Convocatorias 2016
Proyectos RETOS
Dirección General de Investigación
Científica y Técnica
Subdirección General de Proyectos de
Investigación
INVESTIGADOR PRINCIPAL: Luis E. Santamaría Galdón
TÍTULO DEL PROYECTO: Desarrollo de sistemas sostenibles de producción
ganadera en espacios protegidos con alta variabilidad interanual en la
producción primaria: vacas, caballos y ciervos en el E.N. Doñana
ACRÓNIMO: GRAZE
RESUMEN:
En áreas mediterráneas y semiáridas, la elevada incertidumbre en
el régimen de precipitaciones y la productividad vegetal asociada represent un
importante reto para el desarrollo y optimización de sistemas sostenibles de
producción ganadera extensiva, particularmente en áreas con alta abundancia de
ungulados silvestres. Este proyecto está
enfocado endesarrollar criterios a largo plazo y herramientas de modelado para
la gestión sostenible de ganadería extensiva en áreas protegidas mediterráneas
con alta variabilidad climática, centrándose en el Espacio Natural Doñana (END)
como caso de estudio. Para ello, propone desarrollar un programa
interdisciplinar que combina: (1) La obtención de estimas históricas y actuales
del tamaño poblacional, uso del espacio y requerimientos alimenticios de los
cinco ungulados presentes en el END (silvestres: gamos, ciervos y jabalíes;
domésticos: vacas y caballos). (2) Estimas históricas y actuales del efecto del
nivel de precipotación y la presión de herbivoría sobre la producción de
biomasa aérea de la vegetación de Doñana, basadas en una combinación de prospecciones
de campo, experimentos y modelos de teledetección. (3) El desarrollo de modelos
dinámicos y espacialmente explícitos de la relación entre precipitación,
presión de herbivoría y producción de biomasa vegetal en el END, y su
utilización para generar y evaluar diferentes escenarios de gestión en las
condidiones climáticas actuales y aquellas previstas en los diferentes
escenarios de cambio climático. El resultado esperado es el desarrollo de una
base de conocimiento, de criterios a largo plazo y de herramientas de modelado
para la gestión sostenible de la ganadería extensiva en Doñana y en otras áreas
protegidas de la región mediterránea.
C.1.
PROPUESTA CIENTÍFICA
Introduction
Free-ranging livestock production is a
widespread exploitation system in many areas of the world (Launchbaugh & Howery 2005), including the Iberian Peninsula. The high
conservation of many of these areas has resulted in their inclusion within
conservation areas, where human exploitation systems are then requested to meet
the societal demand of nature conservation. In many of these areas, often as a
result of the management changes associated to its new status (e.g. hunting
reduction or elimination, access restrictions to the local population), two
conflicting trends arise: livestock must coexist with increasingly large
numbers of wild ungulates, and local stakeholders may increase their demand for
higher livestock stocking rates for a diversity of reasons (e.g. increasing
economic gain, compensating the loss of other sources of income and/or gaining
access to the conservation site) (Weisberg et al. 2002). The resulting
management conflict often result in local or widespread overgrazing, reducing
plant productivity and thus affecting both livestock production and nature
conservation (Vavra et al. 1999) – and may develop into open social conflicts (Gómez-Baggethun et al. 2013,
Bejarano-Bella & Torres Rodríguez 2016). Unfortunately, these effects often reflect a lack of adequate
knowledge or understanding of the factors driving to effects of livestock on
biodiversity (Lunt et al. 2007).
In strongly seasonal areas, such as the
Mediterranean region, this problem may be exacerbated by the perceptual and
management constraints imposed by the large seasonal and inter-annual
fluctuations in rainfall, which results in large changes in plant productivity
across years (e.g. Lázaro et al. 2001). In such situations, planning the
stocking rates and management regime becomes increasingly harder owing to the
amplification of effects of environmental unpredictability by the strong
feedbacks between plant standing crop and regrowth potential (which amplifies
the impact of grazing on plant growth) (e.g. Naveh 1982). In dry years,
overgrazing exhausts the asexual organs and depletes the seed bank of the
vegetation, thus reducing its productivity during the wet years that follow.
And, while wild ungulates may even have positive effects of livestock during
wet years (Odadi et al. 2011), the increases in population numbers of wild
ungulates and/or in the stocking rates of livestock following (sequences of)
wet years may also increase the likelihood of overgrazing in the dry years that
follow. In all these cases, food limitation during periods of low productivity
requires the assumption of additional expenses by livestock breeders (who must
stock food to free-ranging animals or transport them to pens during such
period) and/or may entail levels of ecosystem degradation that may be
unacceptable in conservation areas.
