\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[T2A]{fontenc}
\usepackage[ngerman,polish,romanian,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Habitat characteristics and the rate of decline in a threatened farmland
bird, the Ortolan Bunting}



\author[1]{Sirke Piirainen}%
\author[2]{Markus Piha}%
\author[2]{Tuomas Seimola}%
\author[2]{Andreas Linden}%
\affil[1]{University of Helsinki}%
\affil[2]{Natural Resources Institute Finland}%


\vspace{-1em}



  
  \date{June 17, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Farmland habitats are witnessing steep declines in biodiversity. One
rapidly declining farmland species is the Ortolan Bunting. In Finland, a
staggering 99\% of the population has been lost during the past 30
years. Changes in the breeding habitats have been proposed as a reason
for the decline, although hazards during migration and wintering may
also play a role. We gathered a 19-year data set of Finnish Ortolan
Buntings and studied which spatial characteristics, habitat features,
and climate factors might explain the population growth rate at the
singing-group level. As explanatory variables we used region, density of
small-scale landscape structures, proportion of agricultural area in the
landscape, diversity of crop types, proportion of bare ground, and
temperature and precipitation of previous breeding season. The only
region with a marginally positive growth rate was North Ostrobothnia,
where the species often occupies newly established fields. High crop
type diversity mitigated the declines by perhaps providing a wide array
of feeding, hiding and nesting places. Bare ground benefited Ortolan
Buntings by perhaps providing an easy access to food. The last Ortolan
Buntings occurred in landscapes dominated by interconnected agricultural
land which, we think, reflects the species' sociability and avoidance of
forested areas. We suggest that agricultural intensification and the
following potential reduction in food availability may be a cause of the
decline of Ortolan Bunting. As general conservation measures, such as
promoting set-aside land or field margins, have been inadequate, either
in effect or in extent of application, it is evident that work remains.
Northern populations of Ortolan Bunting should be targeted for further
studies on feeding and breeding ecology as well as for urgent
conservation actions, such as increasing crop type diversity and bare
ground. Promoting more multi-functional and agro-ecologically managed
agricultural landscapes would benefit a wider range of farmland species
as well.%
\end{abstract}%



\sloppy


\textbf{TITLE}

Habitat characteristics and the rate of decline in a threatened farmland
bird, the Ortolan Bunting

\textbf{ABSTRACT}

Farmland habitats are witnessing steep declines in biodiversity. One
rapidly declining farmland species is the Ortolan Bunting. In Finland, a
staggering 99\% of the population has been lost during the past 30
years. Changes in the breeding habitats have been proposed as a reason
for the decline, although hazards during migration and wintering may
also play a role.

We gathered a 19-year data set of Finnish Ortolan Buntings and studied
which spatial characteristics, habitat features, and climate factors
might explain the population growth rate at the singing-group level. As
explanatory variables we used region, density of small-scale landscape
structures, proportion of agricultural area in the landscape, diversity
of crop types, proportion of bare ground, and temperature and
precipitation of previous breeding season.

The only region with a marginally positive growth rate was North
Ostrobothnia, where the species often occupies newly established fields.
High crop type diversity mitigated the declines by perhaps providing a
wide array of feeding, hiding and nesting places. Bare ground benefited
Ortolan Buntings by perhaps providing an easy access to food. The last
Ortolan Buntings occurred in landscapes dominated by interconnected
agricultural land which, we think, reflects the species' sociability and
avoidance of forested areas.

We suggest that agricultural intensification and the following potential
reduction in food availability may be a cause of the decline of Ortolan
Bunting. As general conservation measures, such as promoting set-aside
land or field margins, have been inadequate, either in effect or in
extent of application, it is evident that work remains. Northern
populations of Ortolan Bunting should be targeted for further studies on
feeding and breeding ecology as well as for urgent conservation actions,
such as increasing crop type diversity and bare ground. Promoting more
multi-functional and agro-ecologically managed agricultural landscapes
would benefit a wider range of farmland species as well.

\textbf{KEY WORDS}

farmland birds, agricultural intensification, species conservation,
habitat selection, population decline, vegetation structure

\textbf{1. INTRODUCTION}

Several farmland bird species in Western Europe are declining rapidly
primarily due to the intensification of agricultural practices (Burns et
al., 2016; Jerrentrup et al., 2017; Tryjanowski et al., 2011). These
practices include for example building sub-surface soil drainage
systems, which cause habitat loss and change, increased fertilizer use
leading to denser vegetation, fast crop growth and short turn-over
rates, increased pesticide and herbicide usage resulting in lower
abundance and diversity of food/insects/arthropods, and the
specialization and standardization of agriculture, which tends to create
homogenous landscapes with large fields of low crop diversity
(Schifferli, 2001). The European Union has initiated several schemes
with the aim to prevent the loss of biodiversity in agricultural
habitats, but these schemes seem to have had limited success, preserving
biodiversity only at the local scale and to moderate extent (Gamero et
al., 2017; Kleijn et al., 2011).

The Ortolan Bunting, a small Palearctic migratory songbird, is an
example of a species experiencing an extreme population decline. It
breeds from Spain to Mongolia and from Iran to northern Finland and
migrates to spend the winter in sub-Saharan Africa (Jiguet et al.,
2019). Across Europe, the species has faced continuous population
declines, with a general drop of 88\% since 1980 (Jiguet et al., 2016).
The status of the species is particularly alarming in Northern Europe,
where it is critically endangered (Hyv\selectlanguage{ngerman}ärinen et al., 2019). In Finland,
the decline has been approximately 99\% within the past 30 years
(Väisänen and Lehikoinen, 2013), with only 2,600 pairs remaining in 2020
(Piha and Seimola, 2021). In Fennoscandia, Ortolan Buntings occur at
their northernmost range limit and are genetically and demographically
isolated from the rest of the European population, making them
particularly sensitive to potential threats with no immigration to
counteract the declines (Moussy et al., 2018).

Understanding the reasons behind such dramatic declines as the one of
the Ortolan Bunting can provide highly valuable information on how to
manage farmlands in a more biodiversity-friendly way. Numerous threats
such as habitat loss and degradation, climate change, and illegal
hunting, are believed to explain the declines of Ortolan Buntings (Menz
and Arlettaz, 2012). Especially the threats along the flyways have been
studied intensively (Jiguet et al., 2016), and recently, the wintering
habitats have been under investigation (Gremion et al., 2022).

Survival studies done in Norway and Finland show that Ortolan Buntings
may not be suffering exceptionally great losses during their migration
or wintering in Africa. In a study done by Nousiainen (2020) during
2013--2019, Finnish male Ortolan Buntings had an apparent annual
survival rate of 43.3 \% (41.9--58.0 \%; in 15 other similarly sized
passerine species). Similar, or somewhat higher, survival rates were
found in the Norwegian Ortolan Bunting populations (Dale, 2016).
Additionally, Nousiainen (2020) found that the survival was equally good
throughout all the three main regions where the species occurs in
Finland. Based on this result, the survival of the male Ortolan Buntings
is likely not particularly low, and thus does not appear to be the most
important factor explaining the declines. In contrast, there were
regional differences in population declines, with the steepest declines
in southwestern parts of the population, where more than fourth of the
population was lost annually (Nousiainen 2020, Piha \& Seimola 2021). In
summary, although the survival of females and juveniles were not
examined in this study, this result already in itself hints that there
might be some regionally varying factors regulating breeding success
that might, at least partly, explain the dramatic declines in Ortolan
Bunting populations. Hence, it seems that important reasons for the
declines are to be found within the breeding areas.

