly, increased productivity in

the lake associated with expanded wetlands could have driven the enrichment in

13 12 δ Ccarbonate resulting from the depletion of C from the DIC pool through organic carbon

13 fixation. Enrichment in δ Ccarbonate values is not likely to be the result of more detrital

inwash from increased precipitation, because detrital carbonate is also enriched in δ18O

18 and this period in the record is associated with depleted δ Ocarbonate. These isotope

excursions are also associated with peaks in CaCO3 concentration (Figure 7).

Interestingly, diatoms, which are only intermittently observed in the core, are found

associated with the lower peaks and may be taken as a proxy for eutrophication and

increased photosynthetic activity.

An alternative explanation is that this signal represents a period when the Velino

River was contributing water to Lake Ventina. The river is isotopically depleted 35

compared to Lake Ventina, and the addition of Velino water could explain the depleted

18 13 δ Ocarbonate values. The Velino River also has enriched δ CDIC compared to modern

Ventina lake water and thus input into Lake Ventina could explain the shift to more

13 enriched δ Ccarbonate during this period. Without other geochemical measurements such

as C:N ratio of organic material (Archer, 2017), it is difficult to determine the driver of

the carbonate isotope signal during this period.

One approach to resolving this question and assessing how well the site is

recording low-frequency climate is to compare the record from Ventina to other local and

regional records. If the record from Lake Ventina, and particularly the signal in period

from 750 to 950 AD, has been identified in other records, it suggests climate was the

primary driver because shifts in climate tend to be regional. In Figure 9 the isotope record

from Lake Ventina is compared to that from Lake Lungo (Archer, 2017), which is in the

center of the Rieti Basin and about 10 km from Lake Ventina. Below 750 AD the two

lakes have very different signals, with Lake Lungo’s being associated with depleted

18 18 δ Ocarbonate and Lake Ventina’s being associated with enriched and variable δ Ocarbonate.

Beginning at around 750 AD and continuing to the top of the cores the two lakes have

similar signals. The most prominent feature in both lakes from this period is the shift in

18 δ Ocarbonate to more enriched values around 950-1100 AD. Both records also have more

18 13 depleted values for both δ Ocarbonate and δ Ccarbonate over the last 300 years. Overall, it

appears that both lakes are responding to the same environmental variables over the past

1250 years, but before then there is no agreement between the records.

When aggregated into broad taxa categories, lakes Lungo and Ventina have

similar pollen signals since 750 AD (Figure 9). The amount of forest pollen appears to 36

18 match the δ Ocarbonate record well in both lakes. Periods of increased forest cover (green

shaded areas in Figure 9) in the two lake’s pollen records match periods of depleted

18 δ Ocarbonate and vice versa (red shaded area in Figure 9).

Comparing the record from Lake Ventina to other regional records (Figure 9) can

help better interpret the record. Periods of Apennine glacial advance (Giraudi, 2005)

18 coincide well with periods of depleted δ Ocarbonate in both Lake Ventina and Lungo.

However, the lack of Holocene carbonate isotope records from Italy has been noted

(Giraudi et al., 2011; Roberts et al., 2008). The lack of sufficient carbonates in sediments from Italian lakes is cited as part of the reason, as is difficulty dating records using 14C

(Giraudi et al., 2011). The only record from stable isotopes of lacustrine carbonate that

covers the late Holocene at sub-decadal resolution is Sadori et al., (2016) from Lago di

Pergusa in Sicily. That record is characterized by substantially enriched

18 13 18 δ Ocarbonate/δ Ccarbonate compared with the lakes in the Rieti Basin and δ Ocarbonate and

13 δ Ccarbonate co-vary through most of the record. These reflect its more arid location and

thus stronger evaporative signal. Lago di Pergusa is also unambiguously a closed-basin

lake, something that is not true of any of the Rieti Basin lakes. The primary limitations of

comparing this record to Ventina’s are the 500 kilometers between the sites and significant dating uncertainties in both records. However, given that the Lago di Pergusa record appears to reflect regional shifts in climate, it is still useful. The most obvious similarity between the Rieti Basin records and the Lago di Pergusa record is the strong

18 shift in all 3 records to more enriched δ Ocarbonate at around 1000-1100 AD.

Although there are few climate records local to central Italy, there are many reconstructions from across Europe, which can be used to put this study in a broad 37

context. Natural climate variability in the western Mediterranean on millennial to multi-

centennial frequencies is primarily driven by changes in ocean and atmospheric

circulation in the north Atlantic. The North-Atlantic Oscillation (NAO) is a mode of

atmospheric variability that plays an important role in controlling winter storm track

position in the northern hemisphere (Visbeck et al., 2003). The NAO reflects variations in

the pressure difference between the subtropical high near the Azores and the subpolar

low near Iceland (Wanner et al., 2001), and influences precipitation and temperature

across Europe (Trigo et al., 2002). Because of the strong influence of the NAO on

western Mediterranean climate, climate reconstructions from the western Mediterranean

over the late Holocene are often compared to reconstructions of the NAO (e.g. Di Rita et

al., 2018). Arguably a persistent positive NAO may have been a key driver of climate

conditions during the Medieval Climate Anomaly (MCA), and negative NAO may have

been a key driver of the Little Ice Age (LIA) (Trouet et al., 2009), though this has been

disputed recently (Cook et al., 2019).

Figure 9 shows a comparison of the records from Lake Ventina and Lake Lungo

to a reconstruction of the NAO (Baker et al., 2015), the record of Apennine glacial

advance (Giraudi, 2005), and the reconstructed PDSI from the Old World Drought Atlas

(OWDA) for the point 42.5°N, 12.8°E (Cook et al., 2015), smoothed with a 30-year

spline. The Lake Ventina record broadly replicates much of the low-frequency variability in the NAO reconstruction within the error range of the age models associated with the two records. The OWDI does not have great explanatory power for Central Italy (Cook et al., 2015), but none-the-less is one of the few high-resolution records with coverage of

central Italy. This record matches several of the features present in the Lake Ventina 38

isotope record, including a pattern between 750 and 950 AD of two periods of wetter

conditions separated by a brief period of drought.

The most important take-away from comparing these records is how well they

appear to agree beginning at around 750 AD and continuing until at least 1800 AD. Most

records in Figure 9 identify cool/wet climate from around 750 to 950 AD and from 1450

to at least 1600 AD, and a warm/dry climate from 1050 to 1400 AD. Overall comparison

to several local and regional records suggests substantial coherence between

reconstructions from disparate locations. This lends support to the hypothesis that shifts

18 in the δ Ocarbonate record from Ventina are driven primarily by low-frequency climate variation.

Records, particularly those from Lakes Ventina and Lungo do not match well

18 prior to 750 AD. Archer (2017) suggests depleted δ Ocarbonate values from Lake Lungo

prior to 750 AD likely represent a period when the lake was surrounded by substantial

18 13 marsh. Depleted δ Ocarbonate and enriched δ Ccarboante values as well as elevated

CaCO3% during this period (Archer, 2017) are similar to the values during the 750-950 period in Lake Ventina. The Rieti Basin has a long history of human modification of its hydrology, beginning with Roman conquest in 270 BC (Mensing et al., 2015). It is plausible that the natural hydrological system of the Rieti Basin, with marshy wetland covering much of the basin floor, was not very isotopically sensitive to shifts in climate.

Only after reclamation efforts began, which reduced wetlands and began to isolate the

lakes, did the sediments from Lake Lungo begin to record climate. Changes in the Lake

Lungo isotopic system driven by changes in lake hydrology, in part caused by human 39

modification of the Rieti Basin, could explain why the two systems have such different signals prior to 750 AD.

While not as dramatic as in Lake Ventina, 750-950 AD (and particularly 800-900

AD) does correspond to a period of change in the Lake Lungo record (Archer, 2017).

13 CaCO3 % is elevated and δ Ccarboante values are enriched, with the caveat that only two

18 carbonate isotope samples date from this period. However, δ Ocarbonate values are not

substantially different than the preceding 1200 years of the record. Like in Lake Ventina,

this period appears to represent a brief expansion of wetland and increased biological

activity in Lake Lungo. Additional measurement of carbonate isotopes is necessary to

further investigate this signal. Overall, the records from Lake Lungo and Lake Ventina

appear largely complimentary. Differences, particularly prior to 750 AD, likely result

from dramatically different hydrological conditions in Lake Lungo than today.

6. Conclusions

Sampling of modern Lake Ventina water and measurement of δ18O/δ2H reveals a

system sensitive to changes in water balance on a seasonal basis. Comparison to a local

meteoric water line and isotopes of rain water reveal Lake Ventina is recharged primarily

from local rainwater and shallow-aquafer groundwater. Two large observed shifts in

18 13 δ Ocarbonate and δ Ccarbonate from Lake Ventina are most likely responding at least in part

to changes in regional climate. This conclusion is supported by isotopic analysis of the

modern lake system as well as a comparison between the Lake Ventina record and other

regional records of climate. The most obvious signal from the Lake Ventina record is the

18 period from 750-950 AD associated excursions of depleted δ Ocarbonate and enriched 40

13 δ Ccarbonate values accompanying increased TIC concentration. These excursions are best

explained by increased primary productivity, as they are also accompanied by increased

TIC and the occurrence of diatom assemblage similar to the modern lake, which is highly

18 eutrophic. Depleted δ Ocarbonate values may also indicate this period was wetter than

18 average. The shift to drier conditions can explain the more enriched δ Ocarbonate around

950 AD, is replicated in a number of other local and regional records.

A comparison of water isotopes between Lake Ventina and the two lakes in the

center of the Rieti Basin (Lungo and Ripasottile) reveals significant differences between

them. Water samples from Lakes Lungo and Ripasottile (Archer et al., 2017) do not

exhibit the same consistent enrichment response as those from Lake Ventina, and do not

plot closely to a linear trend line. Lungo and Ripasottile are more hydrologically open

and have more complex hydrologic histories which can potentially confound climatic

interpretations from their isotopic records. Despite this, the Lake Lungo carbonate isotope record shows an enrichment phase in δ18O during the medieval period similar to

Lake Ventina. The unusual signal in Lake Ventina from 750-950 AD is present in Lake

Lungo but is much less dramatic. Additional measurements of carbonate isotopes form

Lake Lungo are necessary to further evaluate this relationship.

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8. Figures

Figure 1: A: Location map of Lake Ventina, Italy (left), and its relation to Lake Lungo and Lake Ripasottile located within the Rieti Basin (right). B: Lake Ventina is the early 20th century. Reprinted from Riccardi (2006). A

B 47

Figure 2: images of the Lake Ventina master core. Individual core sections are labeled in red and the run depths associated with the top and bottom of each section are labeled in black.

Figure 3: Lake Ventina age model.

Figure 4: Isotopic composition of modern water samples (δ18O and δ2H) from Lake Ventina (light blue circles) and the Velino River (dark blue squares) along with the Mediterranean (MMWL), global (GMWL), and local meteoric water lines (LMWL).

: Monthly average air temperature and precipitation extracted from the Colli Sul Velino Sul Colli the from extracted precipitation and temperature air average : Monthly Figure 5 chemistry. water of lake measurements with compared Ventina near Lake station weather 51

Figure 6: Oxygen isotopes of water vs Carbon isotopes of dissolved inorganic carbon for Lake Ventina (light blue circles) and the Velino River (dark blue squares).

Figure 7: Carbonate isotopes, Diatom Presence (red bars), LOI data (Total Organic Carbon [TOC] and Total Inorganic Carbon [TIC]), and magnetic susceptibility (MS) from the Lake Ventina master core.

Figure 8: Scatterplot of carbonate isotopes from Lake Vetnina. The number associated with each sample is the approximate date (in BC/AD).

Figure 9: Comparison between Lake Ventina and local and regional climate records. 18 From left to right: Lake Ventina δ Ocarbonate (this study), PDSI reconstruction (Cook et 18 al., 205), NAO reconstruction (Baker et al., 2015), Lake Lungo δ Ocarbonate (Archer, 2017), glacial advances (Giraudi, 2005), Lake Ventina total percent tree pollen (this study), and Lake Lungo total percent tree pollen (Mensing et al., 2015)

9. Tables

Table 1: Physical and chemical parameters of Lake Ventina water. Measurements taken by the regional environmental protection agency, ARPA Lazio

Date Temperature Total P Alkalinity pH Conductivity Secchi depth - °C mg/L mg/L Ca(HCO3 ) µS/cm m 5/2/2011 16.2 - 413.1 8.28 410 1 5/2/2011 13.9 - 413.1 7.87 395 4.5 8/24/2011 - - - - - 0.5 8/24/2011 - - - - - 1.4 8/24/2011 - - - - - 2.4 9/16/2011 24.16 0.03 - 8.59 341 0.5 9/16/2011 23.8 0.03 - 8.57 338 2 10/24/2011 - - - - - 2 10/24/2011 - - - - - 0.5 11/23/2011 8.3 0.09 283.5 7.83 311.5 2.5 11/24/2011 8.5 0.13 283.5 7.9 310.5 0.5 12/7/2011 - - - - - 0.5 12/7/2011 - - - - - 2.5 1/25/2012 4.6 0.01 267.3 8 315 0.5 1/25/2012 4.6 0.012 283.5 8 316 3 5/20/2013 18.9 0.023 245 8.1 453.1 2 5/20/2013 19.1 0.017 245 7.96 449 0.5 6/17/2013 - - - - - 0.5 6/17/2013 - - - - - 2.5 6/18/2013 - - - - - 4 7/10/2013 23.9 0.058 250 8.1 456.4 0.5 7/10/2013 21.1 0.001 240 7.9 468.4 3 8/28/2013 - - - - - 0.5 8/28/2013 - - - - - 3 9/20/2013 20.3 0.009 265 8.1 488.2 3 9/20/2013 20.6 0.007 335 8.2 488.4 0.5 10/18/2013 - - - - - 3 10/21/2013 - - - - - 0.5 11/18/2013 13.1 0.006 270 8.5 467.8 3 11/18/2013 13.3 0.013 265 8.5 467.9 0.5 12/20/2013 - - - - - 0.5 12/20/2013 - - - - - 3 Average 15.9 0.03 289.93 8.15 404.76 1.71 Standard Dev. 6.68 0.037 57.36 0.26 70.75 1.25 56

Table 2: Indicators of nutrient loading from lakes in and near the Rieti Basin.

Water DIC 2 δ HVSMOW 18 13 Date (m/y) δ OVSMOW (‰) (‰) δ CVPDB (‰)

Velino River Jul-14 -8.7 -55 -4.7 Feb-15 -8.1 -50 -6.6 May-15 -8.7 -56 -4.1 Sep-15 -8.7 -56 -3.1 Jul-17 -8.6 -55 N/A

Lake Ventina Nov-16 -1.8 -19 -8.1

May-17 -1.9 -19 N/A Jun-17 -0.6 -13 N/A Jul-17 0.1 -10 N/A Mar-18 -4.1 -31 -10.6

May-18 -4.6 -33 -10.6

Jun-18 -4.3 -31 -10.5 Jul-18 -3.6 -28 -10.4 Sep-18 -2.8 -25 -8.7 Nov-18 -2.6 -23 -7.5

Table 3: Isotope data for modern water samples from Lake Ventina and the Velino River, Italy.