The solution to this dilemma is complex, since
it involves the use of very conservative stocking rates (low enough to prevent
overgrazing in dry years) or to develop systems allowing for a dynamic
adjustment of stocking rates and/or space use by livestock in response to
rainfall levels (Graham et al. 2010, Weisberg et al. 2002). In such case, early
detection of expected plant production levels based on combined records of
rainfall levels and cumulative grazing pressure may represent a highly valuable
tool, allowing for the adjustment of grazing rates before reaching levels
conductive to the long-term degradation of plant production (Rowntree et al. 2004). The
development of such tools is all the more valuable because climate change is
expected to result in an amplification of the hydrological cycle, with more
extreme intra-annual precipitation regimes characterized by larger rainfall
events and longer intervals between events (e.g. Knapp et al. 2008) – thus resulting in an amplification of the processes
described above.
The processes described above may however
be buffered by landscape heterogeneity, particular when it is related to water
storage and availability (due e.g. to changes in topography and soil types). In
such cases, lowland areas may provide areas with high plant productivity in dry
years; and these areas will be more resilient to overgrazing because they not
accessible to herbivores (due to prolonged flooding) in wet years. This
mechanism, which fits our preliminary observations in the Doñana marshes (the
study system proposed for this project, see below) and was reflected
traditional management method in the area (Gómez-Baggethun et al. 2012), may provide additional opportunities for the
sustainable management of free-ranging livestock in conservation areas where
wild ungulates are also present, through the wise adjustment of the stocking
rates and space use by such herbivores to the rainfall levels of the current
and previous years (Gómez-Baggethun et al. 2013).
Study system
The project will take place at the Doñana
Protected Area (Espacio Natural Doñana, END hereafter), a nature reserve
(including a National Park and several areas of Natural park) located on the
Atlantic coast of South-West Spain. The region has a Mediterranean climate,
classified as dry sub-humid with marked seasons. Grazing by domestic and wild
ungulates varies along the different seasons, following changes in plant
productivity and accessibility at the different landscape units (Barasona et
al. 2014). In the wet season (December–May), marshlands are flooded and ungulates
graze in the sandy shrublands. As the dry season progresses and shrubland
vegetation senesces, ungulates start grazing in the marshland (where either
bulrushes, notably of Scirpus maritimus, or saltworts, gen. Sarcocornia, Arthrocnemum and
Suaeda, tend to be the dominant vegetation). Ungulates become most
food limited during summer (June–September), when wetlands dry up causing
senescence of their herbaceous vegetation. The humid ecotone between the
shrubland and the marshland (locally known as “vera”) remains humid throughout
the year. Therefore its vegetation, dominated by herbaceous meadows (Galiopalustris
sp. with Juncus maritimus associations), represent a key food
supply for ungulates during such season.
The study area has moderate to high densities
of red deer, fallow deer and wild boar. A traditional breed of cattle (locally
called “marismeña”) is farmed within five cattle management areas in the END:
Coto del Rey (CR), the northernmost area, contains no cattle husbandry; three
areas in the center: SO (n = 350 cattle; density = 5.7 cattle/km2),
BR (n = 168
cattle; density = 2.6 cattle/km2), and PU (n = 152
cattle; density =4.0 cattle/km2); and Marismillas (MA), the
southern-most area (n = 318 cattle; density = 3.1 cattle/km2)
(Barasona et al. 2014). Each cattle management area is surrounded by a
cattle-proof fence, which limits the movements of each herd to within their
designated management area. However, social groups (overwhelmingly females)
showing individual ranging behaviour may be differentiated within each cattle
management area (Lazo 1995).
Previous results of the research team and other
national and international teams
This project builds on the synergies of
the different research interests of the members of the work team and, while
providing a step further in their own research lines, creates the opportunity
of achieving an enriching synthesis of their present and previous work. The
project aims indeed at combining the expertise of all these researchers in a
collaborative and truly inter-disciplinary effort, with the purpose of
addressing the interweaving factors and mechanisms that make-up the complexity
of plant-herbivore interactions in a coherent and comparative manner, rather
than dissecting and addressing them using piecemeal approaches. At the same
time, it aims at providing knowledge and specific tools of direct practical use
for the sustainable management of domestic livestock and wild ungulates in
Mediterranean ecosystems, typically subjected to high inter-annual variation in
key determinants of plant productivity (most notably, rainfall), which should
be directly applicable to the case study (the Doñana Protected Area) and
hopefully easy to extrapolate to other areas of similar climate and conditions.