The breeding habitat requirements of the Ortolan Bunting have been
intensively studied, mainly in the agricultural habitats where the
decline is steepest (Menz and Arlettaz, 2012). In general, the Ortolan
Bunting has largely varying habitat requirements. In the most southern
parts of its current distribution, in the Mediterranean and
sub-Mediterranean Europe, Ortolan Bunting breeds in open shrubland and
steppe-like habitats, and montane zones up to 2,500 m above sea level.
In temperate Europe, it is primarily associated with cultivated land and
shrublands in historically burnt habitats (see references in Menz and
Arlettaz, 2012). In Nordic countries, the species is present in a range
of different breeding environments; not only in farmland habitats, but
also in clear cuts and peat production bogs (Dale and Christiansen,
2010; Dale and Olsen, 2002; Vepsäläinen et al., 2007). In Finland, the
species is rarely observed in small, fragmented fields within forest
dominated landscapes (Piha and Seimola, 2021). Within both natural and
agricultural landscapes, the Ortolan Bunting breeds primarily in
relatively warm, dry areas, with well-drained soils and an annual
rainfall below 600--700 mm (Cramp and Perrins, 1994). The fact that the
species becomes often locally common after disturbance, for example
after a fire or a clear cut, indicates that the species may behave like
a pioneer species, typically colonizing the early stages of vegetation
succession (Pons and Clavero, 2010).

At the territory level in agricultural habitats, the Ortolan Bunting is
associated with field margins featuring structural elements such as
isolated trees and hedges which are used for perching and singing
(Grützmann et al., 2002). High crop type diversity seems to be important
for the species since the species primarily nests and forages on the
ground (Berg, 2008), and a single crop type rarely provides a suitable
vegetation structure throughout the breeding season. Low vegetation
structure with patches of bare ground is more easily accessible to birds
foraging and moving on the ground than uniformly dense growing crops
(Schaub et al., 2010; Schifferli, 2001), while higher and denser
vegetation is needed for hiding the nest.

Despite extensive studies on Ortolan Bunting breeding habitat
requirements, few have directly linked habitat factors to the population
growth rate of the species. Furthermore, many of the previous studies
have been limited either to small geographical areas, conducted solely
at the territory scale or focused on the occurrence probability (or
density of territories) over a single year or a few years.

We investigated the relationship between changes in the Ortolan
Bunting's breeding habitat characteristics and the rate of decline of
the species in a multiscale context where both territorial and landscape
levels are considered simultaneously. We used an exceptionally large
data set which covered approximately the whole Finnish breeding range
area and nearly two decades of observations, collected with a
comprehensive territorial mapping approach.

Specifically, we studied whether the rates of decline in Ortolan Bunting
populations were associated with i) proportion of agricultural land
cover within the landscape surrounding the subpopulation (landscape
variable), ii) crop plant type diversity and the proportion of bare
ground (crop variables), iii) density of roads, ditches, main drains,
riverbanks and buildings (small-scale structure variables), or iv)
temperature and rainfall from the previous year (weather variables),
while also assessing v) potential regional variation in the declines.

We hypothesized that the reduction of small-scale structures, loss of
diversity in crop types and reduction in the amount of bare ground have
had negative effects on Ortolan Bunting population growth rate. We also
expected that population growth rates are more negative in areas with
smaller proportion of farmland in the landscape. In addition, we
expected that cold and rainy breeding seasons reduced population growth
to the next year.

\textbf{2. MATERIAL AND METHODS}

2.1 Study area

Most of the studied Ortolan Bunting subpopulations, hereafter singing
groups, were located along the coast of Finland and in the southern
parts of the country, where agriculture in general is concentrated in
Finland. Few study sites were in the eastern and Central Finland (Figure
1). The study area represents the northernmost distribution range limit
of the species.

2.2. Bird data

The territories of the Ortolan buntings were mapped annually using a
two-visit mapping method, which has been shown to be effective and
reliable for mapping the species (Tiainen et al., 1985). The visits were
made in May and the first half of June. Special attention was paid to
simultaneous observations of singing males, to the territory locations,
and to accurate estimation of territory numbers in territory
concentrations. For each observed territory, its centre coordinates were
recorded. In total 4,430 territories were recorded over the 19-year
study period, from 2000 to 2018.

2.2.1 Forming singing group units

To form a study unit, we aggregated observations of territories from
years 2000--2017 (observations from year 2018 were added in after the
forming of singing groups) based on their proximity and surrounding
landscape. Territories that were less than 500 metres away from each
other, were considered to belong to the same singing group, i.e.,
subpopulation. Thus, we drew a 250-meter buffer around each territory
observation within a singing group, merged the overlapping buffers and
interpreted the outline as delineating the area occupied by that singing
group (Figure 2). Ortolan Bunting territories have an average radius of
about 100--300 meters (Vepsäläinen et al., 2007).

This kind of automatic forming of singing groups based on distance only
produced sometimes very large singing groups which, in reality, might
have consisted of several smaller groups separated by some natural
boundary or other unfavourable matrix, such as a narrow stretch of
forest or a busy road. Sometimes separate smaller singing groups were
formed, when, in reality, they might have belonged to the same group
despite the distance between the observations (or despite the failure to
observe individuals between the observations). Therefore, in few cases a
spatially very large singing group was divided into two or several
smaller ones, or a few small and separate but adjacent singing groups
were merged into one large group. When splitting a large group, the area
along the split was proportionally divided to the newly formed singing
groups. This ensured that a certain habitat area was not covered twice
in separate singing groups. These exceptions (splits and merges) were
always based on the observer's perception on the field.

In total we formed 277 singing groups. Each singing group had an
individual identification code (ID) and its centroid coordinates were
recorded. Additionally, we recorded the region (REGION) and the
municipality (MUN) within which a singing group was located (seven
regions and 65 municipalities in total).

For each singing group we counted the annual number of territories
(TERRI). For some years and some singing groups this information is
missing, as not all sites have been visited annually, or because new
locations (singing groups) have been added to the monitoring scheme
during the study period. In total, the data consists of 1,474 annual
territory mappings of singing groups.

2.3 Habitat and climate data

For each singing group area, we defined variables describing the habitat
they occupied. From the Finnish topographic database (National Land
Survey of Finland, 2023) we counted the length of roads, ditches, main
drains and riverbanks (in metres) and the number of buildings within the
singing group area. As there are little annual changes in these
measures, we used data from years 2005, 2010 and 2016 to cover the years
2000--2007, 2008--2012 and 2013--2018, respectively. We then divided
each of these measures by the area of the singing group to form a
variable describing the density of each small-scale element (AROAD,
ASTREAM, ARIVER, ABUILD).