Phosphorus (mg/L) Secci disk (m) Lake Ventina 0.031 1.71 Lake Lungo 0.035 1.77 Lake Ripasottile 0.017 1.75 57

Chapter 2: Spatial and temporal patterns of environmental change over the last 3000 years from the Rieti Basin, central Italy

Abstract

Fossil pollen is a valuable tool for reconstructing environmental change and

helping evaluate the impacts of climate and humans. By comparing history to pollen

records scientists can begin to evaluate how changes in political control impact the

landscape. Here I present a 3000 year pollen record from Lake Ventina, central Italy, and

compare it to history and another nearby pollen record from Lake Lungo. Utilizing

multiple pollen records in the same region and at similar temporal scales improves

understanding of local spatial patterns in environmental change. Findings from this study

include: chestnut (Castenea) and hemp (Cannabis) were important cultivates back to the pre-Roman period, Roman conquest did not have a substantial impact on the landscape, and forests were limited prior to 1400 AD and expanded significantly after. Comparison with the Lake Lungo pollen record indicates several deviations between records, including that Lake Ventina has a much more extensive record of chestnut and cannabis cultivation, a much more open and anthropogenic landscape pre-1400, and less extreme late Middle Ages forest degradation. The impact of Roman conquest at the two sites is very different, with little impact at Ventina but substantial forest clearance at Lungo.

These results have important implications for analyzing interactions between climate, humans, and the environment and illustrate how geographically very similar pollen records can produce somewhat different but complimentary results.

1. Introduction

It is increasingly apparent that humans have had a large role in changing the

composition and structure of species on the landscape for millennia. The scope of human

activity, and the specific landscape changes they have created in the past are critical to

understanding modern ecological dynamics (Whitlock et al., 2018). However, the ability

to distinguish human caused impacts as opposed to climatic-driven changes when reconstructing past environments is a challenge that requires three specific elements: a high-resolution record of vegetation change, an independent record of climate change, and historical and/or archaeological evidence of human land use activities. The number of studies that are able to incorporate all three of these elements to provide a more nuanced picture of causes of landscape change are still few (e.g. Sadori et al., 2016; Di

Rita et al., 2018) although there has been a new emphasis on this recently. The presence of extensive local written histories (e.g. Leggio 1994; 1998) and archaeology (Coccia et al., 1992; 1995) in and around the Rieti Basin, central Italy have established a chronology of political and economic control that can be linked to land use. Paleoecologic studies have linked environmental change in the region to the narrative of political, demographic,

economic, and technological change (Mensing et al., 2015; 2016; 2018; Schoolman et al.,

2018).

This study builds on that research by comparing established historical narratives with a new 3000-year pollen record of environmental change from Lake Ventina, located just north of the Rieti Basin. Additionally, it examines to what extent human impacts occurred at local or sub-regional scale by comparing this new record to a nearby record from Lake Lungo (Mensing et al., 2015), in the Rieti Basin. Local-scale environmental 59

impacts that might cause the signal from the two lakes to diverge may include human

activities such as differences in local political control or the spatial distribution of transportation networks, as well as physical controls, such as topography. Our ability to evaluate these different variables is enabled by both the rugged topographic setting around the Lake Ventina watershed as opposed to the flat valley within the Rieti Basin, and Lake Ventina’s location outside of the basin, further from the Rieti urban center that likely affected local land-use and intensity of human management of the landscape. This work has important implications for how we use individual pollen records to characterize regional trends in environmental change.

Paleoecologists have stressed the importance of humans as the key driver of vegetation change in Italy over the last 2-3 thousand years (e.g. Mercuri et al., 2002;

Mensing et al., 2015; Sadori et al., 2016). Humans became a significant driver of environmental change in records from coastal Sardinia (Beffa et al., 2016) beginning at

700 BC, Sicily beginning 850 (Tinner et al., 2009) and 650 BC (Noti et al., 2009), and southern Italy beginning 750 BC (Caroli and Caldara, 2007; Di Rita and Magri, 2009). In central Italy, major human influence began ~1050 BC near Rome (Mercuri et al., 2002).

Several records from northern Italy have found significant human impacts as early as

2,000 BC (Kaltenrieder et al., 2010; Mercuri et al., 2012).

The impact of humans on the landscape of central Italy is typically reflected in two ways in pollen records, the first of which is changes in forest cover. Significant declines in forest are likely a result of clearance by people (e.g. the medieval period in

Rieti, beginning at 900 AD [Mensing et al., 2015], during the Bronze Age in the Po River

Valley beginning 1500 BC [Mercuri et al., 2012]). The inverse is also true, that 60

significant forest regeneration is likely primarily a result of less intense management of the landscape by humans. The second way human impacts are reflected in pollen records is through identification of pollen from plants closely associated with agriculture. This includes cultivates such as hemp (Cannabis), cereals, corn (Zea mays), olive (Olea), and

grape (Vitis vinifera) as well as plants which are strongly associated with agriculture and

animal husbandry such as Chicoreae (See table 1 for a list of common taxa and their

common names), Plantago, and Urtica (Mercuri et al., 2013). This study tracks both forest cover and taxa associated with agriculture to reconstruct the intensity of human impacts on the landscape.

2. Site

Vegetation

The climate, geology, and limnology of Lake Ventina are discussed in Chapter 1.

Here I limit the discussion to a description of the vegetation of the area around Lake

Ventina. The lake is surrounded by forested hills, with the most common vegetation

assemblage being Mediterranean temperate deciduous forest composed primarily of

Quercus pubescens, Q. cerris, Carpinus orientalis, and Ostrya carpinifolia. Much of the

area devoted to these trees is actively coppiced for wood on a ~20 year rotation. There is

at least one small grove of Castanea in the watershed, but it does not contribute

significantly to the forest composition outside of areas where it is being cultivated. At

lower elevations Q. ilex is common, and because the hills surrounding Lake Ventina only

reach 1000 m elevation, mesic and alpine adapted tree species like Fagus sylvatica are

largely absent. The relatively restricted basin floor is mostly devoted to agriculture. 61

Riparian or floodplain communities are limited to a narrow band around Lake Ventina

and along the Velino River, and a small wetland area to the east of the lake. These

communities are dominated by Phragmites and Salix.

3. Methods

Core recovery, sediment analysis and description, and age control are discussed in

Chapter 1.

Pollen analysis

Eighty-four samples (0.625 cc volume) were processed for pollen analysis using

standard acid digestion methods (Faegri et al., 1989). A known quantity of an exotic

tracer (Lycopodium) was added to each sample at the start of processing and counted

along with pollen for calculating pollen concentration (Stockmarr, 1971). Samples were

taken at regular intervals, every 20 cm in the composite Ventina core, in order to assess

broad patterns of vegetation change. Additional samples were then analyzed to expand

the sampling resolution in sections with substantial shifts in pollen assemblage or which

correspond to periods of interest in the historical record. Overall sampling resolution was

one sample every 15 cm. Samples were counted either to a minimum of 300 terrestrial

grains (n = 62), or, if pollen concentration was exceptionally low, 250 terrestrial grains (n

= 22).

Pollen and non-pollen palynomorphs were identified using reference material in the University of Nevada Paleoecology Laboratory and published reference guides and keys (Kapp et al., 2000, Chester and Raine, 2001; Beug, 2004). Deciduous oak species

(Q. cerris or Q. pubescens – robur) were aggregated into a single category. TC (Taxaceae 62

and Cupressaceae) pollen was assumed to be Juniperus because it is the only member of

that group which contributes significantly to land cover in the region. Cereals were

differentiated from other members of the Poaceae family following Köhler and Lange

(1979). Pollen percentages were calculated from the total pollen sum excluding Alnus, a

riparian species that only grows along the lakeshore, and reaches >30% in several

samples, dramatically affecting the relative percentage of other pollen taxa.

Statistical analyses were performed on a pollen dataset consisting of all taxa

which contributed >0.5% to the total pollen sum of the dataset using Past (Hammer et al.,

2001). Constrained cluster analysis was used to identify breaks in the data and is the basis

for the zonation in the pollen diagrams. Non-metric multi-dimensional scaling (NMDS),

based on Bray-Curtis distances was used to identify ecological gradients, detect periods of land-cover change, and quantitatively compare pollen assemblage between samples.

1. Results

Stratigraphic Analysis

Zone 1a: 1000 BC to 760 AD

Two main zones (1 and 2) were inferred from the cluster analysis (Fig. 1) with

three subzones (1a, 1b and 1c) within Zone 1. The average temporal resolution for pollen

analysis is one sample every 36 years. In Zone 1a, most samples are characterized by low

to moderate tree pollen, around 30% of the total pollen sum (Fig. 2). Quercus (deciduous)

and Castanea are the most common tree taxa (Fig. 3). Mesic forest taxa such as Carpinus betulus and Fagus are only present in low percentages. Riparian or floodplain taxa vary 63

wildly. Alnus spikes to above 10% of the total pollen sum several times during this period, the most pronounced of which occurred prior to 600 BC, between 100 and 300

AD, and between 600 and 700 AD. These peaks often comprise only a single sample (e.g.

samples at 690 BC [33% Alnus] and 620 AD [13% Alnus]), even though samples on

either side of these peaks date to within 50 years. For example, Alnus increases from

3.4% to 22.5% of the pollen sum in samples which date from 900 and 860 BC,

respectively, and decreases from 19.4% to 1% in samples which date from 220 and 240

AD, respectively. The most extreme Alnus peak dates to 130 AD and comprises 45% of

the total pollen sum for that sample.

Herbaceous taxa make up around 50% of the total pollen sum, and shrubs/vines

make up about 5% (Fig. 2). Indeterminate grains average about 10% of the total pollen

sum and represent mostly oxidized/re-worked grains (Fig. 3). The most common taxon is

Poaceae, which averages about 10%, followed by ferns and Chicoreae, which each make

up 5-10% (Fig. 4). Cannabis is also present in moderate levels throughout this time

period, making up 2-5% of the pollen in most samples. Cereal grains are present

throughout in low levels. No shrub or vine makes a consistently large contribution to the

pollen sum. Artemisia is the most common shrub/vine, and Vitis vinifera is present at

levels above 1% in several samples, particularly prior to 200 BC.

NMDS Axis 1, which corresponds to openness, is positive (less forested) for most

of this zone, with only brief deviations into negative values between 200 BC and 300 AD

(Fig. 5). NMDS Axis 2, which corresponds primarily to the amount of riparian taxa is

negative (more riparian) for most of the record prior to 400 BC and during the period

between 100 and 300 AD, and otherwise positive. Glomus and Sporomiella both peak 64

during the period between 1 and 300 AD and are otherwise present at moderate to low levels.

Zone 1b: 760 to 800 AD

Zone 1b covers only 40 years, consists of 3 samples, and is characterized by high tree (around 50%) and riparian (20%) pollen and low herb pollen (around 25%) relative to Zones 1a and 1c. Both NMDS Axis 1 and Axis 2 are negative during this period, suggesting greater forest cover and more riparian vegetation growing around the lake.

Higher tree percentages in this period are driven by an increase in Quercus (deciduous) and Ostrya type as well as several other less common forest taxa, including Carpinus betulus, Corylus, Quercus ilex, Fagus, and Betula. Castanea is the one major tree taxa which is less common in Zone 1b than in Zones 1a and 1c. Riparian pollen in this period are a mix of Alnus and Salix, which average 13% and 7.5%, respectively. The decline in the percentage of herbaceous taxa is driven by a reduction in the percentage of the most common taxa, including Poaceae, Cannabis, and Chicoreae. This zone is also characterized by an increase in Juniperus, a decrease in indeterminate grains, higher than average overall pollen concentration, and very low Glomus and Sporomiella.

Zone 1c: 800 to 1450 AD

Zone 1c is characterized by low tree (30%) and high herbaceous (50%) pollen.

Riparian taxa generally have low to moderate percentages and are present in higher percentages at the beginning and end of the zone. The dominant taxa in this zone are very similar to those in most of Zone 1a. Castanea is slightly less common and Ostrya type,

Cannabis, ferns, and Juniperus are slightly more common than in Zone 1a. Sporomiella peaks in the second half of the zone, to the highest concentration at any time in the Lake 65

Ventina record. Glomus generally has low to medium concentration, and the percentage

of indeterminate grains is the highest in the record. Both NMDS Axis 1 and Axis 2 are

positive throughout Zone 1c, indicating an open, less forested environment with sparse

riparian vegetation.

Zone 2: 1450 to 2014 AD

Zone 2 is characterized by high tree (50%) and low herbaceous (35%) pollen.

Riparian pollen is low (3%) and shrub/vine pollen is higher than at any other time in the

record (8%). The elevated percentage of tree pollen is driven primarily by increases in

Quercus (deciduous), Ostrya type, Carpinus betulus, Quercus ilex, Olea, and Pinus.

Castanea is the only major tree taxa that is substantially lower in Zone 2 than in Zone 1.

There is very little Alnus in Zone 2, and the riparian taxa are dominated by Salix. The decline in herbaceous taxa from Zones 1a and 1c is not driven by a change in Poaceae or

Cannabis, which both maintain their percentages though most of Zone 2. The reduction in herbaceous taxa is instead driven by dramatic reductions in ferns, Chicoreae, Urtica,

and several other less common taxa. The increase in shrubs/vines is driven primarily by

an increase in Juniperus, to the highest levels found in the record. Sporomiella is

generally low, Glomus rare, and indeterminate grains are lower than anywhere else in the record. NMDS Axis 1 is strongly negative, suggesting that Zone 2 represents the least open, most forested part of the record. NMDS Axis 2 is generally slightly negative, indicating low levels of riparian vegetation.

Ordination Analysis

NMDS ordination (Figure 5) of the Lake Ventina pollen data reveals key patterns.

Most samples from Zones 1a and 1c, ranging from 1000 BC to 1450 AD, cluster closely 66

together. This includes the oldest sample in the record (dating to 990 BC) and the very

top-most sample of Zone 1 (dating to 1440 AD). There are no significant long-term trends or permanent transitions in the pollen data from the bottom of the record until

1440 AD. In samples which fall into Zones 1a and 1c, variation in the pollen assemblage is driven primarily by spikes in riparian vegetation, mostly Alnus. Riparian dominated samples plot apart from all other samples in Zone 1 (Figure 5). The Roman period is characterized by substantial variation between individual samples. In Figure 5, samples from the first century BC though the 3rd century AD are labeled in red and encompass

essentially the entire range of pre-1450 AD pollen variation. Nowhere else in the Lake

Ventina record do we see such radical change in pollen composition between sequential

samples.

The samples from Zone 1b (770 to 800 AD) are unique. The NMDS ordination

highlights the constrained cluster analysis showing that these three samples fall to the left side of the diagram, indicating that they are dominated by forest and are significantly different than the rest of the record prior to 1450 AD. Additionally, samples from Zone

1b contain significant riparian taxa and thus plot below post-1450 AD samples which have very little riparian vegetation.

The shift in pollen assemblage at about 1450 AD that is the transition from Zone

1c to Zone 2 in the constrained cluster analysis is radical and permanent. There is no overlap in ordination space between samples before and after this transition.