Luis SANTAMARIA, a tenured researcher
(Científico Titular) who leads the Spatial Ecology Group at the Doñana
Biological Station (EBD-CSIC), has a extensive experience in the main topics
addressed in this study, including (i) the ecology, evolution and management of
plants and herbivores (e.g. Jonzen et al. 2002, Latorre et al. 2013, Santamaría
2002, Santamaría & Rodríguez-Gironés 2002, Santamaría et al. 2007), (ii)
the ecology of the Doñana marshes and its vegetation (Santamaría et al. 1996,
Santamaría et al. 2005, Santamaría & Amézaga 1999), (iii) the development
of spatially-explicit models and its application to the management of
conservation areas (e.g. Magrach et al. 2011, Rodríguez-Pérez et al. 2012), and
(iv) the collaborative development of management plans and policies (e.g.
Méndez et al. 2012, Santamaría & Méndez 2012, Santamaría et al. 2013).
During such work, we successfully used all the techniques proposed in this
project, such as surveying animal populations, tracking and modelling animal
movement, surveting the composition and biomass yield of plant populations,
applying remote-sensing techniques to habitat characterization and modelling,
developing spatially-explicit models, and conducting collaborative workshops to
Luis Santamaría’s expertise will be
complemented by the extensive knowledge of the work team, which includesRicardo
DÍAZ-DELGADO, a tenured technician at EBD-CSIC who has an extensive experience
in remote-sensing and GIS analysis of Doñana’s landscape and vegetation
structure, as well as in the development of long-term monitoring programs (he
is the Spanish representative at the International Long-Term Ecological
Research network, ILTER). Francisco CARRO, a tenured technician at EBD-CSIC who
has an extensive experience in monitoring wildlife mammals, including
ungulates, at the Doñana region (he is the coordinator of the mammal monitoring
program at EBD). Cristina PÉREZ, who has ample experience in the analysis of
vegetation and herbivore-dropping samples.
Plant-ungulate interactions and, more broadly, plant and ungulate
ecology are very wide disciplines with many different teams working on very
different model organisms around the world. At international level, a few
examples of leading research teams include those led by Marcelo Sternberg (Tel Aviv University), Peter Weisberg (University of Nevada), Mark Hebblewhite (University
of Montana) and Philippe Ballon (IRSTEA, Antony, France), as
well as interdisciplinary groups such as the Ungulate Ecology Group (CEES Norway). At national level, some of the leading research teams
include those led by Juan Carranza (Universidad de Córdoba) and J. Vicente
(IREC).
Purpose and opportunity of the
Project
Finalidad del proyecto,
oportunidad de llevarlo a cabo y adecuación del mismo a la Estrategia Española
de Ciencia y Tecnología y de Innovación y, en su caso, a Horizonte 2020 o a
cualquier otra estrategia nacional o internacional de I+D+i.
The develoment of sustainable livestock production systems is one
of the key elements of Challenge 2 of the Spanish Strategy of Science and
Technology (Reto 2: Seguridad y calidad alimentaria; actividad agrarian
productive y sostenible, sostenibilidad de los recursos naturales,
investigación marina y marítima), which explicitly mentiones the need to
improve the competitiveness of the food-production sectors while improving the
management of natural resources and (“…
la competitividad de los sectores agroalimentario, forestal y pesquero en los
mercados nacionales e internacionales, …, mejorando la gestión de los recursos
naturales utiliz ados por los distintos sectores productivos… [y] avanzar en la
conservación de los recursos naturales, en particular en el uso eficiente del
agua, … la lucha contra la erosión de los suelos, …, la protección de nuestros
sistemas agroecológicos, su biodiversidad…”). More specifically, the Priorities set with Challenge 2
include explicitly the sustainable improvement of livestock production systems,
including the improvement of its productive efficiency, the reduction and
improvement of the intakes and the environmental and social valuation and
modeling of agro-forestal systems (Prioridad II. Mejora
sostenible de los sistemas de agrícolas, ganaderos y forestales: (i) eficiencia
productiva … en especies agrícolas, ganaderas y forestales, promoviendo … el
desarrollo y mejora de la eficiencia de los insumos; […] (iv) sistemas de
producción animal y vegetal, incluyendo insumos, maquinaria, tecnologías y
sistemas; […] (vi) valoración y modelización económica, ambiental y social de
los sistemas agroforestales.”)