By combining data from the Finnish land and crop parcel registers
(Finnish Food Authority, 2023) we counted the total area of crop species
grown within a singing group area. For years 2000--2016, in cases where
more than one crop species was grown per field parcel, the data were
unspecific about the precise location of different crop plants within a
field parcel. Therefore, in cases where a field parcel with multiple
crop plants was only partly within the singing group area, the areas of
crop species were estimated based on their relative proportions within
the field parcel. In cases where crop data were untraceable or not
available, we completed the data from field notes, when possible,
otherwise the crop was classified as ``unknown species''.

Based on plant type or growth form we classified crop species into ten
crop types: spring cereals (proportion of all observed crop types 0.54),
grasses (0.26), winter cereals (0.06), oil plants (0.06), open-ground
vegetables (0.03), legumes (0.02), herbs (0.01), unknown species (0.01),
fruits and berries (0.005) and bioenergy crops (mainly reed canary
grass, 0.003). For each singing group area, we then counted the
proportions of each of these crop types and based on those, a
Shannon--Wiener diversity index of crop types (SHANG).

Crop types were further classified into two groups based on how much
vegetative cover the plants form during the start of the Ortolan Bunting
breeding season in early May. Crop types which provide only minor cover
and leave substantial amounts of bare ground on the field, mainly as a
result of the associated ploughing practice, were classified as `bare'
(spring cereals, open-ground vegetables, oil plants and legumes), and
crop types that provide substantial vegetative cover were classified as
`cover' (grasses and winter cereals, autumn-sown oil-seed rape). We then
counted the proportion of `bare' crop types within a singing group area
(BARE).

To assess the interconnectedness of the agricultural landscape
surrounding the singing group, we created a 5-km buffer around the
singing group centroid and calculated the proportion of agricultural
land cover (AGRI5) within the buffer using the Finnish Corine land cover
data provided by the Finnish Environment Institute (Finnish Environment
Institute, 2023). We used data from years 2000, 2006, 2012 and 2018 to
cover the years 2000--2003, 2004--2009, 2010--2015 and 2016--2018,
respectively.

From the Finnish meteorological data (Aalto et al., 2016) we calculated
the mean daily temperature (TEMP) and precipitation (PREC) of the
previous summer (21. May--15. July).

2.4 Statistical analyses

To focus on the multiplicative population rate of change of Ortolan
Buntings, we first delimited our data to only those cases that had data
from two consecutive years, i.e., with no gap between annual
observations. Then we created a variable describing the number of
territories in a singing group during the previous year (TERPRE), and
further removed from the data those observations, where TERPRE was zero
(no territories observed the previous year).

These limitations reduced the number of observations (annual territory
counts of singing groups) to 678. The number of individual singing
groups also reduced to 238. The number of consecutive visits (annual
territory counts) per singing group varied from 1 to 13 (mean 2.8) and
the number of territories per singing group varied from 0 to 26 (mean
4.25). Singing group areas ranged from 0.19 to 2.98
km\textsuperscript{2} (average 1 km\textsuperscript{2}, SD = 0.73). The
spatial and temporal extent of the data remained approximately the same
after the data limitations. However, from Central Finland and North
Carelia only three and one observations, respectively, remained and they
were, in both cases, from only one singing group.

To model the change in number of Ortolan Bunting territories per singing
group, we applied generalized linear mixed models with logarithmic
link-functions. In the statistical analysis we first did model selection
based on the model with the simplest set of fixed effects, to determine
the most parsimonious approach for describing randomness, i.e., the
random effect structure and error distribution -- to be further used for
studying the drivers of the decline as fixed effects. We compared 12
different models, each with only the categorical variable region
(REGION) as a fixed effect and number of territories in previous year
(TERPRE) as a log-transformed offset, and either i) no random effect
(i.e., resulting in a GLM rather than a GLMM), ii) ID as random effect,
iii) MUN as random effect, or iv) ID nested within MUN as random effect.
These four model combinations were evaluated using three error
distributions: i) Poisson, ii) COM-Poisson and iii) negative binomial;
all of which show different dispersion patterns or relationships between
the mean and the variance. Option ii) accommodates both over- and
underdispersion, while option iii) can model overdispersion only. As
singing groups were sampled multiple times, we wanted to test applying a
mixed model in which~singing group~is used as random intercept, as this
models a dependency structure among observations (variation in the
average rates of change) from the same singing group. Including
municipality as random intercept controls for possible spatial
correlation in the average rate of change between singing groups which
are located near to each other. In the fitting of the models, we used
restricted maximum likelihood estimation (REML) in order to acquire
estimators for the variance terms which are not biased.

We ranked the candidate models by the Akaike information criterion with
a correction for small sample sizes (AICc) to evaluate their relative
fit with data (Burnham and Anderson, 2002) and chose the model with the
lowest AICc value as the best model structure for further analysis of
fixed effects.

Based on the selected random structure (see Table S1 in Supplementary
material), we studied which habitat variables explain the decrease in
number of Ortolan Bunting territories within a singing group, by
creating 16 nested models varying in their fixed effects only. All
models included region (REGION) as fixed effect and number of previous
year territories (TERPRE) as a log-transformed offset variable. In
addition to these, the models contained all the possible combinations of
the following groups of variables: i) weather (TEMP and PREC), ii) crop
(SHANG and BARE), iii) small-scale structural element (AROAD, ASTREAM,
ARIVER and ABUILD) and iv) landscape (AGRI5) variables (see Table 1 for
full list of models). In the model selection for different fixed effects
models, we used maximum likelihood estimation. Again, we ranked the
candidate models by the Akaike information criterion with a correction
for small sample sizes (AICc) to evaluate their relative fit with data
(Burnham and Anderson, 2002) and chose the model with the lowest AICc
value as the best model. Prior to running the model, all continuous
variables AGRI5, PREC, TEMP, SHANG, BARE, ABUILD, ARIVER, ASTREAM and
AROAD were scaled by subtracting the mean and dividing with the standard
deviation.

All statistical analyses were done in the programming environment R
program, version 4.3.1 (R Core Team, 2023). Models were fitted with
glmmTMB-package (Brooks et al., 2017) and model selection was conducted
with the MuMin-package (Bárton, 2023).

\textbf{3. RESULTS}

Regarding the 12 models of random effect structure, the model with no
random effects structure and COM-Poisson error distribution was selected
as the most parsimonious one (Table S1 in Supplementary material).

Regarding the 16 alternatives fixed effects models (all including the
permanent variable REGION), the model with the lowest AICc included also
AGRI5 and crop variables, SHANG and BARE (Table 1).

Compared with the North Ostrobothnia region, which showed stable or
slightly positive population growth, all other regions were associated
with strongly negative rates of population change (Table 2, Figure 3).
Crop type diversity (SHANG) was, as expected, associated with positive
rates of change (Table 2, Figure 4). Considering the proportion of
farmland within the landscape surrounding the singing group (AGRI5) and
the proportion of bare ground within the singing group's range (BARE),
the coefficient point estimates show a positive association with the
rate of change but do not differ clearly from zero (Table 2, Figure 4).

In the whole of Finland, the average logarithmic rate of population
growth was --0.21 (SE = 0.04; excluding Central Finland and North
Carelia which had so low sample sizes).

\textbf{4. DISCUSSION}

Our results showed that the multiplicative population rate of change of
Ortolan Buntings within the study period from 2000 to 2018 was
positively associated with greater crop type diversity and with higher
proportion of bare ground within a singing group's range. Also, the
proportion of farmland surrounding the singing group had a positive
association with the rate of population change. Notably, the mean rate
of population growth was positive only in the North Ostrobothnia region,
while all other regions showed negative growth rates.