5. Discussion 67

Pollen taxa relationships

A correlation matrix (Table 2) was created to examine the relationships between pollen taxa in the Lake Ventina record. These relationships can help improve the interpretation of landscape change. Poaceae is consistent throughout the pollen record and does not have strong correlations (positive or negative) with any other taxa. This is likely in part because the Poaceae family encompasses many species that fit a variety of ecological niches. For example, the Phragmites that ring the lake today are in the Poaceae family, as are many of the plants that make up both the understory in forests as well as meadows in the Lake Ventina watershed. It also suggests that the landscape was never dominated by old-growth forest with a well-developed canopy under which grass does not grow well. Instead, it indicates that woodland or open pasturage has been important land-cover in the basin since at least 1000 BC.

The single strongest relationship in the dataset is a 0.76 correlation between

Juniperus and Quercus (deciduous). This reflects that both taxa are at their highest levels in samples which date from after 1450 AD. Interestingly, today these taxa do not grow in the same locations on the landscape. Juniperus typically comes from shrubs (species?) which grow in the middle/edges of meadows, while Quercus (deciduous) (Q. cerris and

Q. pubescens-robur) is one of the dominant forest taxa in the watershed.

Juniperus has strongly negative correlations with indeterminate grains, Castanea, and ferns. All 3 are present at much higher levels in samples prior to 1450 AD. In general, the strongest correlations in Table 2 appear to be driven by the shift in landscape which occurred at 1450 AD. Given that Juniperus is associated with meadows and other open landscapes today, it suggests that the structure and ecology of meadows changed at 68

1450 AD. If the ecology of the area didn’t change, then Juniperus should have been

present in higher numbers prior to 1450 AD, when the pollen record from Lake Ventina

suggests conditions were more open. This is important in part because many of the taxa

associated with meadows today are largely silent (see Chapter 3) and thus do not appear

in high percentages in the pollen record.

Ostrya and Quercus (deciduous) are both negatively correlated with Castanea (R

= -0.55, -0.62, respectively). Given all three taxa represent trees with similar natural ecologies, the fact that the former two correlate negatively with the latter suggests that humans have played a role in shaping Castanea’s presence and distribution in the watershed. This is unsurprising given the well-documented role Castanea has played in the region as a source of animal feed, food, and wood (Squatriti 2013). However, it is an important finding because the Lake Ventina record contains moderate to high levels of

Castanea from the beginning of the record, which is well before many historical sources indicate Castanea was widely cultivated in the region (Squatriti 2013). Today, Castanea is found in a handful of small groves in the watershed and is not a significant presence in the Ostrya and Quercus-dominated forests being managed primarily for wood.

The two dominant riparian taxa, Alnus and Salix, do not strongly correlate (R =

0.17). One of the major features of the Lake Ventina pollen record is the high variability in riparian pollen, mostly driven by high percentages of Alnus. However, if those fluctuations were driven by fluvial transport and deposition of riparian pollen during flood events, and not growth of vegetation around the lake, we would expect the two dominant riparian taxa to co-vary. That they do not is evidence that shifts in Alnus 69

percentage are being driven by the amount of Alnus growing around the lake and can tell

us something about either human management of the riparian zone or changing climate.

To further evaluate the source of Alnus I’ve examined the relationship between its

percentage of the pollen sum and sediment appearance between 100 BC and 300 AD

(Figure 6). This period includes the most extreme Alnus spike in the record (sample

dating to 130 AD contains 45% Alnus) as well as samples with <5% Alnus. There does

not appear to be a visual relationship between stratigraphy and Alnus percentage, further

suggesting that flood-born sediment is not the ultimate source of the Alnus in the Lake

Ventina record.

Comparison with other local records

The Lake Lungo pollen record

In order to improve the interpretation of the Lake Ventina pollen record, assess

local variation in environmental change, and better differentiate human and climate as

drivers, the record is compared with the record from Lake Lungo (Mensing et al., 2015).

Figure 7 reveals broad relationships between the pollen records from Lake Ventina and

Lake Lungo, and Figure 8 compares the total tree pollen in the two lakes with the record of climate from Lake Ventina (Chapter 1). Tree pollen in these figures is defined as non-

anthropogenic (i.e. not including Olea, Juglans, and Castanea [OJC]) and non-riparian.

Riparian taxa, of which Alnus is the dominant taxon, was excluded from the calculation

of total tree pollen because it is restricted to riparian/floodplain land and is sensitive to

small changes in lake hydrology. Changes in Alnus are sometimes so great as to mask changes in non-riparian forests, and the goal of this figure and analysis is to evaluate

landcover change through time beyond the riparian habitat. 70

Percent total non-riparian, non-cultivate tree pollen likely reflects a combination

of the intensity of human management of the hillsides surrounding each lake, the

vegetative response to climate, and the interaction between the two. In order to

differentiate these potential drivers when analyzing specific periods of environmental

change in the Lake Ventina record, two approaches are taken. First, the pollen from both

sites is compared to the climate record from Lake Ventina. Cool/wet climate is expected

to facilitate increased forest cover, and warm/dry climate is expected to facilitate a

decrease in forest cover. Second, if climate is the primary driver of environmental change

it should have similar impacts on the signal from both lakes, which are less than 10 km

apart and have watersheds that are similar ecologically. If the two lakes have different

signals, it eliminates climate as the primary mechanism of landcover change.

Pollen records from Lake Ventina and Lake Lungo (Figures 7) have very different

signals prior to 750 AD and very similar signals after 750. Prior to 750 AD the Lake

Ventina record has low tree pollen percentage (around 20%) and has no long-term trend.

The Lake Lungo record has high tree pollen percent prior to 1 AD (around 55%) and shifts towards less forest over the following 700 years. Both sites show afforestation from

750 to 850 AD, though the duration of forest recovery shown in the Lungo record is longer than in the Ventina record. The 10th through 14th centuries in both records are

dominated by very low tree pollen percentages, and both show a rapid increase in forest

cover beginning around 1350 AD which peaks from 1500 to 1600 AD.

In part, the two records differ because of the contrasting topographies of their

basins. The Lake Lungo record appears very sensitive to changes on the floor of the Rieti

Basin, including the draining or reclaiming of land for agriculture, while the Lake 71

Ventina record is more sensitive to changes in the hills. This is because there is limited

basin floor around Lake Ventina; surrounding hills are only 1000 m elevation, and most

Fagus in the region grows above 1000 m. In contrast, Lake Lungo is surrounded by

broad, flat, floodplain and we know from historic maps (Riccardi, 2006) and historical

accounts (Schoolman et al., 2018) that wetlands and lakes covered large areas of the

basin prior to 1750 AD. Lake Lungo has a much larger contribution of mesic forest taxa

like Fagus because the hills surrounding Lake Lungo are much higher elevation (2000 m)

than those surrounding Lake Ventina (1000 m). Fagus in this region is generally

restricted to areas above 900 m.

Why do the environmental records from the Rieti region begin to respond very similarly beginning around 750? This question is central to understanding the specific roles humans play in altering landscapes. The record from Lake Lungo has been interpreted as reflecting primarily anthropogenic impacts driven by historical events, with climate playing a secondary role (Mensing et al., 2015; 2016; 2018; Schoolman et al.,

2018). If climate is not considered the primary driver of environmental change in the region, there should be evidence of an economic, political, or demographical change about 750 AD towards more homogenous land use. The following section discusses how the analysis of pollen and isotopes from Lake Ventina can improve our ability to detect and separate the effects of human and climate as drivers of environmental change in the

Rieti Region.

Comparison with other local records

The Lake Ventina pollen record is also compared with two other nearby records

(Figure 8). A record of erosion from the Turano drainage basin just south of Rieti 72

(Borrelli et al., 2014) provides a valuable reconstruction of the intensity of human land-

use to compare against the pollen records from Lakes Ventina and Lungo. It utilizes the

sum probability of 36 radiocarbon dates from fluvial terraces of a tributary of the Velino

River to reconstruct periods of alluviation driven by erosion of upland areas in the basin.

Changes in erosion are interpreted as reflecting changes in land-use, with periods of more intense exploitation associated with greater environmental degradation and erosion. This is consistent with other records from the Mediterranean (e.g. Casana, 2008; Benito et al.,

2008) which attribute erosional periods with expansions of agro-pastoral activities, specifically on hilltops and other steep slopes (Butzer, 2005).

The record of Tiber flooding at Rome is one of the best-studied pieces of environmental history anywhere in Europe (citations). Variations in the frequency of

Tiber flooding from the 3rd century BC has generally been interpreted as reflecting a mix

of changes in climate, land use, and biases in the historical record (Aldrete, 2007). By

comparing it to the pollen record from Lake Ventina I am able to better distinguish

drivers in addition to utilizing it to interpret drivers of environmental change.

Separating climate and human-induced environmental change

One of the key challenges interpreting the record from Lake Lungo (Mensing et

al., 2015; 2016; 2018; Schoolman et al., 2018) was detecting the specific roles climate

and humans have played in changing the environment and assessing which had primacy

during different periods. The primary approach taken with that record, which is similar to

that taken by others in Italy (e.g. Sadori et al., 2016; Di Rita et al., 2018), was to compare

independent records of climate with the historical and archaeological record from the area

in order to create a reconstruction of potential environmental impacts. These are then 73

compared with the pollen-based environmental reconstruction, and in places where one or both sets of drivers indicate impacts which match the pollen signal, causality is suggested.

In establishing the primacy of humans, it is particularly effective to compare historical and archaeological records with anthropogenic indicators in the pollen record such as cultivates (e.g. cereals, Cannabis, OJC), indicators of grazing (e.g. Sporomiella), and other taxa associated with agriculture (e.g. Plantago, Chicoreae). Comparing records of environmental change to records of climate is a common approach to identifying periods where climate was important (e.g. Mensing et al., 2015; Sadori et al., 2016; Di

Rita et al., 2018). The isotope-based climate reconstruction from Lake Ventina is especially useful for this approach because it provides a local record of climate. It is also particularly effective because the climate and environmental records are from the same sediment core, so the timing of shifts are not in question. One of the major sources of uncertainty when analyzing drivers of environmental change is error associated with comparing age models between records, and differences in age control affect potential synchronicity and thus how we interpret drivers.

As an example of the kind of analysis that can be performed by comparing records of climate with pollen reconstructions of environmental change, we look at how forest cover might be affected. An increase in forest must be preceded by the change in climate if climate is the primary driver because it takes decades for the distribution and extent of forests to shift in response to a change in precipitation or temperature. This is important because it is plausible that a large increase in forest cover may be driven at least in part by climate, particularly if the landscape contained large areas of human- 74

created open spaces beforehand. If left undisturbed, trees can colonize hillsides rapidly because in this region of central Italy the landscape is naturally dominated by forest, and coppiced trees can rapidly increase in size and pollen productivity. In contrast, a sharp decline in forest, absent evidence of a significant disturbance event (e.g. a major forest fire), must be driven by humans. Forests, once established, are relatively stable ecosystems which without human impacts are unlikely to decline rapidly (i.e. in the span of decades) as a result of climate change.

Our ability to separate humans from climate as the key driver of environmental change is further improved by a comparison between two pollen records from nearby sites with similar ecologies. If the pollen records from Lake Ventina and Lake Lungo show substantially different responses, climate can be ruled out as a primary driver because climate would be expected to impact both records similarly (e.g. forest and riparian taxa increasing in both records as a response to cool/wet climate). The opposite is not true however; if both records are responding similarly, we cannot conclude climate is the primary driver based on this analysis alone. By using the approaches outlined above we interpret the Lake Ventina pollen record in terms of the impacts of climate and humans, and improve our understanding of spatial and temporal trends in environmental change across the Rieti region.

Lake Ventina pollen interpretation

The Pre-1450 Landscape

The Lake Ventina pollen record prior to 1450 AD is dominated by high levels of anthropogenic indicators and low total arboreal pollen percentages. This includes nearly the entire pre-Roman (1000 to 250 BC), Roman Republic and early Imperial period (250 75

BC to 100 AD), the era of Ostrogoth and Lombard political control (400 to 750 AD), and

the entire mid to late middle ages (850 to 1400 AD). Only the mid and late Roman

Imperial period during the 2nd and 3rd centuries, the Carolingian conquest (750 to 800

AD), and several small deviations in the pre-Roman period represents shifts from this landscape. The pre-1450 pollen record is characterized by high Castanea pollen, which averages 8.8% during this period, and significant contributions from cereals and

Cannabis. The record also includes high percentages of herbaceous taxa which have been interpreted to indicate human impacts (Mercuri et al., 2013), including Plantago,

Chicoreae, and Urtica. Overall non-riparian non-cultivate forest taxa make up only about

20% of the total pollen sum through much of the pre-1450 period at Lake Ventina. This

contrasts with most pollen records from lake sediments in Italy which contain 60+

percent arboreal taxa, at least until the later Middle Ages (e.g. Allen et al., 2002; Mercuri

et al., 2002; Di Rita et al., 2018). Even the record from Lake Lungo contains >50% arboreal pollen prior to 900 AD. Thus, the early development (in place by at least 1000

BC) and persistence of the highly anthropogenic landscape around Lake Ventina is remarkable. Samples which date from 900 BC and 1370 AD are virtually indistinguishable in ordination space (i.e. they plot very close to each other, Figure 5).

Historically, settlement and land-use intensified substantially during the medieval period in Italy, driven at least in part by the process of incastellamento, which involved the construction of numerous fortified hill towns, including in the Rieti region. This included the settlement of Moggio, chartered in 1152 AD (Coccia, 1992) in the hills above Lake

Ventina. Given that this process did not cause a significant shift in the pollen assemblage 76

from Lake Ventina, it supports the conclusion that the watershed was being managed

intensively during the Iron Age, well before Roman conquest.

Even with differences in the surrounding topography, the divergence between

pollen signals from Lakes Lungo and Ventina rule out climate as the primary driver of

environmental change prior to 750 AD. Lake Ventina carbonate isotopes suggest

warm/dry conditions from 100 BC to 750 AD, which likely helped facilitate the

management and clearance of forests. Prior to 100 BC, the isotope record from Lake

Ventina is much more variable and generally more depleted. Cool/wet conditions during

the 1st millennium BC may have played a role in creating the mesic forest and Alnus

dominated pollen assemblage in the Lake Lungo record (Mensing et al., 2015), and this is

a period of glacial advance in the Apennines (Giraudi, 2005, Fig. 8). In Lake Ventina,

peaks in Alnus found in the bottom 1500 years of the record do not correspond to periods

with depleted isotopes, suggesting wet periods are not driving increases in Alnus.

Late Bronze Age, Iron Age, and Archaic Periods (1000 BC – 270 BC)

The early presence of a highly anthropogenic landscape surrounding Lake

Ventina beginning during the late Bronze Age (up to 900 BC) and continuing through the

Iron Age and Archaic periods (900 to 270 BC), while unusual, is not unique in the region.

The consistent presence of Cannabis in substantial percentages (>1-2%) has been found

at other sites in central Italy beginning in the Iron Age (Mercuri et al., 2002). Castanea is another taxon closely associated with human impacts. The history of chestnut in Italy is complicated because it is native to the region (Conedera et al., 2004; Krebs et al., 2019), but its pollen increases in records from Italy beginning around 1000 BC, suggesting management of Castanea in forests for wood and food intensified to the point of being 77

detectable in pollen records (Mercuri et al., 2013). Historical sources have generally

stressed the importance of chestnut as a cultivate beginning after the collapse of the

Roman Empire (Squatriti, 2013), but pollen records indicate moderate to high levels of

the pollen beginning ~2000 BC (Mercuri et al., 2002; Di Rita et al., 2018). Thus, the

early presence of Castanea in the Lake Ventina record is not unprecedented, and its

earliest cultivation in the Ventina watershed remains unknown because the record begins

1000 BC and the oldest sample in the record has substantial Castanea.

In the absence of written sources, we must rely on the archaeological record to

detect human impacts on the environment prior to Roman conquest. The Rieti Basin

survey (Coccia et al., 1992; 1995) and Carancini (1990) identified a peak in settlements

during the late Bronze Age located in a 371-380 m band surrounding the Rieti Basin lakes. No such settlements have been identified in the Lake Ventina watershed, probably because the Ventina basin has not been systematically surveyed. The Rieti region was inhabited by Sabini people during Iron Age (beginning about 900 BC), but close to the boundary with Umbrians to the north and east, and Etruscans to the west.

Regionally, the Iron Age (beginning around 900 BC) saw broad intensification in the region, including the increasing importance of hill forts in nearby Umbria, and an

expansion in trade, agriculture, and transhumance (Bradley, 2000). This period also saw

the increasing importance of urban centers in central Italy beginning around 1000 BC

(Stoddart, 2016) and these played an important role in driving the increase in

anthropogenic pollen seen in records from central Italy at this time (Stoddart et al., 2019).

A reconstruction of population based on radiocarbon frequency from archaeological sites

indicates a rapid increase in population in central Italy beginning around 1500 BC and 78

peaking 1000 to 300 BC (Stoddart et al., 2019), and erosion peaks in the Turano basin

(Borrelli et al., 2014) between 1000 and 750 BC. Authors stress the significant

heterogeneity of landscape during this period (Stoddart 2016), which matches pollen

records Some, like those from Lakes Vico (Magri and Sadori, 1999), and Albano and

Nemi (Mercuri et al., 2002), show substantial anthropogenic indicators and OJC (Olea,

Juglans, Castanea) pollen beginning 1000 BC, while many others (including from Lake

Lungo), do not (Stoddart et al., 2019). Overall comparison between records from Lake

Ventina and Lungo during the pre-Roman period support spatial landscape heterogeneity,

but without better local archaeology around Lake Ventina, linking anthropogenic

landscape indicators to specific land-use patterns is challenging.

There is limited archaeological evidence for early Iron Age settlements following the disappearance of basin floor Bronze Age sites by 900 BC (Coccia et al., 1995). This period is associated with a decline in summed probability distribution of radiocarbon dates both from archaeological settings (Stoddart et al., 2019) and limited erosional building of fluvial terraces in the Turano watershed (Borrelli et al., 2014). Nucleated settlements and dispersed rural settlements begin to appear by 700 BC (Coccia et al.,

1995). Identification of a large Archaic village (c. ~500 BC) on a hillside overlooking the

Rieti Basin (Coccia et al., 1992) suggests this period may be characterized by a shift in where land was being occupied and intensively managed rather than abandonment of the landscape. Coccia et al., (1992) conclude that the pattern of land-use associated with the

Roman Period (exploitation of hill slopes between 380 and 500 m asl) was likely in place

prior to Roman conquest in 270 BC. The intensely managed landscape indicated by the 79

Lake Ventina pollen record during this period would strongly support a model occupational and exploitational continuity in some areas from late Bronze Age onward.

Some authors have argued that there is little evidence of forest modification by

Sabini (Cifani, 2003), but this finding is strongly countered by pollen record from Lake

Ventina. The lack of pre-Roman archaeology in the Ventina basin is surprising given the pollen record and may be in part explained by survey methods. Giuseppe et al. (2002) found dramatically increased evidence for pre-Roman settlement in an area controlled by the Sabini during a re-survey near Farfa. The identification of a highly anthropogenic landscape around Lake Ventina in place by 1000 BC indicates sustained human presence and landscape modification in the region and warrants further archaeological examination.

An early anthropogenic landscape around Lake Ventina contrasts with Lake

Lungo. Clear anthropogenic impacts only begin in the Lungo record with Roman conquest of the region in 270 BC, and forest cover with percent tree pollen <20% is not seen until the Medieval period ~900 AD. In the period between 900 and 1400 AD the pollen signals from the two lakes are very similar, having low percentages of forest at both sites, with the notable exception of Castanea, which remains nearly absent in the

Lake Lungo record. Cultivates like Castanea and Cannabis are nearly absent from that record before then, and other anthropogenic indicators like Chicoreae and Plantago are present at very low percentages. Instead, the Lungo record is dominated by Alnus and forest taxa, including mesic taxa such as Fagus, which are only present in low levels at

Lake Ventina. 80

Differences in topography mean that even absent human modification of the

landscape, the Lake Lungo record would be expected to contain greater Alnus and Fagus

pollen than the record from Lake Ventina. Broad wetlands surrounding Lake Lungo

would have meant that people were not living in close proximity to the coring location,

while the limited wetland around Lake Ventina would have supported people living near

the lake’s edge, thus making Lake Ventina a more sensitive recorder of anthropogenic

activity along the lake margins than Lake Lungo. It is also probable that the higher

elevation forests in the Lake Lungo watershed were not as easily exploited by pre-Roman

societies than the lower elevation forests around Lake Ventina. For example, it is unlikely

high elevation forests would have been exploited given the challenges of transporting

wood and timber unless people were living nearby or lower elevation forests were

already intensely managed. Finally, Lake Ventina is closer than Lake Lungo to major

Iron Age trade routes and the city of Interamna Nahars (Bradly, 2000), located near

modern day Terni, about 10 km from Lake Ventina. Thus, greater intensity of land use

around Lake Ventina may have been in part a result of spatial patterns of human

settlement un-related to the local topography of the lakes.

The Roman Imperial period

The Roman Imperial period (roughly 1 AD to 300 AD) at Lake Ventina is characterized by rapid shifts in the pollen assemblage. Samples from before and after this period are characterized by low percentages of most tree pollen and high percentages of

Castanea and Cannabis, suggesting the watershed was being inhabited and managed intensely. During the 2nd and 3rd century AD, pollen samples from Lake Ventina are associated with high riparian vegetation and forest regeneration. Carbonate isotopes from 81

this period do not deviate much from the long-term average, so it is unlikely that changing climate is the primary driver of these shifts in vegetation. The signal from Lake

Ventina is different from that of Lake Lungo, which has forest clearance and a decline in riparian vegetation (mostly Alnus) during this period. Additionally, the Roman Imperial period is associated with a peak in both Sporormiella and Glomus in Lake Ventina, which suggests an elevated presence of animals and increased soil inwash.

It is possible that differences between the way Romans managed the land in the

Rieti region compared to the Sabini, who occupied the region before Roman conquest in

270 BC, can at least in part explain the signal from Lake Ventina and the differences between it and the Lake Lungo record. Archeological investigation in the Rieti Basin has revealed that Roman settlement and field agriculture was concentrated in the band of land between 380 and 480 m asl (Coccia et al., 1992; 1995). GIS analysis of the basin’s topography (Figure 9) indicates that there is a great deal more land flat enough for field agriculture at that elevation, near Lake Lungo than Lake Ventina. Thus, it may be that the topographical setting of the two lakes is largely the reason for their divergent pollen signals during this period.

Archeological study also indicates that the Romans avoided living in the valley bottoms in the Rieti Basin (Coccia et al., 1992). They did however begin the process of draining the basin (Sisani, 2009) and converting wetlands and riparian zones into pasturage, a landscape known as the Rosea. This is reflected in the Lake Lungo record by a reduction in Alnus and increase in herbaceous taxa beginning around 300 BC. This contrasts with Bronze Age settlement, which was largely along the 375m contour and there is no evidence for pre-Roman anthropogenic impacts to wetlands in the Rieti Basin. 82

If Roman conquest drove people out of the region or caused their life-ways to change, it

could explain the increase in Alnus during the Roman Imperial period in Ventina. Less

floodplain habitation could allow Alnus to grow in places it was prevented from doing so or because it was being cut down for timber and wood. The elevated Sporormiella and

Glomus during the Roman people remains somewhat mysterious. It may be that the

Romans displaced the Sabini in the Ventina watershed and began using the hillsides for pasture for sheep rather than for Castanea cultivation. This explanation is plausible in part because Varro, writing in the first century AD, notes that the Rieti region was known for its sheep (Varr. 2.2.9).

Fewer archeological sites were found which date from the 2nd and 3rd century AD

than from periods before and after (Coccia et al., 1992). Little is known about local

occupation and land-use in the Ventina basin because archeologists did not survey

thoroughly in the basin and Roman sources (e.g. Varro and Strabo) are too general to

provide information about sub-regional scale land-use variation. The increase in riparian vegetation during this period may represent reforestation of the lake shore associated with land abandonment. Pre-Roman settlements in the Rieti Basin were mostly found along lake shores (Coccia et al., 1992), so it is logical that abandonment would result in regrowth of riparian communities.

The record of Tiber flooding is characterized by a peak in flooding during the

Roman period that has generally been attributed to a combination of more complete record keeping as compared to the period following and an increase in peak discharge during rain events driven by forest clearances (Aldrete, 2007). Erosion in the Turano basin is elevated but not extreme during the Roman Republican period and reaches a 83

minima during 1st through 3rd centuries AD (Roman Imperial period), suggesting less

intense land-use. This finding matches the pollen record from Lake Ventina and further

supports the interpretation that the Romans were not intensively utilizing hillsides which

would drive both the pollen signal from Lake Ventina and erosion in the Taurano Basin.

The clearance of flat basin land around Lake Lungo, and reclamation efforts to drain the

Rieti Basin, which began in 270 BC (Leggio and Serva, 1991), could have helped to drive

increased flooding of the Tiber without affecting overall erosion rates or intensity of

land-use around Lake Ventina. The way the Romans used the landscape of the Rieti

region appears to have limited their environmental impact in some ways and amplified it

in others. This period in the environmental history of the region serves as an example of

the complexity of landscape change.

Ostrogoth & Lombard Period (Early Medieval: 500 to 750 AD)

The dominant narrative is a substantial decline in population, trade, and

technological innovation following the collapse of the Western Roman Empire, including

in the Rieti Basin where diagnostic wares are minimal beginning in the 5th century AD

and continuing until the 10th century AD (Coccia et al., 1992). However, neither the

pollen record from Lake Ventina or the record from the Turano Basin (Borrelli et al.,

2014), which identifies the period from 300 to 800 AD as one of increased erosion,

support this interpretation. Possible explanations for why the intensity of land us does not

decline in the Rieti region are varied. A breakdown of trade networks, as identified by the

lack of diagnostic pottery during this period (Coccia et al., 1992), may have encouraged

greater intensification of local land-use. This period may be associated with increased erosion in part because of a disruptions of land management tied to political instability 84

and conflict. Economic and political disruption have been identified by Butzer (2005) as a key facilitator of environmental degradation and increased erosion in the

Mediterranean. Biases in the historical (lack of preservation of documents) and archaeological record (shift from stone to wood buildings which are not as well preserved, lack of diagnostic pottery) are likely causing an overestimation of the impact the collapse of the Roman Empire had on the economy and population of the region.

There are substantially fewer Tiber River floods from the 3rd to 12th centuries AD, which has at in part been attributed to poor record keeping (Aldrete, 2007), which again highlights that our perception of this period as a “Dark Age” may in part be a result of biases in preservation of historical documents.

The Lake Lungo pollen record (Mensing et al., 2015) suggests a slow intensification of land-use via forest clearance and a reduction in forest diversity during the 6th-8th centuries. This pattern begins to bring the Lake Lungo pollen signal more in line with the Lake Ventina record as well as the Turano Basin erosion record (Borrelli et al., 2014), which shows increasing intensity of land-use during this period. It suggests a homogeneity in the intensity of landscape use beginning at the end of the Roman period and solidifying by 750 AD that was not characteristic of the region previously.

Carolingian conquest (750 – 800 AD)

The period from 750 to 800 AD in Lake Ventina corresponds to pollen Zone 1b and is characterized by a spike in forest taxa. This period coincides with the conquest of the region by the Carolingians in 774 and a shift in political control and land management from the Duchy of Spoleto and the Lombard Kingdom to the Royal Monastery of Farfa and Rome (Delogu, 1995). This transition resulted in changes in land management and 85

confusion over who owned and controlled much of the land in Rieti, including around

Lake Ventina (Davis, 1992). For example, the position in the government of the Duchy of

Spoleto responsible for managing forests, the archiporcarius, disappears after the

Carolingian conquest. The impacts on vegetation were brief however, and the pollen record suggests that by 800 AD the landscape reverted to a largely cleared landscape similar to the period prior to the change in political control.

Local climatic evidence suggests that a period of cooler and/or wetter climate may have played a part in causing this spike in forest. The carbonate isotope record from Lake

Ventina has a dramatic shift of more depleted values beginning around 750 AD and continuing until about 950 AD, indicating cool/wet conditions. Historical documents record an expansion of lakes in the Rieti Basin and increased flooding during this period

(Leggio 1994, 1998). The timing of this spike in forest occurs during a period of

Apennine glacial advance (Giraudi, 2005) and falls in the latter half of the Dark Ages

Cold Period as determined by environmental proxies (i.e. pollen records) from across

Europe (Helama et al., 2017). However, the forest spike in Lake Ventina is much shorter in duration than the cold/wet climate period suggested by other proxy records, including the isotopic record from Lake Ventina. This suggests the primary driver of landscape change during this period was humans, and that climate played a subsidiary role.

The Lake Lungo record shows a very similar signal during this period, including reforestation primarily by Quercus (deciduous) and Ostrya type. This suggests that impacts of changing political control were regional (or at least extra-local). It also supports the theory that climate may have played a role in helping facilitate reforestation.

That the two sites responded similarly at least means climate cannot be eliminated as a 86

key driver. The only significant difference between records during this period is an offset of the reforestation by about 50 years. This may be an effect of age model error, but a true difference between records can’t be ruled out.

The record of erosion and land clearance (Borrelli et al., 2014) from the Turano

basin closely matches the pollen records from Lakes Lungo and Ventina during this

period, with a sharp decline in erosion at about 750 AD and a return to greater erosion

around 900 AD. This helps to confirm the interpretation that forest regeneration was

being driven by less intense land use. This period is characterized by a small peak in

flood frequency of the Tiber River (Aldrete, 2007), which provides additional evidence of

wetter conditions during this period. This interpretation is strengthened because the

pollen records from Lakes Lungo and Ventina suggest forest regeneration and erosion

reaches a minima (Borrelli et al., 2014), so land clearance is unlikely to be a driver of an

increase in flood frequency.

Medieval Warm Period (~900 – 1250 AD)

From 850 to about 1250 AD the pollen from both lakes indicate open conditions

with low forest cover and the isotopes from Ventina indicated a warmer/drier climate.

This period corresponds closely to the Medieval Warm Period in Europe, which is

associated with warm Northern Hemisphere Temperatures (Wilson et al., 2016) and a

persistently positive NAO (Baker et al., 2015), which causes dry conditions in southern

Europe. Warm/dry climate is conducive to reduced forest growth in central Italy

(Piovesan and Schirone, 2000), and the fact that both pollen records indicate open

landscapes with reduced forest cover suggests climate may have played an important role

in driving forest change during this period. 87

However, several lines of evidence contradict interpretation. First, the timing of forest decline is not consistent with the climate record (Fig. 8). Open conditions developed around Lake Lungo and returned to the Lake Ventina watershed between 800 and 900 AD, during which the isotope record suggests cool/wet conditions persisted.