\textbf{4.1} \textbf{Importance of crop type diversity and bare ground}

Our study revealed a positive association between Ortolan Bunting
population growth rate and the two crop variables, crop type diversity
and proportion of bare ground. Albeit the association was rather weak
for bare ground. High crop type diversity at the territory scale may
emerge as a critical factor, as single crop types rarely offer suitable
vegetation structure for both nesting and foraging throughout the
breeding season. Ground-feeding birds, like the Ortolan Bunting, may
face challenges in finding food (insects, arthropods etc.) within
impenetrable, tall and dense vegetation (Schifferli, 2001) usually
associated with intensive farming. On the other hand, various taller or
denser vegetation is needed for providing safe nest sites. Therefore, a
mosaic of diverse crop plants of different sowing times, sward heights
and densities as well as patches of bare ground may better support the
Ortolan Bunting which may otherwise suffer from higher costs of
reproduction, reduced breeding success and chick survival.

The importance of these crop variables has been found in earlier habitat
preference studies as well. In central Sweden, Ortolan Buntings were
found to prefer habitats which had heterogeneous ground vegetation
characterized by patches with bare ground, or at least sparse ground
vegetation, intermixed with patches with taller vegetation (Berg, 2008).
In Finland, in the Tavastia region, Vepsäläinen et al. (2005) showed
that the area of field growing spring cereal, root crops, etc. (i.e.,
field not covered in springtime) had a positive effect on the occurrence
of the Ortolan Bunting, although they witnessed a population crash
happening in spite of an increase in the area of non-covered field.
Santana et al. (2017) however, found that in open Mediterranean
farmland, when considering bird species richness, it was more important
what crops were grown than their diversity or spatial configuration.
Also Morelli (2012) showed that the occurrence of Central Italian
Ortolan Buntings was not clearly related to structural heterogeneity,
rather the species seemed to be associated with sunflower fields, oats
and alfalfa. Yet, the authors concluded that these crop types may be
preferred because of certain structural characteristics that may
increase space with bare soil, which would be consistent with our
findings.

Climate change might affect, now and in the future, the choice between
grains that are sown in the spring or in the autumn. If farmers choose
to grow more autumn sown grains, the proportion of bare ground in the
spring, at the time of feeding the nestlings, will reduce in the future.
This change will most likely affect Ortolan Buntings negatively,
starting from the southwestern populations which occupy areas that are
specialized in growing grains. Similarly, the increasing popularity of
direct sowing techniques might be reducing the amount of ploughed field
areas i.e., bare ground, affecting Ortolan Buntings negatively.

\textbf{4.2 Importance of interconnected agricultural landscape}

Our findings revealed a weak positive connection between the proportion
of farmland surrounding the singing groups and the population growth
rate. Indeed, in Finland, we see that Ortolan Buntings are still
surviving in singing groups located in landscapes that are characterized
by interconnected agricultural areas.

We propose two explanations for this result. Firstly, large and
interconnected farmland areas tend to be more intensively managed than
smaller, more scattered farmlands which usually include less intensively
managed or even abandoned fields. In Germany, in the Wendland region,
the Ortolan Bunting population was growing at the turn of the
21\textsuperscript{st} century (approx. 1995--2007). This increase was
connected with a major change in land use: a notable proportion of
grassland was converted to arable land (Deutsch, 2007). Abandoned arable
land will eventually have higher and denser vegetation cover, and
possibly more predators, which will be unfavourable for Ortolan
Buntings. In Italy, the dense afforestation and grassing after the
abandonment of pastoral and agricultural activities are hypothesized to
be the causes of Ortolan Bunting extinctions in the hills of Brescia
(Leo et al., 2023). Also, in Sweden and England farmland birds are
declining possibly due to both agricultural intensification and
abandonment (Wretenberg et al., 2006). Also at its wintering grounds,
the Ortolan Bunting seems to prefer extensively managed, structured and
semi-open agricultural landscapes (Gremion et al., 2022). It seems
evident, that an intermediate level of management benefits the Ortolan
Buntings by providing a suitable set of habitat characteristics.

Secondly, Ortolan Buntings are social birds that form singing groups of
several males (Cramp and Perrins, 1994). Therefore the species shows an
aggregated distribution pattern, one which is only partly determined by
habitat structure and quality (Vepsäläinen et al., 2005). In large,
interconnected farmland areas there is more space and suitable habitat
for several singing males to establish territories. These males then, in
turn, can attract more singing males, and eventually also females to the
same area. A smaller, isolated farmland patch of otherwise ideal habitat
might not be as attractive to the species, because it has a lower
potential for formation of a new singing group. The disappearance of
group structure in declining populations might hamper breeding even
further. In Norway, the small Ortolan Bunting population has a strongly
male-biased adult sex ratio due to female-biased natal dispersal away
from the small and isolated distribution area. This skew logically
affects the pairing success of males. In the Norwegian population, about
half of all males are unpaired (Dale, 2011). In Finland, less than 70\%
of Ortolan males were paired in an inventory study (Piha and Seimola,
2021). If females disperse away from good but fragmented habitats,
without finding better breeding sites or companions elsewhere, small
local population might be heading to extinction slowly and irrespective
of whatever conservation measures are made locally. The only measure
that can help in this situation would be the rapid habitat restoration
in the matrix between existing habitat fragments (Dale, 2001). Another,
in this case potentially disadvantageous, aspect of sociability, is the
strong site fidelity of adult Ortolan Bunting males. Adult males may
maintain singing groups despite the habitat transforming to suboptimal
for breeding. Site fidelity might hence further mask the results related
to habitat characteristics.

In summary, at the landscape level, large and interconnected farmland
areas represent open and sufficiently managed areas, possibly attracting
conspecifics, and might therefore function as an ecological filter which
can influence the preference for certain habitat characteristics.
Otherwise good breeding sites might be neglected if they do not occur
within interconnected farmland landscapes.

\textbf{4.3} \textbf{Positive growth rates only in North Ostrobothnia}

Among all the regions, only North Ostrobothnia showed positive
population growth rates, while South Ostrobothnia, Tavastia, South-West
Finland, North Carelia, Uusimaa and Central Finland showed negative
population growth rates.

Several factors might contribute to the observed variance in growth
rates between regions. Firstly, North Ostrobothnia boasts a substantial
amount of newly established agricultural fields, mainly converted from
peatlands. These areas have not yet been under heavy agricultural
management practices, such as pesticides or turning of the soil. They
often feature exposed mineral soil and natural vegetation with extensive
growth of bushes (\emph{Salix} sp.) and young trees (\emph{Betula}
sp.,\emph{Sorbus} sp., etc.), which offer abundant food resources. Food
seems to be plenty during the feeding period along the stretches of land
between the peat extraction fields where willows and birches are growing
(field observations).

Secondly, the specialization of farms has been intensive in Finland
during the last decades, namely eastern and northern parts of the
country are mainly specialized in cattle farming and southern parts in
grains and vegetables (Hiironen and Ettanen, 2013). For example, in
eastern Finland large farmland areas almost exclusively grow fodder
grass hence leaving negligible amount of bare ground for the birds
during spring.