Second, the landscape around Lake Ventina during this period appears nearly identical to the lengthy period from 1000 BC to 750 AD, when climate wasn’t persistently warm/dry.

Third, there are strong historical reasons unrelated to climate that people began to clear the hillsides and create an open landscape. These include incastellamento, as a response to increased political instability and invasion (Coccia et al., 1992) and the reestablishment of control by political elites capable of organizing labor effectively (Leggio, 1989;

Hodges, 2012), which would have included having people more intensively managing or clearing forests. A shift to high elevation farming utilizing terracing of the hillsides between 700 and 1000 m (Coccia et al., 1992), which would have required the clearing of forest, was likely driven by shifts in population to fortified hill tows, but may have been facilitated by warmer/drier climate after 950 AD. A shift to greater exploitation of hillsides had the effect of substantially increasing erosion in the region. The period from

1000 to 1350 AD contains the highest erosion rates in the Turano basin (Borrelli et al.,

2014). This peak was likely driven by a combination of political instability, population growth, and a focus on exploiting the portions of the landscape most susceptible to erosion. In short, 3 key factors identified by Butzer (2005) as important drivers of erosion and environmental degradation in the Mediterranean. Overall the pollen and isotope records from Lake Ventina support the interpretation of Mensing et al. (2015; 2016; 88

2018) that the initial loss of forest cover and opening of the landscape during the during

early Medieval time was not primarily driven by climate.

Post-1400 afforestation

The most radical change in the pollen record from Lake Ventina occurred around

1450 AD, between Zone 1C and Zone 2 (Figs. 2 and 5). This shift represents a transition to a more forested landscape which has persisted until today, and was likely driven by two events. The first was the major outbreak of plague in 1348, the Black Death, which caused dramatic population loss and likely had a profound impact on the intensity with which the landscape was managed. By 1450 AD plague had reduced Italy’s population by

60% (Lo Cascio and Malanima, 2005), and the resulting loss of labor had caused the price of bread to double in Tuscany (Tognetti, 1995). Records from across the continent indicate that forests expanded as a response to land abandonment driven by the dramatic reduction in population (Yeloff and van Geel, 2007; Rull and Vegas-Vilarrúbia, 2015).

This shift also coincided with a period when the Rieti region was on the frontier between

the Kingdom of Naples and the Papal States, and political instability may have played a

role in reducing human impacts on the landscape and driving forest regeneration

(Schoolman et al., 2018). The combination of political instability and plague-related

mortality has been directly linked to reduced tree felling in Germany during this period

(Ljungqvist et al., 2018) and it is likely a similar process occurred in the Rieti region.

The second cause of forest increase during this period was a shift in climate, from

warm/dry during the Medieval Climate Anomaly to Cool/Wet conditions during the Little

Ice Age. This shift has been recorded in proxies from across Europe (Martín-Chivelet et

al., 2011; Luterbacher et al., 2016; Baker et al., 2015). Dendroclimatology has revealed 89

substantial temporal and spatial variation in temperature (Anchukaitis et al., 2017) and

PDSI (Cook et al., 2015; 2016) across Europe during this period, but central Italy lacks

long-lived trees sensitive to climate, and does not have any chronologies which

contribute to these studies. In central Italy, this period is associated with glacial advance

18 in the Apennines (Giraudi, 2005). Locally, the δ Ocarbonate from both Lake Ventina

(Chapter 1) and Lake Lungo (Archer, 2017) show a shift to more depleted isotopes beginning around 1250 AD, indicating cooler/wetter conditions. Carbonate isotopes become progressively more depleted over the following three centuries, and reach their most depleted from 1500 to 1600 AD. The frequency of Tiber River floods also increases substantially beginning in the 14th century. This is likely in part a result of better record keeping, but climate probably also played a role (Aldrete, 2007).

The shift to cooler/wetter conditions identified in the carbonate isotope record from Lake Ventina begins before the shift to increased forest cover, which begins at 1400

AD and peaks at 1540-1610 AD. This lag is expected if climate was a major driver because it takes time for forest to expand. Even if climate began to cool starting at 1250

AD, it was not until after the plague in 1349 AD that forest regeneration began, suggesting the important role of demographic change and reduced population pressure on land use. Overall, it appears that the shift to increased forest cover after 1400 AD was likely driven in part by both cooler/wetter climate and reduced intensity of land management due to plague mortality.

The Lake Ventina pollen record remains dominated by forest taxa even after population levels rebounded (Lo Cascio and Malanima, 2005) and the isotopes suggest a return to more neutral climate conditions. In contrast, after 1650 AD the Lungo record 90

shows declines in forest (Fig. 7). Intensified land management around Lake Lungo

included fully draining the Rieti Basin floor for large-scale field agriculture (Lorenzetti,

1989; Leggio and Serva, 1991). With an increase in reclaimed land brought under cultivation and more efficient farming methods, the need to intensely manage hillsides declined. The Lake Ventina watershed is dominated by sloped hills that are not useful for modern field agriculture, thus, the emphasis since ~1700 AD on exploiting flat areas that can be easily irrigated and plowed using modern machinery likely contributed to maintenance of forest in the Lake Ventina watershed. This contrasts with the Middle

Ages, when agro-pastoralism, which intensively utilized upland areas, was the dominant form of land management (Coccia et al., 1995).

6. Conclusion

The dominant trend in the Lake Ventina pollen record is a shift to greater forest cover at 1450, with the nearly one and a half millennia prior dominated by open, highly managed anthropogenic landscape. Periods of political and economic disruption from 100 to 300 AD and 750 to 800 AD impacted this landscape only briefly. The presence of a highly anthropogenic landscape in place at 1000 BC is unusual but not unique in central

Italy. The similarities between the Iron Age and high medieval landscape around Ventina are remarkable and given the intensity with which landscape was exploited during medieval times, suggests substantial human management during the pre-Roman period.

The differences between the Lake Ventina and Lake Lungo records indicate there was substantial spatial heterogeneity in human exploitation and impacts on the landscape, particularly prior to the 8th century AD. This research suggests that site selection is key, 91

particularly when studying impacts Bronze and Iron Age societies had on the environment, and that multiple sites in the same region can provide different but complementary records of environmental change.

Utilizing a record of climate from Lake Ventina and the pollen records from both

Lakes Lungo and Ventina allows for a more thorough evaluation of human and climatic impacts than just comparing one pollen record to regional climate reconstructions and local history. This analysis found that humans were primarily responsible for creating and maintaining the landscape around Lake Ventina prior to 1450 AD. Climate may have played a role during the brief spike in forest from 750 to 800 AD, but it is unlikely it was the primary driver. The shift to increased forest conditions at 1450 was likely driven by a combination of climate and demographic change and maintained though improvements in technology. 92

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8. Figures

Figure 1: Constrained cluster analysis of the Lake Ventina pollen data. 99

hand hand - . Primary taxa included in each pollen category (left category pollen each in included taxa Primary . summary diagram summary 3 and 4 . : Lake Ventina pollen Ventinaspores : Lake and Figure 2 can in 4 columns)beFigures found 100

Figure 3: Common tree and riparian taxa in the Lake Ventina pollen record. Percentages for all taxa in figures 3 & 4 are calculated with Alnus excluded from the pollen sum.

101

: Common shrub, vine, and herbaceous vine,inLakepollenrecord. taxa Ventina shrub, the : and Common Figure 4 102

Figure 5: NMDS ordination using Brey-Curtis Similarity Index of Lake Ventina pollen samples. Total stress = 0.14. R2 of Axis 1: 0.79; R2 of Axis 2: 0.07. Numbers associated with each sample are the date (BC/AD) rounded to the nearest decade. Red dates indicate samples which date to the Roman republican and early/middle Imperial periods. Background circles correspond to cluster analysis zonation: light yellow is Zones 1a and 1c, blue is Zone 1b, and green is Zone 2. Dashed green box contains riparian dominated samples from Zone 1a.

103

Figure 6: Alnus percentage vs stratigraphy in samples between 100 BC and 300 AD.

104

: Pollen comparison between Lake Ventina (left) and lake Lungo (right). Lungo lake and (left) Ventina Lake between comparison : Pollen Figure 7 105

Figure 8: Proxy comparison. Tree pollen percent from Lake Lungo (green line; Mensing et al., 2015) and Lake Ventina (orange dashed line), excluding riparian taxa (Alnus) and cultivates (Olea, Castanea, Juglans). Carbonate isotope (δ18O) record from Lake Ventina (blue line), periods of central Apennine glacial advance (blue bars; Giraudi, 2005), cumulative probability of 36 radiocarbon dates from fluvial terraces as a proxy of erosion (grey curve; Borretti et al., 2014), and Tiber River floods per century in the historical record (black bars; Aldrete, 2007).

106

Figure 9: Areas suitable for Roman agriculture. Yellow areas fall between 380 and 480 m asl and have a slope <15%.

107

9. Tables

Table 1: list of scientific and common names for common taxa in the Lake Ventina pollen record.

Scientific Name Common Name Quercus oak Quercus ilex holm oak Castanea chestnut Ostrya hop-hornbeam Carpinus betulus hornbeam Corylus hazel Olea olive

Juglans walnut

Fagus beech

Fraxinus ash Alnus alder Salix willow Juniperus juniper Poaceae grass Cannabis hemp Cyperaceae sedge Urtica nettle Chicoreae chicory Plantego plantain Vitis vinifera grape

108

Table 2: Correlation coefficients between the 12 most common taxa plus indeterminate grains in the Lake Ventina record. Positive correlations have green backgrounds, negative correlations have red backgrounds. Darker colors indicate stronger correlations.

Quercus deciduous Poaceae -0.1 Indeterminate -0.6 0.1 Castenea -0.6 0.01 0.43 Alnus -0.4 -0.3 -0.1 0.05 Ostrya type 0.67 -0.3 -0.6 -0.6 -0.2 Cannabis 0.33 0.06 -0.1 -0.3 -0.3 -0 Ferns -0.6 0.02 0.74 0.46 -0.1 -0.5 -0.2 Chicoreae -0.5 0.02 0.65 0.3 -0.1 -0.4 -0.1 0.75 Cyperaceae 0.16 0.22 0.06 -0.2 -0.3 -0 0.15 0.11 0.22 Salix 0.08 -0.2 -0.3 -0.2 0.17 0.27 -0.1 -0.3 -0.3 -0.2 Juniperus 0.76 -0 -0.6 -0.7 -0.3 0.68 0.31 -0.6 -0.5 0.24 0.18 - Urtica -0.4 0.1 0.29 0.21 -0 -0.4 -0.1 0.24 0.21 -0.1 -0 0.4

type

deciduous

Salix Ferns Alnus Poaceae Cannabis Castenea Juniperus Chicoreae Cyperaceae Ostrya Indeterminate

Quercus 109

Chapter 3: Pollen-vegetation relationships and modern analogs from central Italy

Abstract

Understanding the relationship between land cover and pollen assemblages allows for more accurate interpretation of fossil pollen records and is an important aspect of palynology. However, a thorough examination of this relationship has not been attempted for most of Italy, a region that has numerous important fossil pollen records. This study utilizes modern pollen samples collected from moss pollsters and soil samples at 32 locations in central Italy to address this gap in our knowledge. These samples are compared with a presence-absence vegetation survey at each location and regional maps

of land cover to examine pollen-vegetation relationships at multiple spatial scales.

Specific goals of this research are to better understand the relationship between forest cover and tree pollen, aide in our ability to interpret anthropogenic taxa in fossil records, and identify modern analogs for landscapes of the past. Results indicate that while pollen rain effectively captures broad differences in landscape between sites, local-scale variation in the amount of forest cover is difficult to detect, particularly in patchy environments. The consistent underrepresentation of cultivates is a recurring issue and highlights the challenges in detecting agriculture in fossil pollen records. There do not appear to be many modern analogs for pollen assemblages found the Lake Ventina record, driven in part by a lack of riparian vegetation in the modern land cover of central

Italy. The results of this study expand our understanding of pollen-vegetation relationships and improves the ability of palynologists working in the region to better analyze pollen records and reconstruct landscapes of the past. 110

1. Introduction

Analysis of modern pollen rain by measuring the relationship between land cover

and pollen assemblages to calibrate interpretation of fossil pollen records is an important

aspect of palynology (Overpeck et al., 1985). Differing pollen production and transport characteristics between taxa (Soepboer et al., 2007)), the impact of landscape structure

(patchy vs homogenous)(Sugita, 1994; Hellman et al., 2009), and the contribution of both

local and regional pollen (Sugita, 2007) make understanding vegetation-pollen

relationships challenging but important for interpreting past landscapes from pollen

records.

Much of the modern pollen research to date is from temperate forested regions

such as eastern North America or north-western and central Europe (e.g. Broström et al.,

1998; Soepboaer et al., 2007; Lisitsyna et al., 2012; Bunting et al., 2016). Studies take a variety of approaches and focus on different aspects of pollen-landcover relationships, including using modern samples as analogs to compare with fossil samples (e.g. Gaillard et al, 1994; Nielsen and Odgaard, 2004), studies that aim to quantify impacts of uniquely anthropogenic landscapes on pollen assemblages (e.g. Waller et al., 2012; Bunting et al.,

2016a, Bunting et al., 2016b), and studies focused on developing pollen productivity estimates for specific taxa (e.g. Soepboer et al., 2007; Broström et al., 2008). Modern pollen studies from southern Europe are more limited, including central Spain (Lopez-

Saez et al., 2010, Broothaerts et al., 2018), Greece (Glais et al., 2016), and Turkey

(Vermoere et al., 2003). There are no comparable studies from Italy, a region with many

important fossil records published in the last several years (e.g. Mercuri et al., 2012;

Mensing et al., 2015; Sadori et al., 2016; Di Rita et al., 2019; Stoddart et al., 2019). 111

Pollen records from Italy which focus on the last 2-3 thousand years are particularly

important for assessing the role human history has played in influencing landscape

change. The Italian peninsula’s mix of Mediterranean and temperate deciduous forests and highly anthropogenic landscape makes quantifying landcover-pollen relationships

challenging but important for understanding how humans have shaped the environment.

This study examines pollen-vegetation relationships in central Italy through

modern pollen samples combined with local-scale vegetation survey data and regional

land-cover maps. There are three primary goals. First, to look for modern analogs for

pollen assemblages found in fossil pollen records. This is a well-established approach in

palynology (Nielsen and Odgaard, 2004) but requires a broad sampling of modern

environments to have sufficient data for statistical comparison. Identifying locations that

serve as modern analogs can be challenging in a region that has seen radical shifts in land

cover in the last 100-200 years. The past two centuries have seen a transformation of the

landscape of Italy as modern technology has dramatically expanded our ability to re-

make the landscape and modern agricultural practices have shifted how and where land is

intensively managed. As a result, areas that might serve as analogs for past environments

may be limited and require substantial investigation to identify. This is particularly true

of riparian environments, which are important for the ecology of the region and tend to be

important in fossil pollen records from lakes/wetlands, but have declined precipitously in

the modern period with draining of wetlands for agriculture and flood control. Identifying

riparian analogs is one goal of this study.