Thirdly, concerning species distribution, it is important to consider
that the presence of species in a particular location may not solely be
due to the suitability of the habitat but also influenced by the fact
that species had a means of getting there (spatial aspects of population
dynamics, metapopulation dynamics) (Storch et al., 2003). The fact that
the Finnish Ortolan Bunting population has declined less in the north
and the resulting shift towards north could be a mere result of the
deterioration of the southern habitats and the fact that the birds have
no other direction to go to. However, field observations do not support
this wholeheartedly. In Finland, there are two easily distinguishable
singing type populations (dialects) in Finland, the northern and the
southern, which are geographically isolated, and seem to be disconnected
from each other without any significant immigration between populations
(Piha \& Seimola, 2021). As birds generally learn their songs from one
another, the persistence of these song types may indicate limited
dispersal (via recruitment), which is likely in the context of a
declining population.

Research on the breeding- and population biology of Ortolan Buntings in
different regions of Finland would elucidate whether the breeding of the
species is failing and the causes for it, and which regions currently
act as sources or sinks. Although, this research might already come too
late as the Allee effect often occurring in extremely small populations,
might impair deductions from such investigations. The fast decline of
Ortolan Buntings has continued after the study period, in all regions of
Finland (Piha and Seimola, 2021).

\textbf{4.4. Small-scale landscape characteristics and weather: lack of
impact on population growth}

Surprisingly, small-scale landscape structures did not significantly
influence population growth rate in this study. One explanation to this
could be the way we formed these variables. By measuring the density of
linear structures such as roads, main drainage ditches and riversides,
we aimed at quantifying the potentially beneficial effect of edge
habitats; for example, woody perennial vegetation, such as
\emph{Salix}sp. or \emph{Betula} sp., providing an important source of
larvae and insects to feed the nestlings. However, our variables lacked
the information whether the roadside or drainage ditch had any such
vegetation. Most likely they had at least some taller vegetation most of
the time, but every few years the farmers tend to cut down the bushes
along their driveways. It is possible that crop type diversity (SHANG)
served as an indirect indicator of smaller average field plot size thus
suggesting a greater availability of important edge habitat (ditches,
field margins) for nesting.

Concerning the weather variables, likewise, Vepsäläinen (2005) did not
find a link between weather conditions of previous year's breeding
season and Ortolan Bunting densities. These results suggest that other
variables are primarily driving the Ortolan Bunting declines.

\textbf{4.5. Potential role of agricultural intensification in the
decline of Ortolan Bunting}

Our results show the importance of specific habitat characteristics such
as high crop type diversity and availability of bare ground for the
Ortolan Buntings. These preferred habitat characteristics are more
typical for traditional, small-scale farming. The results also highlight
regional variations. Notably, regions with higher agricultural
intensification, like South-West Finland, showed lower population growth
rates, suggesting a potential link between intensification and
population decline. The fields occupied by Ortolan Buntings in North
Ostrobothnia are usually rather new fields and have thus not been under
intensive agricultural management as long as the fields occupied by
Ortolan Buntings in South-West Finland have.

Agricultural intensification may have detrimental effects on
biodiversity through several means. Concerning the Ortolan Bunting,
reductions in prey availability or accessibility due to habitat
deterioration on the breeding grounds could be one of the main reasons
behind the negative population growth rate of the species. Also, the
role of nest predators might have changed due to habitat deterioration
caused by agricultural intensification. Habitat change might have forced
birds to nest in unsafe habitat types or reduced availability of
alternative food sources may have caused generalist predators to change
their diets (Evans, 2004). Krüger et al. (2018) showed that the Raccoon
Dog (\emph{Nyctereutes procyonoides} ) is a potential new mammalian nest
predator successfully invading agricultural habitats in Finland. The
Raccoon Dog has colonized the country within the past 70 years, starting
from the Southeast Finland and now has a distribution which covers most
of Finland, except the northernmost parts (Kauhala and Kowalczyk, 2011).
However, the densities of Raccoon Dogs are not yet high in the North
Ostrobothnia region (Natural Resources Institute Finland, 2022), which
could partly explain the higher growth rates of Ortolan Bunting there.
Another, potentially also very damaging, predator is the feral cat which
probably has an equal effect in all regions. The impact of increasing
effectiveness of plant protectants (pesticides, herbicides, insecticides
etc.) on the breeding and survival of Ortolan Buntings also remains
unknown. Eng et al. (2019) studied the effect of neonicotinoids on
migrating White-crowned Sparrows. They found that ingestion of
imidacloprid by the birds during migratory stopover caused a rapid
reduction in food consumption, mass and fat, and delayed their
departure.

In summary, although our study did not directly investigate the
relationship between the level of intensity of agricultural practices
and the population growth rate of Ortolan Bunting, our results, however,
suggest a potential adverse impact of agricultural intensification on
the decline of this species.

\textbf{5. CONCLUSIONS AND CONSERVATION IMPLICATIONS}

Current conservation efforts in farmland areas seem to be ineffective in
mitigating the negative effects of agricultural intensification on bird
populations. Measures taken so far might simply be too light to
influence declining farmland birds. At present, it is often unclear
whether current conservation measures have beneficial impacts at all or
whether the measures are just inadequate, either at the local scale (too
narrow field margins for example) or at the wider scale in which they
are applied (too few farms applying the measures).

To conserve the Ortolan Bunting there clearly is a simultaneous need to
avoid abandonment of agricultural areas, and to promote
``de-intensification'' of agricultural practices. This general
recommendation would benefit also many other threatened farmland
species. However, in the case of this very rapidly declining species, it
is evident that more precise and finely targeted conservation actions
need to be taken urgently at the remaining and still (somewhat) viable
singing group locations.

Based on our results, we recommend applying conservation measures which
increase the diversity of crop types. Often a field with a greater
diversity of crop plant types also includes more bare ground as a result
of various plant structures and related managing practices.
Alternatively, if increasing diversity is not feasible, or additionally,
we recommend establishing non-crop growing stripes of ploughed bare
ground. We also recommend targeting these actions to populations living
in interconnected farmland landscapes and in northern parts of the
species' distribution range as it is more likely that these populations
act as sources, rather than sinks, of population growth.

In general, we agree with several researchers stating that we need more
multi-functional, mixed, agro-ecologically managed agricultural
landscapes that promote agricultural yield, biodiversity, and ecosystem
services to conserve biodiversity in farmlands (Baudron et al., 2019;
Tscharntke et al., 2012; Wilson et al., 1997).

\textbf{REFERENCES}

Aalto, J., Pirinen, P., Jylhä, K., 2016. New gridded daily climatology
of Finland: Permutation-based uncertainty estimates and temporal trends
in climate. J. Geophys. Res. Atmospheres 121, 3807--3823.
https://doi.org/10.1002/2015JD024651

Bárton, K., 2023. MuMIn: Multi-model inference. R-package version 1.47.5
{[}WWW Document{]}. URL https://cran.r-project.org/package=MuMIn
(accessed 11.3.23).

Baudron, F., Schultner, J., Duriaux, J.-Y., Gergel, S.E., Sunderland,
T., 2019. Agriculturally productive yet biodiverse: human benefits and
conservation values along a forest-agriculture gradient in Southern
Ethiopia. Landsc. Ecol. 34, 341--356.
https://doi.org/10.1007/s10980-019-00770-6

Berg, Å., 2008. Habitat selection and reproductive success of Ortolan
Buntings \emph{Emberiza hortulana} on farmland in central Sweden -- the
importance of habitat heterogeneity. Ibis 150, 565--573.
https://doi.org/10.1111/j.1474-919X.2008.00825.x

Brooks, M., E., Kristensen, K., van Benthem, K., J., Magnusson, A.,
Berg, C., W., Nielsen, A., Skaug, H., J., Mächler, M., Bolker, B., M.,
2017. glmmTMB Balances Speed and Flexibility Among Packages for
Zero-inflated Generalized Linear Mixed Modeling. R J. 9, 378.
https://doi.org/10.32614/RJ-2017-066

Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel
inference: a practical information-theoretic approach. Springer, New
York.

Burns, F., Eaton, M.A., Barlow, K.E., Beckmann, B.C., Brereton, T.,
Brooks, D.R., Brown, P.M.J., Fulaij, N.A., Gent, T., Henderson, I.,
Noble, D.G., Parsons, M., Powney, G.D., Roy, H.E., Stroh, P., Walker,
K., Wilkinson, J.W., Wotton, S.R., Gregory, R.D., 2016. Agricultural
Management and Climatic Change Are the Major Drivers of Biodiversity
Change in the UK. PLoS ONE 11, e0151595.
https://doi.org/10.1371/journal.pone.0151595

Cramp, S., Perrins, C.M., 1994. Handbook of the birds of Europe, the
Middle East and North Africa: the birds of the Western Palearctic. Vol.
9, Buntings and new world warblers. Oxford University Press, Oxford.

Dale, S., 2016. Cost of reproduction: a comparison of survival rates of
breeding and non-breeding male ortolan buntings. J. Avian Biol. 47,
583--588. https://doi.org/10.1111/jav.00898

Dale, S., 2011. Lifetime patterns of pairing success in male Ortolan
Buntings \emph{Emberiza hortulana} . Ibis 153, 573--580.
https://doi.org/10.1111/j.1474-919X.2011.01138.x

Dale, S., 2001. Female-biased dispersal, low female recruitment,
unpaired males, and the extinction of small and isolated bird
populations. Oikos 92, 344--356.
https://doi.org/10.1034/j.1600-0706.2001.920217.x

Dale, S., Christiansen, P., 2010. Individual flexibility in habitat
selection in the ortolan bunting \emph{Emberiza hortulana} . J. Avian
Biol. 41, 266--272. https://doi.org/10.1111/j.1600-048X.2009.04824.x

Dale, S., Olsen, B.F.G., 2002. Use of farmland by Ortolan Buntings
(\emph{Emberiza hortulana} ) nesting on a burned forest area. J. Für
Ornithol. 143, 133--144. https://doi.org/10.1007/BF02465445

Deutsch, M., 2007. Der Ortolan \emph{Emberiza hortulana} im Wendland
(Niedersachsen) -- Bestandszunahme durch Grünlandumbruch und
Melioration? Vogelwelt 105--115.

Eng, M.L., Stutchbury, B.J.M., Morrissey, C.A., 2019. A neonicotinoid
insecticide reduces fueling and delays migration in songbirds. Science
365, 1177--1180. https://doi.org/10.1126/science.aaw9419

Evans, K.L., 2004. The potential for interactions between predation and
habitat change to cause population declines of farmland birds. Ibis 146,
1--13. https://doi.org/10.1111/j.1474-919X.2004.00231.x

Finnish Environment Institute, 2023. Corine land cover.

Finnish Food Authority, 2023. Land parcel register.

Gamero, A., Brotons, L., Brunner, A., Foppen, R., Fornasari, L.,
Gregory, R.D., Herrando, S., Ho\selectlanguage{polish}ř\selectlanguage{ngerman}ák, D., Jiguet, F., Kmecl, P.,
Lehikoinen, A., Lindström, Å., Paquet, J.-Y., Reif, J., Sirkiä, P.M.,
\selectlanguage{polish}Š\selectlanguage{english}korpilov\selectlanguage{ngerman}á, J., van Strien, A., Szép, T., Telenský, T., Teufelbauer, N.,
Trautmann, S., van Turnhout, C.A.M., Vermouzek, Z., Vikstrøm, T.,
Vo\selectlanguage{polish}ř\selectlanguage{ngerman}í\selectlanguage{polish}š\selectlanguage{english}ek, P., 2017. Tracking Progress Toward EU Biodiversity Strategy
Targets: EU Policy Effects in Preserving its Common Farmland Birds.
Conserv. Lett. 10, 395--402. https://doi.org/10.1111/conl.12292

Gremion, J., Marcacci, G., Mazenauer, J., Sori, T., Kebede, F., Ewnetu,
M., Christe, P., Arlettaz, R., Jacot, A., 2022. Habitat preferences of
the Ortolan Bunting (\emph{Emberiza hortulana} ) in its prime wintering
grounds, the cereal-dominated Ethiopian Highlands. Ibis 164, 74--87.
https://doi.org/10.1111/ibi.12992

Gr\selectlanguage{ngerman}ützmann, J., Moritz, V., Südbeck, P., Wendt, D., 2002. Ortolan
(\emph{Emberiza hortulana} ) und Grauammer (Miliaria calandra) in
Niedersachsen: Brutvorkommen, Lebensräume, Rückgang und Schutz. Vogelkd.
Berichte Aus Niedersachs. 34, 69--90.

Hiironen, J., Ettanen, S., 2013. Peltoalueiden tilusrakenne ja sen
parantamismahdollisuudet (No. 113), Maanmittauslaitoksen julkaisuja.
National land survey of Finland.

Hyvärinen, E., Juslén, A., Kemppainen, E., Uddström, A., Liukko, U.-M.,
2019. The 2019 Red List of Finnish Species. Ympäristöministeriö \&
Suomen ympäristökeskus.

Jerrentrup, J.S., Dauber, J., Strohbach, M.W., Mecke, S., Mitschke, A.,
Ludwig, J., Klimek, S., 2017. Impact of recent changes in agricultural
land use on farmland bird trends. Agric. Ecosyst. Environ. 239,
334--341. https://doi.org/10.1016/j.agee.2017.01.041

Jiguet, F., Arlettaz, R., Bauer, H.-G., Belik, V., Copete, J.L., Couzi,
L., Czajkowski, M.A., Dale, S., Dombrovski, V., Elts, J., Ferrand, Y.,
Hargues, R., Kirwan, G.M., Minkevicius, S., Piha, M., Selstam, G.,
Skierczynski, M., Siblet, J.-P., Sokolov, A., 2016. An update of the
European breeding population sizes and trends of the Ortolan Bunting
(\emph{Emberiza hortulana} ). Ornis Fenn. 93, 186--196.