A second goal of this research is to begin to quantify the relationship between

individual taxa on the landscape and their pollen in assemblages. This can ultimately lead 112

to pollen productivity estimates (PPE) being developed for taxa in a region, an approach which has gained widespread application in northern/central Europe (Soepboer et al.,

2007; Broström et al., 2008), but has been slow to develop in southern Europe. This study focuses on a less rigidly quantitative approach to measuring relative representation of taxa in the pollen record by comparing pollen taxa to local presence of plants. This will help in interpreting fossil pollen records by determining which specific taxa tend to be over/under-represented in pollen samples.

Third, this study seeks to quantify relationships between forest cover and forest pollen. Clearance of forests is one of the most common anthropogenic impacts in the past and understanding the relationship between forest cover and percent forest pollen can help reconstruct the magnitude of these changes.

Finally, this study seeks to better understand the impact specific land management and agricultural practices have had on pollen assemblages. Forest management practices such as coppicing are an important part of traditional forestry in central Italy and have been in place since at least the middle ages and understanding how such practices impact the pollen signature of forests can help us detect changing forest management strategies in the fossil records. Similarly, measuring the pollen signal of pastures and agricultural fields and orchards may help us better reconstruct periods of past agricultural activity.

2. Study area

Central Italy lies in a transition zone between Mediterranean and temperate climate zones and is characterized by hot dry summers but with more precipitation than in much of the Mediterranean basin. Most of central Italy gets >750 mm of precipitation 113

annually while much of the Iberian peninsula, north Africa, and the eastern

Mediterranean receive < 500 mm (citation). The Apennine Mountains run though the

center of the peninsula and rise to above 2000 m. The landscape of central Italy,

including in and around the Rieti Basin, is highly anthropogenic. Field agriculture

dominates in flat, low laying areas. Gentle slopes are often dominated by olive, fruit, and

nut orchards. Hills are mostly forested with some patches of pasture. Forests are often

highly managed for wood through coppicing. At higher elevations (>1000 m) there are

more substantial open meadows used for grazing. Floodplain areas are limited, and

riparian zones are narrow or nonexistent along many rivers, a legacy of hundreds of years

of infrastructure building aimed at controlling floods, opening up land for agriculture, and

expanding the amount of irrigated land. As a result of human impacts, relatively

unmodified vegetation communities are limited. In general, higher elevation forests are

dominated by Fagus with some Abies and Pinus spp. which was mostly planted during

the 20th century in an attempt to create a timber industry in the region (citation). Mid- elevation forests tend to be dominated by deciduous oaks (Quercus cerris, Q. pubescens - robur) and Ostrya spp. Lower elevation and less well watered hillsides tend to be dominated by holm oak (Q. ilex). Riparian communities contain Alnus, Fraxinus, and

Salix.

3. Methods

Pollen analysis

Samples were taken from the major vegetation communities of the Rieti Basin

and the surrounding hills. The sampling strategy was intended to capture different 114

vegetation communities and agricultural settings rather than sample along a transect or across a range of environmental variables. We also attempted to take adjacent samples to examine local scale variation within similar vegetation communities, across different topographical settings, and between paired coppiced and un-coppiced forests. Sampling was conducted during June and July of three consecutive years (2013-2015). The primary methodology of collection was sampling from moss polsters. Moss polsters serve as recorders of the pollen rain (Räsänen et al., 2004; Pardoe et al., 2010; Lisitsyna et al.,

2012; Bunting et al., 2013), and estimates suggest that they represent pollen deposition of one or two years (Räsänen et al., 2004). Sampling after the end of the flowering season

(March-May) ensures that our moss polsters are providing an accurate and consistent representation of a location’s pollen signal.

We were primarily interested in comparing the pollen signal of different vegetation types, so we sampled from within the middle rather than from the edge of patches. At each sampling location we picked a center point and took 5-10 moss samples each roughly 2 cc in volume from within an approximate 10 m radius of this center point but at least 2 m apart. These samples were aggregated to form a single sample prior to chemical processing and analysis. The purpose of this sampling technique was to create a pollen signal from a single patch of vegetation while also averaging individual moss samples to help smooth out micro scale differences in pollen composition (Gaillard et al.,

1994; Räsänen et al., 2004).

Moss polsters were dried at 100° C for a minimum of 2 hours, ground with a mortar and pestle, and then processed for pollen using standard acid digestion processing techniques (Faegri et al., 1989). Processed material was mounted in silicon oil and 115

counted using a light microscope at 400x magnification. Samples where the most

common taxa was less than 40% of the total sum were counted to a minimum of 400

grains, and samples with a single taxa greater than 40% were counted to a minimum of

600 grains. Pollen identification was based on keys (Kapp, 2000, Chester and Raine,

2001), reference books (Beug, 2004), and reference slides maintained at the UNR

palynology laboratory.

Land-cover quantification

Pollen sampling was accompanied by a complete list of plant species found in that

vegetation patch. The goal of the vegetation survey was to provide a list of nearby plants

to compare with the pollen rain at each site. These plant lists were used to create a list of

potential local pollen producers for each sample and species were aggregated to the

genus/family levels for plants whose pollen is difficult or impossible to differentiate at the species level.

To compare tree pollen to forest cover, percent forest cover was calculated from the Corine Land Cover raster dataset (EEA, 2005). Corine is a 100 m raster dataset with

44 categories of land cover at 100 m resolution generated through remote-sensing

analysis of satellite imagery. For this study were are primarily interested in forest cover

rather than specific taxa, so we converted the categories of land cover into three types:

forested, semi-forested or woodland, and open. This process was accomplished through

qualitative comparison of Corine data with satellite imagery in ArcGIS. Land cover

categories in central Italy which contained greater than 75% forest cover were considered

forested, land cover categories which contained between 25 and 75% forest cover were 116

considered semi-forested, and land cover categories which contained less than 25% forest

cover were considered open.

Statistical analysis

In order to determine what plant taxa are likely over and under-represented in pollen samples we created a fidelity/dispersability scatter-plot of key taxa (following the methodology of Nascimento et al., 2015). A taxon’s fidelity is defined as: when that taxon is present in the vegetation survey, the percent of time it is also found in the pollen sample from the same location. A taxon’s dispersability is defined as: when that taxon is not present in the vegetation survey, the percentage of time it is found in the pollen sample.

Two forms of multivariate statistical analysis were performed to examine relationships between pollen sample assemblages. Cluster analysis was used to identify groupings and major statistical breaks between pollen samples. Two ordination methods,

Principle component analysis (PCA) and non-metric multidimensional scaling (NMDS) using Bray-Curtis distances were used to provide insight into relationships between modern pollen assemblages and to compare modern pollen to the fossil pollen record from Lake Ventina (Chapter 2)(Nascimento et al., 2015; Rodrigues et al., 2016 for PCA,

Broothaerts et al., 2018, Mensing et al., 2018 for NMDS). Both cluster and ordination

(PCA/NMDS) were performed using Past (Hammer et al., 2001). The decision of which ordination approach to present was based on qualitative assessment of which method best captured variation in the data. Analysis was performed on pollen percentages excluding rare taxa, defined as those taxa contributing <1% to the total pollen sum of all modern and fossil samples, excluded. 117

To compare pollen samples with nearby forest, cover zonal statistics were performed in ArcGIS. A 3 km buffer around each pollen modern sampling location was created, and the percentage of forest within those buffers was calculated based on Corine- derived forest cover (see above). Areas classified as open were considered 0% forested, semi-forested/woodland areas were considered 50% forest, and forested areas were considered 100% forest. The percentage of forest cover nearby to each pollen sampling location was then compared with the percentage of forest taxa in that site’s pollen sample using x-y plots. Categories of sites (forested, semi-forested woodland, and open) were analyzed separately to assess how different categories of site reflect surrounding forest cover.

4. Results

Thirty modern pollen samples were collected and analyzed from around central

Italy (Table 1, Figures 1 and 2). Most samples were taken from the Rieti Basin or the surrounding Apennine foothills. Four samples (sites 1, 2, 3, 14) were taken from a regional park closer to the Tyrrhenian coast called [Barbarano? I don’t know what the proper name of this place is] which is characterized by significant riparian land cover which was absent from Rieti. Each sample was paired with a presence-absence survey of local vegetation at the site (Table 2). Sampling locations range from 215 to 1240 m elevation and include a mixture of obviously anthropogenic locations such as orchards and fields (e.g. sites 4, 7, 14), sites that are being managed less intensively such as fields used for grazing and forests under coppice (e.g. sites 8, 19), and forests not being actively managed (e.g. sites 1, 3). Samples have been categorized by land-cover type. Twelve samples were taken from open environments, which are defined as sites without trees 118

within ~50m of the sampling location. Four samples are from semi-open sites, which are

defined as sites with patchy tree cover (e.g. olive and chestnut grove sites #14 and #9).

Fourteen samples were taken from forested sites, which are defined as sites with

complete or nearly complete forest cover. Of these, three samples, 1, 3, and 17 were

taken from areas dominated by riparian vegetation, and eleven were non-riparian.

Structure of the pollen dataset

A cluster analysis of the 30 modern pollen samples reveals the data’s structure

(Figure 3). Two of the three riparian-dominated samples (1 and 3) plot as dissimilar from

all others in the dataset, highlighting the lack of contribution of riparian habitat to the

regional pollen rain. The sample taken from an olive orchard (14) is the most dissimilar

sample in the dataset, reflecting the fact that Olea pollen makes up ~65% of the sample

but is not one of the primary taxa in the dataset as a whole. Sample 9, taken from a

chestnut (Castanea sativa) grove is also an outlier. This sample, along with the two

riparian samples dominated by Alnus (1 and 3), and the olive grove sample (14) represent

the four most dissimilar samples and are all characterized by very high pollen

percentages of an individual tree taxa pollen. These taxa (Olea, Alnus, Castanea), while

they dominate the signal of samples taken in close proximity to the trees, are not amongst

the most common taxa in the dataset overall, so samples not in the immediate vicinity of

the plants record only trace amounts of the pollen. For example, sample 12 was taken less

than 1 km from the Castanea dominated sample yet contains no Castanea pollen.

Another feature of the data is that the two pairs of coppiced/uncoppiced sites (8 and 10,

25 and 26) represent the two most closely related pairs. These sites represented 119

approximately 20 year coppices and suggest that long-term coppicing may not have a significant impact on the pollen signal from a patch of forest.

All but one of the open sites cluster together, despite some substantial variation in local and regional site situation. Within the cluster of open sites, variation between samples appears not to be related to the proximity of sampling location. Sample 23, located in the center of the Rieti Basin surrounded by agricultural fields, is more closely related to mid-elevation meadows than it is to other nearby samples taken from agricultural fields (7, 5, 4). Six samples were taken from different parts of a ~10 km wide meadow (samples 6, 18, 19, 20, 21, 22,) but do not all plot next to each other within the open site cluster.

NMDS ordination (Figure 4) performed on a dataset with 35 taxa reveals similar patterns to the cluster analysis. Coordinate 1, which accounts for 44% of the variance in the dataset corresponds to open (right) vs forested (left). As a result most tree taxa plot to the left of the graph and most herbaceous taxa plot to the right. This matches the separation of sites into open (right) and forested (left). Juniperus, which is primarily a shrub in these mid-elevation environments in central Italy, is one of only two non- herbaceous taxa to plot to the right. This is likely because Juniperus is a pioneer species that invades open meadows that are not being intensively managed (grazed). The other is

Pinus, which is not amongst the local vegetation of most of the sampling locations but makes up a significant portion of the regional pollen rain due to very high pollen productivity and the ability to disperse over long distances. Several taxa have been aggregated into higher-order groups than initially identified in the pollen in order to simplify the data and because the taxa have similar ecologies. Deciduous Quercus is 120

primarily Q. cerris and Q. robur. Ferns are primarily monolete in the Aspleniaceae

family.

Figure 4 highlights some of the same features that are seen in the cluster analysis

(Figure 3) and reveals additional patterns. Two of the three riparian samples (3, 17, grey

boxes in Figure 4) plot far away from other samples suggesting those samples have

substantial differences in pollen composition from the rest of the dataset. Sample 14 (red

box in Figure 4), which was taken from an olive orchard and was identified as the most

dissimilar sample in the cluster analysis, plots within the range of other samples in the

ordination but is not close in ordination space to any other sample. The two pairs of

coppiced/uncoppiced sites (Samples 25 and 26, 8 and 10) are connected to each other

with dashed lines in Figure 4. In each pair, both sites plot in the same quadrant but are not

the closest sample to each other, indicating there are some significant differences in the

sample composition.

Composition of the pollen dataset

A list of the twenty most pollen taxa found in the dataset is presented in Table 3.

It shows that Ostrya type, Quercus deciduous, and Poaceae make up the greatest

proportion of the pollen rain across the dataset. There is a substantial drop off for Q. ilex

at #4 and a further drop off for Pinus at #5. Plantago (3.3%) and Chicoreae (2.5%) are

the only herbaceous taxa other than Poaceae to make up more than 1.2% of the total sum.

The dataset contains very low percentages of deciduous forest taxa such as Betula

(0.01%) and Carpinus (0.4%), which are not among the twenty most common taxa in the modern pollen. These taxa are uncommon primarily because central Italy is near the southern end of their habitat range and in this region only grow in the most mesic sites. 121

Most taxa have mean values substantially higher than their median, suggesting

very high values in a limited number of samples. The most obvious exception is Pinus,

which is a result of long-distance dispersal and is generally absent from sampling sites.

Amongst the most common taxa, Ostrya type has the most even distribution across all samples. Another feature of the data is that many grains associated with agriculture are entirely absent even though the plants are relatively widespread. Pollen from cereals, which make up the most common field crop in the region, represent only 0.8% of the total pollen sum.

A fidelity and dispersability plot (Figure 5) helps illustrate which taxa are likely

to be under or over-represented in pollen percentage diagrams compared to their presence

on the landscape. Taxa broadly fit into 3 clusters. Cluster #1 consists of local producers

and “Silent Taxa”. If taxa in this category are found in a pollen sample the plants must be

growing close by, but simply growing nearby does not necessarily result in their pollen

appearing in a sample. Cluster #2 consists of semi-local producers. If taxa in this category

show up in significant amounts in a pollen sample the plant is likely growing nearby, but

taxa in this category may also appear in smaller percentages if growing regionally.

Cluster #3 contains regional producers. These are the taxa which make up the regional

pollen rain and appear in significant numbers even if the plants are not growing

immediately adjacent to a sampling location. Most major forest taxa are regional

producers, while many important meadow taxa, including Gallium are in group 1. The

most common herbaceous taxa in the pollen data is Poaceae, which is a large family that

has pollen most of which cannot be differentiated to the genus or species level. Grass

species can inhabit a wide range of ecological niches, and thus it cannot be linked 122

explicitly to meadows/open environments in the same way many other herbaceous taxa can.

Forest land cover vs forest pollen

Correlations between forest cover near each sampling location and tree taxa

(Table 4a) help quantify how well pollen samples capture the openness of the landscape.

For example, we would expect a pollen sample taken from a site with 50% forest cover within 1 km to have lower forest pollen percentage than a sample taken from a site with

100% forest cover within 1 km. How closely the actual data matches this assumption across a wide range of forest cover percentages helps us evaluate how accurately pollen samples reflect landscape. The correlation between forest pollen percentage in a sample and percent forest cover within 500 m of the sampling site is 0.75, but declines to 0.71 for forest cover within 1 km and 0.6 for forest cover within 3 km. This suggests that in modern pollen samples, the local site openness is the primary control on forest pollen percent. As the area analyzed around a sampling location is expanded, it captures patches of vegetation that do not contribute significantly to the pollen, and thus correlation decreases. This highlights the difficulty of using pollen from a single site to characterize forest cover in a patchy landscape.