Jiguet, F., Robert, A., Lorrillière, R., Hobson, K.A., Kardynal, K.J.,
Arlettaz, R., Bairlein, F., Belik, V., Bernardy, P., Copete, J.L.,
Czajkowski, M.A., Dale, S., Dombrovski, V., Ducros, D., Efrat, R., Elts,
J., Ferrand, Y., Marja, R., Minkevicius, S., Olsson, P., Pérez, M.,
Piha, M., Rakovi\selectlanguage{polish}ć, \selectlanguage{english}M., Schmaljohann, H., Seimola, T., Selstam, G.,
Siblet, J.-P., Skierczy\selectlanguage{romanian}ǹski, M., Sokolov, A., Sondell, J., Moussy, C.,
2019. Unravelling migration connectivity reveals unsustainable hunting
of the declining ortolan bunting. Sci Adv 5, eaau2642.
https://doi.org/10.1126/sciadv.aau2642

Kauhala, K., Kowalczyk, R., 2011. Invasion of the raccoon
dog\emph{Nyctereutes procyonoides} in Europe: History of colonization,
features behind its success, and threats to native fauna. Curr. Zool.
57, 584--598. https://doi.org/10.1093/czoolo/57.5.584

Kleijn, D., Rundl\selectlanguage{ngerman}öf, M., Scheper, J., Smith, H.G., Tscharntke, T., 2011.
Does conservation on farmland contribute to halting the biodiversity
decline? Trends Ecol. Evol. 26, 474--481.
https://doi.org/10.1016/j.tree.2011.05.009

Krüger, H., Väänänen, V.-M., Holopainen, S., Nummi, P., 2018. The new
faces of nest predation in agricultural landscapes---a wildlife camera
survey with artificial nests. Eur. J. Wildl. Res. 64, 76.
https://doi.org/10.1007/s10344-018-1233-7

Leo, R., Romanenghi, G., Franchini, D., Gobbini, M., 2023. Spontaneous
renaturalization of open ecosystems in the hills of Brescia seen through
the bird community. Riv. Ital. Ornitol. 93.
https://doi.org/10.4081/rio.2023.667

Menz, M.H.M., Arlettaz, R., 2012. The precipitous decline of the ortolan
bunting \emph{Emberiza hortulana} : time to build on scientific evidence
to inform conservation management. Oryx 46, 122--129.
https://doi.org/10.1017/S0030605311000032

Morelli, F., 2012. Correlations between landscape features and crop type
and the occurrence of the Ortolan Bunting \emph{Emberiza hortulana} in
farmlands of Central Italy. Ornis Fenn. 89, 264--272.

Moussy, C., Arlettaz, R., Copete, J.L., Dale, S., Dombrovski, V., Elts,
J., Lorrillière, R., Marja, R., Pasquet, E., Piha, M., Seimola, T.,
Selstam, G., Jiguet, F., 2018. The genetic structure of the European
breeding populations of a declining farmland bird, the ortolan bunting
(\emph{Emberiza hortulana} ), reveals conservation priorities. Conserv.
Genet. 19, 909--922. https://doi.org/10.1007/s10592-018-1064-9

National Land Survey of Finland, 2023. Topographic Database.

Natural Resources Institute Finland, 2022. Game bag statistics.

Nousiainen, I., 2020. Sinne ja takaisin --- aikuisten
peltosirkkukoiraiden (\emph{Emberiza hortulana} Linnaeus, 1758)
elossasäilyvyys Suomessa vuosina 2013--2019 (PhD Thesis). University of
Helsinki.

Piha, M., Seimola, T., 2021. Bird of the year 2020: the Ortolan Bunting
- regional population estimates and trends. Linnut-Vuosik. 2020, 6--7.

Pons, P., Clavero, M., 2010. Bird responses to fire severity and time
since fire in managed mountain rangelands. Anim. Conserv. 13, 294--305.
https://doi.org/10.1111/j.1469-1795.2009.00337.x

R Core Team, 2023. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria.

Santana, J., Reino, L., Stoate, C., Moreira, F., Ribeiro, P.F., Santos,
J.L., Rotenberry, J.T., Beja, P., 2017. Combined effects of landscape
composition and heterogeneity on farmland avian diversity. Ecol. Evol.
7, 1212--1223. https://doi.org/10.1002/ece3.2693

Schaub, M., Martinez, N., Tagmann-Ioset, A., Weisshaupt, N., Maurer,
M.L., Reichlin, T.S., Abadi, F., Zbinden, N., Jenni, L., Arlettaz, R.,
2010. Patches of Bare Ground as a Staple Commodity for Declining
Ground-Foraging Insectivorous Farmland Birds. PLOS ONE 5, e13115.
https://doi.org/10.1371/journal.pone.0013115

Schifferli, L., 2001. Birds Breeding in a Changing Farmland. Acta
Ornithol. 36, 35--51. https://doi.org/10.3161/068.036.0112

Storch, D., Konvicka, M., Benes, J., Martinková, J., Gaston, K.J., 2003.
Distribution patterns in butterflies and birds of the Czech Republic:
separating effects of habitat and geographical position. J. Biogeogr.
30, 1195--1205. https://doi.org/10.1046/j.1365-2699.2003.00917.x

Tiainen, J., Pakkala, T., Piiroinen, J., Vickholm, M., Virolainen, E.,
1985. The changes in the farmland bird community of the municipality of
Lammi, southern Finland, during the last five decades. Lintumies 20,
30--42.

Tryjanowski, P., Hartel, T., Báldi, A., Szyma\selectlanguage{polish}ń\selectlanguage{english}ski, P., Tobolka, M.,
Herzon, I., Go\selectlanguage{polish}ł\selectlanguage{english}awski, A., Konvi\selectlanguage{polish}č\selectlanguage{english}ka, M., Hromada, M., Jerzak, L., Kujawa,
K., Lenda, M., Or\selectlanguage{polish}ł\selectlanguage{english}owski, G., Panek, M., Sk\selectlanguage{ngerman}órka, P., Sparks, T.H.,
Tworek, S., Wuczy\selectlanguage{polish}ń\selectlanguage{english}ski, A., \selectlanguage{polish}Ż\selectlanguage{english}mihorski, M., 2011. Conservation of Farmland
Birds Faces Different Challenges in Western and Central-Eastern Europe.
Acta Ornithol. 46, 1--12. https://doi.org/10.3161/000164511X589857

Tscharntke, T., Clough, Y., Wanger, T.C., Jackson, L., Motzke, I.,
Perfecto, I., Vandermeer, J., Whitbread, A., 2012. Global food security,
biodiversity conservation and the future of agricultural
intensification. Biol. Conserv. 151, 53--59.
https://doi.org/10.1016/j.biocon.2012.01.068

V\selectlanguage{ngerman}äisänen, R.A., Lehikoinen, A., 2013. Suomen maalinnuston pesimäkannan
vaihtelut vuosina 1975--2012. Linnut-Vuosik. 2012, 62--81.

Vepsäläinen, V., Pakkala, T., Piha, M., Tiainen, J., 2007. The
importance of breeding groups for territory occupancy in a declining
population of a farmland passerine bird. Ann. Zool. Fenn. 44, 8--19.

Vepsäläinen, V., Pakkala, T., Piha, M., Tiainen, J., 2005. Population
crash of the ortolan bunting \emph{Emberiza hortulana} in agricultural
landscapes of southern Finland. Ann. Zool. Fenn. 42, 91--107.