Comparison between the average local forest cover and average tree pollen percentages separated by site category (Table 4b) allow us to examine trends across different sampling environments. The average forest cover within 3 kilometers of sampling sites is 58.6%, which closely matches the overall forest pollen in the modern pollen dataset (60.6%), suggesting that pollen samples are doing a reasonable job of capturing overall forest cover in the region. The percentage of forest pollen in samples 123

from open sites is less than the percentage of tree cover within a 3 km radius. At 0.5 km and 1 km the opposite is true. The correlation between nearby forest cover and forest pollen from open sites are much worse than those from forests sites. The overall correlation in the dataset is much higher than the correlations when separated by site category. A scatter plot of forest within 3 km vs tree pollen (Figure 6) visualizes that open sites have a much weaker correlation (0.28) than forested sites (0.63). This likely reflects that forest taxa contribute significantly to the pollen assemblages of open sites but that meadow taxa do not contribute significantly to the pollen assemblages from forested sites.

5. Discussion

Forest cover vs forest pollen from open sites

One of the key goals of this research is to assess at what spatial scales open sites

are reflecting the surrounding vegetation, particularly forest. The clustering of nearly all

open sites in Figures 3 and 4 suggests that they are receiving similar contribution from

the region pollen rain. Open sites correlate poorly with local forest cover (Figure 6), which is also indicative of a strong regional pollen signal. Given not all open sites have the same tree taxa growing around them, it suggests that the regional pollen rain is having a strong averaging effect. The two samples with the lowest forest pollen percentage, 7 and 23, are the two samples taken from the center of the Rieti Basin, and have very little forested area within 5-8 kilometers. Those two samples do not plot significantly differently in ordination space compared to other open site samples (Figure 4), likely because their herbaceous pollen assemblage is very similar to other open sites. 124

Overall, the finding that very open sites have the least forest pollen suggests that a complete forest clearance from a large portion of the landscape is likely to be reflected in the pollen record. The poor correlations between forest cover and forest pollen in more patchy landscapes suggests detecting more subtle changes in forest cover in the past may be difficult. Difficulties detecting moderate changes in the percentage of forest cover in a patchy landscape may be a result of several factors. First is the tendency of trees to produce more pollen and for that pollen to be more widely dispersed when growing along edges of patchy forest or woodland (Bunting, 2002; Bunting et al., 2013). Second, calculation of forest cover in patchy landscapes using the Corine land cover database has limitations because of its 100m resolution. In landscapes with small patches of forest the database may not be accurately capturing overall forest cover.

Categorizing vegetation zones using modern pollen

It is difficult to differentiate the pollen signal of different vegetation zones in our dataset. Often modern pollen studies set out to categorize pollen from different plant assemblages (e.g. Glais et al., 2016; Broothaerts et al., 2018). This often results in modern pollen datasets which consist of many sample clusters based on these ecological classifications. This study forwent that sampling approach in favor of one based on forested vs non-forested sampling locations and largely avoided sampling specific plant communities. The resulting dataset does not show any clear clustering pattern beyond open vs closed canopy sites. Even samples taken from within a kilometer of each other do not always plot similarly as compared to the dataset as a whole (e.g. samples 8, 10, 12,

24). Despite sampling a wide variety of vegetation zones, we did not see further structure.

This suggests two things; first, there may not be as clear differentiation between 125

vegetation zones in central Italy as compared to other regions in Europe. This may be in part a legacy of long-term human management and modification of the landscape.

Second, it suggests that modern pollen studies that base sampling on zones may overestimate the importance of vegetation communities in the overall pollen-vegetation relationship and structure of vegetation in a region. By not sampling transition areas or small-scale patches of vegetation they may create a modern pollen dataset which does not have an analog in the fossil record, and thus may limit the utility of such a study for interpreting fossil records.

Challenges in detecting specific human impacts

One of the key goals of many fossil pollen studies from Italy is to evaluate human impacts on the landscape, including forest management for fuel and timber, clearing of forests for pasturage and agriculture, planting and management of cultivates, and the clearing of wetlands and riparian areas for flood control and agriculture. This modern pollen dataset can help better quantify what pollen signal might be associated with these sorts of events.

We were unable to detect a clear pattern in the pollen signal from coppiced and uncoppiced woodland (Figure 4), suggesting it may be difficult to detect changing forest management techniques unless they resulted in either a shift in forest species composition or substantial clearance/forestation. Difficulty in detecting the pollen signature of cultivates was also a major feature of this dataset. In spite of a large percentage of the land in the region being dedicated to agriculture, pollen from key cultivates is limited.

Even tree species such as Olea and Castanea, which have high values in the samples where the plants are nearby, comprise a small percentage in most pollen samples (median 126

values of 1.73% and 0.25%, respectively). None-the-less, these tree species may represent the best chance to detect agriculture in the past because may other cultivates are severely under-represented in pollen samples (Mercuri et al., 2013). Cereals are present in the modern pollen data, but do not contribute at a rate representative of the plant’s land cover. This is particularly true of wheat and corn (Zea mays), which are important field crops in the region today, but are absent from nearly all samples. Zea mays is absent from

all samples, except #4 which was taken from an active corn field, in spite of the fact that

it is one of the dominant field crops grown in the Rieti Basin today. Fabaceae, which

includes both important meadow taxa as well as legumes, shows low

fidelity/dispersability. Many other agricultural taxa, including fruit trees in the Prunus

family, and Vits vinifera are nearly or entirely absent from the pollen record. Finally,

meadows used for grazing livestock appear likely to be substantially under-represented in

a fossil pollen record from a lake or wetland because most meadow taxa are not

regionally dispersed.

Given these limitations, what aspects of human-driven landcover change does this

study suggest we are able to detect? First, important riparian taxa such as Alnus and Salix

score high in fidelity/disperability, and riparian samples (samples 1, 3, and 17) stand out

as very different in either the cluster analysis (Figure 3) or ordination (Figure 4). This

suggests that changes in riparian communities in or around a lake, which are often

athropogenic over the last 2500 years (e.g. in the Rieti Basin [Mensing et al., 2015]),

should be readily detectable in fossil records, and the presence of Alnus in particular is a

clear indication of riparian or flood-plain habitat near the sampling location. Secondly,

there are some taxa which are closely associated with highly grazed meadows or fallowed 127

fields which score highly in fidelity/disperability and are significant contributors to the overall pollen rain. One is Chicoreae, which is dominant in the modern sample from a fallowed field (7), suggesting its presence in a fossil pollen sample may be indicative of field agriculture and crop rotation (which creates fallowed fields). Other regional producers associated with open sites include Amaranthaceae and Ranuculaceae.

Notes on specific taxa

• The high fidelity but less than maximum dispersablility of Castanea (Figure 5)

indicates that its pollen likely does not travel far from the tree and is unlikely to

be a significant contributor to the regional pollen rain in the past. Castanea is

absent or only present in extremely low percentages (<1%) in nearly all samples

other than the one from a Castanea grove. This is true even for samples taken

from within 2 km of a Castanea grove (samples 8, 10, 11, 12). This suggests that

if its contribution to a pollen assemblage is above about 1%, it’s likely growing

nearby the sampling location. This finding confirms what others have found

regarding the dispersability of Castanea (Conedera et al., 2004).

• Cannabis is an important contributor to fossil pollen records from Rieti Basin

lakes (Lake Lungo (Mensing et al., 2015), Lake Ventina (Chapter 2), and Lake

Ripasottile (Tunno unpublished data)). Cannabis is present in the vegetation

survey of three modern sampling locations (17, 25, 26) but only present in very

low percentages (<1%) in two samples (24, 30), neither of which had Cannabis in

the vegetation survey. Cannabis pollen averages about 3% of the total pollen sum

from Lake Ventina, and peaks at around 30% in Lake Lungo. Given the extremely

low fidelity/dispersability scores from Cannabis, it is unrealistic that such high 128

percentages in the fossil record would be generated through wind-dispersal. This

supports the interpretation of Mensing et al., 2015 that Cannabis pollen found in

the lake sediment records likely originated from retting or washing of the plants in

the lake rather than wind dispersal of pollen.

• Juniperus pollen is associated with open rather than forested sites in Figure 4, one

of only two only major non-herbaceous taxa to be so. This reflects the fact that

juniper is primarily a shrubby pioneer taxa which grows in open meadows rather

than a taxon associated with forested areas. This suggests that Juniperus pollen

may be useful for detecting open environments which are otherwise characterized

by taxa which are silent.

• Pinus is absent from the vegetation survey at all but one site (15) but is

consistently present is low percentages in the pollen samples, particularly those

from open sites. Pine is a notorious contributor to the regional pollen rain because

pine trees produce a lot of pollen that travels long distances (Bunting 2002 and

many others). The pattern seen in the modern pollen from central Italy matches

that finding.

• Fern spores are present in substantial numbers in only two sites (#2, which

contains 26% fern spores, and #3, which contains 18%) despite the presence of

ferns in the vegetation survey at eight total sampling locations. Both samples with

significant contributions from fern spores are from a mesic riparian dominated

landscape. Ferns fall into group #2 in Figure 5, suggesting mostly local dispersal.

Fern spores are substantial contributors to the pollen sum from Rieti Basin lakes

during periods in the past, particularly during medieval times in Lake Lungo 129

(Mensing et al., 2015) where they peak to as much as 40% of the total pollen sum,

and throughout the record prior to 1450 AD in Lake Ventina (Chapter 2) where

they make up 5-10% of the total pollen sum. It remains unclear what pattern of

fern growth on the landscape allows for such substantial fern spore contribution to

lake core pollen assemblages, but analysis of modern data suggests there must

have been significant fern cover very close to the lakes to produce such high

percentages.

Comparison with the Lake Ventina pollen record

A PCA ordination was constructed (Figure 7) using both the fossil pollen record

from lake Ventina as well as the modern pollen samples. The goal of this analysis was to

compare modern pollen assemblages to those from the past and identify modern analogs

for landscapes in the past. There are several conclusions that can be drawn from this

analysis. Most obviously, there is minimal overlap between the two datasets. However,

samples from the very top of the Lake Ventina record plot very similarly to several

modern samples taken from around the watershed. This suggests that while the different sampling mediums (moss polsters vs lake sediments) do impact the source area of pollen

(Zhao et al., 2009; Lisitsyna et al., 2012), the effect is probably not enough to explain the

minimal overlap between data sets. Instead, it is likely that differences in pollen

assemblage between modern and fossil samples are largely being driven by the fact that

there are not good modern analogs for many paleo landscapes. That does not mean

however that comparisons between modern and fossil records are useless.

An analysis of the modern samples which do plot closely to fossil pollen samples

can greatly enhance our understanding of what landscapes around Lake Ventina were like 130

in the past. Only one modern sample comes close to replicating the pollen assemblage

associated with most of the pre-1450 AD period in the Lake Ventina record. That is

sample #9, which was taken from a Castanea grove in the hills above Ventina. This helps

confirm that an open landscape characterized by widespread Castanea cultivation was the

dominant landscape in the Ventina watershed prior to 1450 AD.

The modern sample which most closely characterizes the post-1450 AD landscape around Ventina is #2, which was taken from a mixed forest in a riparian corridor around

Barbarano, about 40 miles away from the Rieti Basin. That this sample, and not one of the samples taken from the Ventina watershed, was the most similar to the past-1450 AD landscape is intriguing. It indicates that the modern (post-1900 AD) landscape around

Ventina may not reflect what was happening in the basin even 150 years ago. The two most recent samples from Lake Ventina plot slightly away from the other post-1450 AD samples, and very similarly to several modern samples which were taken in or near the basin. This supports the interpretation that the landscape around Ventina as recently as one-hundred years ago lacks a nearby modern analog.

Three other modern samples (4, 13, 17) serve as effective analogs for the post-

1440 AD pollen assemblage from Lake Ventina. Sample #17 was taken from a riparian zone near Piediluco Lake, less than 5 kilometers from Lake Ventina. Sample #4 was taken from a corn field in the center of the Rieti Basin. Because corn is such a low pollen producer, sample #4 is dominated by extra-local and regional pollen and has lowest contribution from local vegetation of any sample in the dataset. Sample #13 was taken from a meadow in the hills above Rieti and is characterized, like samples 4 and 17, by 131

diversity of pollen assemblage. All three samples do not have high percentages of any

one taxa, which is in part why they serve as effective analogs.

That two of the most effective modern analogs are riparian samples highlights an important trend in the dataset – the almost total lack of riparian vegetation in many of the modern samples. This may be driving some of the lack of overlap between modern and historic pollen samples and be at least in part a reflection of the different sources of the samples. Riparian vegetation is likely to be over-represented in lake sediments relative to overall land cover and pollen productivity because riparian plants grow at the edges of lakes. However, it also may be a reflection of a general lack of riparian or floodplain habitat and vegetation in and around the Rieti Basin today. To find a landscape with significant riparian trees, particularly Alnus, we had to travel well outside the Rieti Basin, to Barbarano. That part of central Italy is characterized by a series of narrow valleys cut into highly erodible volcanic tuff. These valleys are too narrow to be utilized for modern farming, have been allowed to maintain their native riparian vegetation, and serve as valuable modern analogs. Indeed, two of the samples taken from Barbarano (1 and 3) are dominated by Alnus, and have similar pollen assemblages to Alnus dominated samples in the Ventina record.

Many of the modern samples taken from forests sites are very different and plot far to the right in the PCA. This reflects the tendency of samples taken under a forest canopy to be dominated by the forest taxa present locally and to have a minimal contribution from the regional pollen rain. Many of those samples are dominated by individual taxa which make up >30% of the total pollen sum (e.g. sample 12 is 69%

Ostrya, sample 25 is 40% Ostrya and 35% Fagus, and sample 10 is 40% Quercus 132

deciduous). That these samples are unlike any samples in the Lake Ventina record is unsurprising. What is more unexpected is that all but one (#13) of the open sites in the modern pollen dataset are very different from anything from the Lake Ventina record.

This disconnect is primarily driven by two factors. First, there are three important taxa in the more open pre-1450 AD samples from Lake Ventina that are almost completely absent from the modern open site pollen assemblages: Castanea, Cannabis, and ferns.

Second, many of the modern samples are characterized by a significant contribution from local meadow taxa like Sanguisoba minor and Ranunculaceae that do not contribute in substantially to the Lake Ventina record. Pinus is also present in moderate percentages

(typically around 5% of the total pollen sum) in the modern samples but largely absent prior to the 20th century in the Lake Ventina record. Finally, Juniperus is present in many

modern open sites and contributes to the modern open samples but is a minor contributor

to the pollen sum in the least forested samples from Lake Ventina which date to before

1450 AD.

6. Conclusion

This study is one of the first to examine the relationship between vegetation and

pollen assemblage in central Italy. It shows that while pollen rain effectively captures

broad differences in landscape openness, variation in forest cover percentage in patchy

environments is difficult to detect. The consistent underrepresentation of cultivates is a

recurring issue and highlights the challenges in detecting agriculture in fossil pollen

records. There does not appear to be many modern analogs for pollen assemblages found

the Lake Ventina record, driven in part by a lack of riparian vegetation in the modern

land cover of central Italy. Additional effort must be made to identify places that might 133

represent analogs for landscapes that were more widespread in the past. This study represents an important first step toward expanding our understanding of pollen- vegetation relationships so that we can better reconstruct landscapes of the past.

134

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8. Figures

Figure 1: locator map for the central Italy and the specific sampling locations for all 30 modern pollen samples. The color of each sampling location corresponds to the site’s category (open = gold, woodland = orange, green = forested).

139

: Pollen diagram for the 30 modern pollen pollen modern 30 the for diagram : Pollen

Figure 2 samples. 140

d coppiced/uncoppiced samples. : Cluster analysis of the 30 pollen samples. Colors correspond to site category (open = gold, woodland = =orange, gold, Colors(open of correspondcategory the to: 30 pollen samples. site Cluster analysis Figure 3 brackets green and samples riparian indicate arrows Red 1. in Table numbers to site correspond Number = forested). green paire indicate 141

Figure 4: Ordination plot of pollen samples with the 20 most common individual taxa overlaid. Open sites (gold circles), semi-forested sites (orange triangles), and forested sites (green squares).

142

Figure 5: Fidelity/Dispersability of pollen taxa based on comparison between pollen samples and presence-absence vegetation survey.

143

Figure 6: Scatterplot of tree pollen % and forested land cover % within a 3 kilometer radius of each sampling location. Black trend line for the data set as a whole, green trend line only forested sites, gold trend line only open sites.

144

Ventina fossil pollen (grey (grey pollen fossil Ventina

: PCA biplot of modern pollen samples (yellow/orange/green squares) and Lake biplotand Lake modernsamplessquares) of (yellow/orange/green : pollen PCA Figure 7 are samples the Ventina with associated numbers number, are site pollen modern with associated Numbers circles). (BC/AD). age approximate 145

9. Tables

Table 1: Information and location of 30 sampling locations. Category codes are: open (O), semi-open (S), and forested (F). Samples marked (R) are riparian.

Site Elevation # Site Name Site Code Lat (W) Long (E) (m) Category 1 Barbarano Alnus forest BarAF 42.2593833 12.05995 215 F (R) 2 Barbarano mixed forest BarMF 42.2593833 12.0577 279 F 3 Barbarano mixed wet forest BarWF 42.2597333 12.053867 280 F (R) 4 Corn field #1 RBCF 42.3699167 12.924283 405 S 5 Edge of cornfield RBECF 42.3888667 12.900817 396 S 6 Edge of Lago de Rascino RasLR 42.34698 13.14423 1142 O 7 Fallowed Rieti field RBFld 42.47177 12.86508 438 O 8 Moggio 10 year coppice MogCop 42.4905833 12.721667 970 F 9 Moggio Castenea grove MogCG 42.5017222 12.722944 919 S 10 Moggio forest MogFor 42.4905833 12.721667 970 F 11 Moggio meadow MogM 42.4905833 12.721806 970 O 12 Moggio Ostrya forest MogOF 42.5016667 12.724167 920 F 13 Monte Cestagueto grassland MCG 42.493299 12.823689 473 O 14 Olea orchard BarOO 42.2637167 12.0735 347 S 15 Piediluco forest PiedF 42.515575 12.766472 399 F 16 Piediluco grassland PiedG 42.516356 12.765871 372 O 17 Piediluco riparian PiedR 42.515957 12.765289 371 F (R) 18 Rascino central meadow RasCM 42.2994833 13.133267 1240 O 19 Rascino meadow RasM 42.2877833 13.13885 1191 O Rascino meadow near 20 agriculture RasNA 42.2877833 13.13885 1191 O 21 Rascino meadow with Juniperus RasMJ 42.3018 13.1302 1234 O 22 Rascino wet meadow RasWM 42.29085 13.135 1175 O 23 Ripasottile lakeside RBRLS 42.47825 12.81104 371 O 24 Road below Moggio MogRd 42.5138611 12.734444 615 F 25 San Francesco Fagus coppice SFFC 42.53445 12.87624 1082 F 26 San Francesco Fagus forest SFFF 42.534839 12.873485 1082 F 27 San Francesco meadow SFM 42.534283 12.874588 1100 O 28 Ventina forest VenF 42.511362 12.749532 408 F 29 Ventina Ostrya coppice VenOC 42.506839 12.752566 410 F 30 Ventina Q. ilex macchia VenQI 42.510101 12.754044 395 F

146

Table 2: Presence (x) and absence of key plant taxa in the vegetation survey.

(deciduous)

type

Sample # Sample Ostrya Quercus ilex Quercus Pinus Fagus Alnus Corylus Olea ornus Fraxinus Fraxinus excelsior Ulmus Castenea Juglans Juniperus Ericaceae Phillyrea fern Poaceae Plantago Chicoreae minor Sanguisorba Ranunculaceae Asteraceae cereals Caryophyllaceae Lamiaceae Apiaceae Brassicaceae 1 x x x x x x x x x x x 2 x x x x x x x x 3 x x x x x x x x x x 4 x x x x x 5 x x x x x x x x x x x 6 x x 7 x x x x x x x 8 x x x x x 9 x x x x x 10 x x x x x x x 11 x x x x x x 12 x x x x x x 13 x x x x x x x x x 14 x x x x x x x x x 15 x x x x x x x x x x x 16 x x x x x x x 17 x x x x x x x x x x 18 x x x x x x x 19 x x x x x x x x 20 x x x x x x x x x 21 x x x x x x x 22 x x x x 23 x x x x x x x x x 24 x x x x x 25 x x x x x x x x x x x 26 x x x x x x x x x x x 27 x x x x x x x x 28 x x x x x x x x x x x x 29 x x x x x x x x x x x 30 x x x x x x x x x

147

Table 3: List of the 20 most common taxa in the pollen dataset along with their average, maximum, and median percentages. Taxa are color coded based on their structure: green for tree species, orange for shrubs and bushes, and yellow for herbs.

20 most common taxa across all samples Taxa (%) Mean Maximum Median

Ostrya type 13.87 69.66 11.6

Quercus deciduous 13.19 45.49 9.69 Poaceae 12.29 40.3 6.91 Quercus ilex 8.23 68.63 4.19 Pinus 4.56 9.37 4.74 Fagus 4.5 41.88 1.05 Olea 4.09 65.5 1.73 Plantago 3.29 24.1 1.24 Alnus 3.04 49.5 0.5 Liguliflora 2.5 33.83 0.5 Castenea 2.37 56.63 0.25

Corylus 1.97 6.99 1.43

Fraxinus ornus 1.67 9.5 0.44

Juniperus 1.62 18.91 0.55 ferns 1.6 26.25 0 Ulmus 1.19 28.25 0.25 Sanguisorba minor 1.17 14.53 0 Juglans 1.07 17.44 0.25 Ranunculaceae 1.06 9.32 0.43 Asteraceae 0.84 4.35 0.25

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Table 4a: Correlations between forest cover within 500 m, 1 km, and 3 km of the sampling sites and pollen percentages.

500 m Forest 1 km Forest 3 km Forest Overall Correlations 0.75 0.71 0.6 Forested Site Correlations 0.5 0.52 0.63 Woodland Site Correlations 0.93 0.63 0.34 Open Site Correlations 0.21 0.24 0.28

Table 4b: Averages of forest cover and tree pollen % overall and separated by site category.

500 m Averages (%) Forest 1 km Forest 3 km Forest Tree Pollen Average forest cover overall 50.9 49.2 58.6 60.6 Average amongst forested sites 69.7 62.4 67 80.6 Average amongst woodland sites 69.5 68.1 64 68.1 Average amongst open sites 22.6 27.6 47 34.8

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Conclusion

This research addressed two overarching research questions. The first was: what impacts have climate change and humans had on environmental change in central Italy and can these effects be differentiated in the fossil record? Environmental change was reconstructed using pollen in lake sediments and several periods of dramatic landscape change were identified. Human and climatic influences were interpreted by comparing that record with a new reconstruction of climate from the same sediment core. The second research question was: are trends in the environmental history of Lake Ventina local, extralocal, or regional, and does it shift over time? This question was addressed by comparing the newly developed pollen record from Lake Ventina and a previously published record from Lake Lungo. This revealed periods during which the records agreed and periods when they did not. Additionally, this comparison helped improve our ability to separate human and climatic drivers of environmental change. Beyond addressing the overall research questions, each individual chapter of the dissertation focused on generating and interpreting detailed information necessary to better understand the environmental history of the Rieti region.

The goal (Chapter 1) was to reconstruct climate in order to address a lack of climate records from central Italy that are reasonably high resolution, independent of human influence, and cover at least the last 2000 years. Modern calibration efforts indicated that carbonate precipitated in Lake Ventina has isotopic values controlled primarily by climate, suggesting that the lake is a good candidate to produce a climate reconstruction using stable isotopes of carbonate. That record revealed a climate sequence over the last 1000 years which is very similar to other records from Europe. 150

This helped confirm the record’s sensitivity to climate and provided local evidence of

climate change to compare with the pollen record. The isotope record from Lake Ventina

also revealed a cool/wet period from 750 to 950 AD which does not match well with

regional records but does coincide with Apennine glacial advance (Giraudi, 2005). This

record helped improve the interpretation of the pollen records from the Rieti region in

terms of separating climate and human drivers, and provides a valuable record of climate

for others to utilize in interpreting their records of environmental change.

The second goal (Chapter 2) was to reconstruct landscape change around Lake

Ventina and analyze drivers of environmental change by comparing that record with local

history, archaeology and other records of climate and environmental change. This

produced 2 major findings. First, that, except for two relatively short periods, from the

beginning of the record (1000 BC) until 1450 AD, the landscape surrounding Lake

Ventina was open, likely only sparsely forested, and dominated by anthropogenic

indicators. Others have found similar results from the region of Italy just to the west

(Magri and Sadori, 1999; Mercuri et al., 2002) and in the Po River valley (Kaltenrieder et

al., 2010; Mercuri et al., 2012), but the Lake Ventina record is the first to identify such an

early anthropogenic landscape from the Apennine region controlled by the Sabini during

the Bronze and Iron Ages. Second, the comparison between the records from Lake

Ventina and Lake Lungo represented a unique opportunity to compare nearby records and

resulted in the discovery of a shift in the heterogeneity of environmental change at 750

AD. That two lakes have radically different pollen signals prior to 750 AD suggests that

in order to capture broad-scale trends in environmental change we must develop records from a wide variety of sites in different topographical settings. It also suggests climate 151

was not a key driver of environmental change from least 1000 BC until 750 AD. The two

records largely co-vary after 750 AD suggesting a greater landscape coherence and

potentially an increase in the importance of climate.

A third goal (Chapter 3) was to make the first attempt to quantify the modern

pollen of central Italy through a surface pollen study. This resulted in several key

findings that improve our ability to interpret fossil pollen records from the region. First,

the lack of modern analogs for fossil pollen assemblages from the Lake Ventina record,

particularly prior to 1450 AD, is striking. Several modern samples had low percentages

of forest taxa similar to the fossil record, but a lack of Castanea prevented them from

serving as reasonable analogs. Additionally, the extremely limited distribution of Alnus

found in central Italy today meant that it was difficult to find modern samples with

similar pollen assemblages to those from the past, which often contain substantial Alnus

pollen. A second important finding was that many taxa associated with anthropogenic

activities do not contribute significantly to the regional pollen rain, and thus when present

in a pollen record are strongly indicative of human impacts. These include Cannabis,

Urtica, and cereals. Pollen of Olea/Juglans/Castanea, which are often used as regional

indicators of human impacts (Mercuri et al., 2013) do not have maximum

fidelity/dispersability scores. This suggests that when those taxa are present in a pollen

record in substantial numbers it is likely that a large number of the trees were present

near the sampling location. Overall, the analysis of modern pollen greatly improved our

ability to interpret spatial patterns of land cover derived from analysis of fossil pollen,

both from Lake Ventina and other sites from the region. 152

Overall, this dissertation was able to address each research question. However, going forward there are several ways to improve this approach to environmental history based on reconstructing and interpreting environmental change through pollen analysis.

By taking the aspects of this research that were successful, and adding additional improvements, we can better understand the history of environmental change in ways that make it applicable for both Italy and other regions.

Future Work

It is important to consider ways that study design and implementation can be improved, and how to apply what has been learned from this study to other similar projects. A major challenge of this study, and the Rieti Basin project as a whole, was the age control. The ineffectiveness of radiocarbon caused us to use paleomagnetic secular variation (PSV) to date the sediment cores from Lakes Lungo, Ripasottile, and Ventina.

While we were successful in constructing robust chronologies, the process is time- consuming and expensive. PSV has the limitation that you cannot take additional measurements in places or periods of time when reduced age uncertainty would be particularly valuable. This is problematic because when comparing precisely dated historical events to proxies from sediment cores, dating of the sediment is a source of error and can limit our ability to establish causality. These issues are minimized by working with sediments which are dateable using radiocarbon. There is substantial value in working with sediment cores which contain abundant plant macrofossils and do not have dead carbon issues. This offers the opportunity to better link features in the pollen record with explicit human events and determine more accurately relative timing between them. 153

A second important improvement that can be made is to develop multiple climate

reconstructions. The development of an oxygen isotope record from Lake Ventina has

been invaluable for the interpretation of environmental change and provided the first

well-dated local climate record for the region. However, a multi-proxy approach to reconstructing climate is more robust and allows for the reconstruction of multiple facets of climate (i.e. the ability to reconstruct temperature and precipitation). Proxies from lake sediments which are not impacted by human-driven changes to limnology are particularly valuable. This is a limitation of carbonate isotopes from lake sediments. By better understanding how local climate has changed in the past via multi-proxy independent reconstructions we can better address questions focused on the role of climate as a driver of environmental change during an era of intense human impacts.

Access to a local historical archive of primary documents will greatly improve our understanding of how humans impacted the landscape. The Rieti Basin project largely relied on secondary historical sources, in part because primary sources were limited.

Working an area with better historical documentation allows us to focus on local land use and land ownership and will improve our ability to compare historical drivers of environmental change with proxy reconstructions. Local climate history can also be developed through the analysis of written records of floods, storms, early frosts, etc.

Going forward, working with better local history promotes integration between history and environmental change because both records are operating at similar temporal and spatial scales.

Developing records that extend back farther in time is another way to improve upon the Rieti Basin project. One of the major unresolved questions raised by the record 154

from Lake Ventina is the timing of the establishment of the highly anthropogenic landscape around the lake. The temporal range of that study was limited by the depth of sediment we were able to collect with our coring equipment. The rapid sedimentation in the Rieti Basin meant that with had operated equipment we were unable to recover sediment cores longer than 12 – 15 m, which extended back about 3000 years. Sites which slower sedimentation rates allow the reconstructions of landscape prior to widespread human impacts and the identification of the timing of the first substantial impacts of humans.

Overall, the lessons learned and insight gained from the Rieti Basin project and outlined in this dissertation will be put to good use, not only though the publication of those records but also in helping guide the next phase of the research.

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Citations

Giraudi, C. (2005). Late-Holocene alluvial events in the Central Apennines, Italy. The Holocene, 15(5), 768–773. https://doi.org/10.1191/0959683605hl850rr

Magri, D., & Sadori, L. (1999). Late Pleistocene and Holocene pollen stratigraphy at Lago di Vico, central Italy. Vegetation History and Archaeobotany 8: 247–260.