Wilson, J.D., Evans, J., Browne, S.J., King, J.R., 1997. Territory
Distribution and Breeding Success of Skylarks Alauda arvensis on Organic
and Intensive Farmland in Southern England. J. Appl. Ecol. 34,
1462--1478. https://doi.org/10.2307/2405262

Wretenberg, J., Lindström, Å., Svensson, S., Thierfelder, T., Pärt, T.,
2006. Population Trends of Farmland Birds in Sweden and England: Similar
Trends but Different Patterns of Agricultural Intensification. J. Appl.
Ecol. 43, 1110--1120. https://doi.org/10.1111/j.1365-2664.2006.01216.x



\textbf{FIGURES AND TABLES}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} Map showing the centroid coordinates of each Ortolan
Bunting singing group (black circles) which had been visited in at least
one pair of consecutive years between 2000 and 2018, so that at least
one male territory was observed (\emph{n} = 238) in the first of those
surveys. Singing groups were classified into seven major regions
indicated with black line. Discarded singing groups (\emph{n} = 41), not
fulfilling these criteria, are indicated by triangles.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2.} Map depicting separate Ortolan Bunting singing groups
which are formed by aggregating close-by territories (observations of
individual singing males, black triangles). Singing groups are
delineated by a black line representing the range occupied by that
singing group. Singing group range centroid is indicated by a black
circle.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3} . Model predictions of multiplicative population
growth rate of Ortolan Bunting in different regions of the species range
in Finland. Model prediction point estimates are shown with black
circles together with their 95 \% confidence intervals error bars.
Violin plots and scattered circles illustrate the distribution of
singing group growth rates averaged over time. These averaged data were
generated by first adding 0.5 to the territory count, both the current
and previous year (TERRI and TERPRE), and then aggregating the data by
singing group and counting the average change in population growth rate
per singing group. The intensity of the colour of the circle indicates
how many times that singing group was visited on consecutive years,
i.e., how many observations were available for estimating the growth
rate for that singing group (\emph{n} = 1--13, mean = 2.8).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4.} Plot illustrating the predicted effect of the crop
plant type diversity (SHANG), the proportion of farmland surrounding the
singing group (AGRI5) and the proportion of bare ground within the
singing group's range (BARE) on the population growth rate of Ortolan
Bunting. The black thick line represents the conditional prediction for
Uusimaa region, with a 95 \% confidence interval around it (grey area),
when TERPRE is kept constant at 1. Scattered circles illustrate the
distribution of singing group growth rates averaged over time. This
averaged data was generated by first adding 0.5 to the territory count,
both the current and previous year (TERRI and TERPRE), and then
aggregating the data by singing group and counting the average change in
population growth rate and the average for each of the three
environmental variables. The intensity of the colour of the circle
indicates how many times that singing group was visited on consecutive
years, i.e., how many observations were available for estimating the
growth rate for that singing group (\emph{n} = 1--13, mean = 2.8).

\textbf{Table 1.} Ranking of AIC\textsubscript{c} values of 16 competing
models, with different sets of explanatory variables for the
multiplicative population growth between two consecutive years. The
models build on a null model with log link function and COM-Poisson
error, where the number of territories is (technically) the response
variable, explained with region and an offset variable, which is the
natural logarithm of the number of territories previous year (i.e.,
R-syntax for the formula: TERRI \textasciitilde{} 0 + region +
offset(log(TERPRE))). The column ``Additional explanatory variables''
describes which other fixed effects variables are included. ``K'' is the
number of estimated parameters, ``logLik'' the log-likelihood,
``AIC\textsubscript{c}'' the Akaike information criterion corrected for
small sample size, ``\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c}'' the difference in
AIC\textsubscript{c} compared with the most parsimonious model, and
``w'' is the Akaike weight.\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
Additional explanatory variables & K & logLik & AICc &
\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c} & w\tabularnewline
\midrule
\endhead
AGRI5 + SHANG + BARE & 11 & --1,354.50 & 2,731.40 & 0.00 &
0.27\tabularnewline
SHANG + BARE & 10 & --1,355.88 & 2,732.08 & 0.68 & 0.19\tabularnewline
AGRI5 & 9 & --1,357.03 & 2,732.32 & 0.92 & 0.17\tabularnewline
none & 8 & --1,358.39 & 2,732.99 & 1.59 & 0.12\tabularnewline
AGRI5 + SHANG + BARE + TEMP + PREC & 13 & --1,353.99 & 2,734.52 & 3.12 &
0.06\tabularnewline
SHANG + BARE + TEMP + PREC & 12 & --1,355.38 & 2,735.24 & 3.83 &
0.04\tabularnewline
AGRI5 + TEMP + PREC & 11 & --1,356.47 & 2,735.34 & 3.93 &
0.04\tabularnewline
TEMP + PREC & 10 & --1,357.84 & 2,736.01 & 4.61 & 0.03\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + AGRI5 + SHANG + BARE & 15 &
--1,352.93 & 2,736.59 & 5.19 & 0.02\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + SHANG + BARE & 14 & --1,354.09 &
2,736.81 & 5.41 & 0.02\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + SHANG + BARE & 14 & --1,354.09 &
2,736.81 & 5.41 & 0.02\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER & 12 & --1,356.75 & 2,737.98 & 6.57 &
0.01\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + AGRI5 + SHANG + BARE + TEMP + PREC &
17 & --1,352.46 & 2,739.85 & 8.45 & 0.00\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + SHANG + BARE + TEMP + PREC & 16 &
--1,353.64 & 2,740.11 & 8.71 & 0.00\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + AGRI5 + TEMP + PREC & 15 &
--1,355.08 & 2,740.88 & 9.48 & 0.00\tabularnewline
ABUILD + AROAD + ASTREAM + ARIVER + TEMP + PREC & 14 & --1,356.23 &
2,741.10 & 9.70 & 0.00\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2.} A summary table including parameter estimates for the
best fitting model used to explain factors contributing to the
multiplicative population growth rate of Ortolan Buntings.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Explanatory variable & Estimate & SE & 95 \% CI\tabularnewline
\midrule
\endhead
region North Ostrobothnia & 0.05 & 0.11 & {[}--0.17,
0.27{]}\tabularnewline
region Central Finland & --0.11 & 0.43 & {[}--0.96,
0.74{]}\tabularnewline
region North Carelia & --0.32 & 0.54 & {[}--1.37, 0.74{]}\tabularnewline
region South Ostrobothnia & --0.35 & 0.11 & {[}--0.57,
--0.13{]}\tabularnewline
region South-West Finland & --0.27 & 0.05 & {[}--0.37,
--0.17{]}\tabularnewline
region Tavastia & --0.34 & 0.11 & {[}--0.56, --0.12{]}\tabularnewline
region Uusimaa & --0.12 & 0.03 & {[}--0.18, --0.07{]}\tabularnewline
AGRI5 & 0.05 & 0.03 & {[}--0.01, 0.10{]}\tabularnewline
SHANG & 0.05 & 0.03 & {[}0.00, 0.11{]}\tabularnewline
BARE & 0.04 & 0.03 & {[}--0.01, 0.09{]}\tabularnewline
Dispersion parameter & 1.50 & &\tabularnewline
\bottomrule
\end{longtable}

\selectlanguage{english}
\FloatBarrier
\end{document}