Similarly, the economic and
environmental importance of sustainable food production systems, including the
sustainable production of terrestrial livestock, is explicitly mentioned in
Horizon 2020 Societal Challenge 2 on “Food security, sustainable agriculture,
marine and maritime research and the bioeconomy”. Indeed, previous H2020 calls
within this program have topics such as “Sustainable terrestrial livestock
production”, framed within the more general topic “Sustainable food production
systems”. Several parts of these documents and calls have stressed the
importance of improving sustainability and productivity of terrestrial
livestock systems, particularly in the face of global change, which is likely
to increase the environmental footprint of such system. This project fits
perfectly within such goal, by aiming to provide tools and criteria for the
development of sustainable livestock production in systems where free ranging
cattle and horses feeding on natural vegetation and share such food resources
with wild ungulates – in particularly, at natural protected areas where such
production must be harmonized with the need to protect highly-valued
biodiversity and ecosystem services. Its focus, aim and interdisciplinary
approach will contribute to meet the main objectives of the Programme, such as
“test, demonstrate and transfer effective solutions to major challenges
affecting the Bioeconomy on land and sea, across the agri-food chain from soil
to society”, “unlock the potentials of
available bio-resources in the different bioeconomy and blue-economy sectors in
a sustainable and socially responsible way”, and “bringing Research and
Innovation at the heart of major primary sectors … taking advantage of new
potential in the biological, ecological, technical and information technology
domains”.
Hypothesis
This project builds on the hypothesis that
in Mediterranean and semiarid areas, large uncertainty in rainfall levels and
the associated levels of plant primary production represents a strong
contstrain for the optimal, sustainable and environmentally-responsible
management of free-ranging livestock production, particularly for conservation
areas such as the Doñana National Park. Overgrazing during dry years exhaust
the asexual organs and depletes the seed bank of the vegetation, thus reducing
its productivity during wet years; while the increases in population numbers of
wild ungulates and/or stocking rates of livestock following (sequences of) wet
years increases the likelihood of overgrazing when they are followed by dry
years.
As a secondary hypothesis, we will
evaluate whether landscape heterogeneity related to water storage and
availability (due e.g. to changes in topography and soil types) may mitigate
these effects by providing areas with high plant productivity in dry years,
which are not accessible to herbivores (due to prolonged flooding) in wet
years. This hypothesis fits our preliminary observations in the Doñana marshes.
Main Goal
The project aims at developing long-term
criteria and modelling tools for the management of free-ranging livestock in
Mediterranean protected areas with high climatic variability, taking the Doñana
Protected Area (Espacio Natural Doñana, END) as a case study.
Specific Goals
1.
Estimate the population size and feeding
demands of the five ungulates feeding in Doñana (wild: red deer, fallow deer,
wild boar; domestic: cattle, horse).
2.
Estimate the effects of rainfall level and
grazing pressure on the productivity and standing crop of the vegetation of
Doñana.
3.
Reconstruct the long-term changes in
productivity and biomass yield of the Doñana vegetation, using remote-sensing
tools.
4.
Develop models of the relationship between
rainfall, grazing pressure and plant standing crop at the END, and use them to
evaluate different management scenarios under current and forecasted climate
conditions.
Infrastructure y equipment available for the project
Infrastructure
The centers and laboratories to which the
members of the research team belong are equipped with all the equipment and
material necessary for the development of the project (with the exception of
the items included in the budget). The EBD-CSIC counts with basic lab equipment
such as precision scales, digital calipers, fridges and freezers, stereoscopes
and (visual and epifluoresce) microscopes, binoculars and telescopes, manual
and digital refractometers, together with climatic and germination chambers, greenhouse
facilities and animal experimentation facilities. EBD’s Service Units include
fully-equipped Animal Physiology Lab, Molecular Ecology Lab and Aquatic Ecology
Lab.
Use of ICTS-Doñana
The Doñana Scientific Reserve (RBD) is a
Singular Research Infrastructure (ICTS)
belonging to CSIC, which depends
administratively from ERBD-CSIC. It extends over
10,000 ha within the 50,000 ha of the Doñana
National Park and offers a complete infraestructure for research purposes.
Around almost a third of our project will be developed in RBD. While we cannot
apply for access to ICTS-RBD because we are staff of EBD (our travel and living
costs will be funded from the current proposal), we will benefit from the use
of its facilities during the extensive field work planned in Doñana. During the
field campaigns there, the researchers have access to the field Wi-Fi network
(allowing them to connect their devices, e.g. data-loggers), field
transportation (4x4 vehicles), use of field laboratories and housing.
Methodology
Ob.1. Estimate the population size and
feeding demands of the five main herbivores feeding in the Doñana marshes
(wild: red deer, fallow deer, wild boar, hare and rabbit; domestic: cattle,
horse, sheep)
Task 1.1. Historical data on herbivore abundance and population
structure
- Achievement H1: Assessment of historical changes in ungulate abundance
completed (data collection and statistical tests).
- Deliverable E1: Scientific Article (together with Task 1.2. and 1.3.).
The population size (number of
individuals) and population characteristics (sex, age class) of the six main
herbivores present at the END have been registered in a number of management,
monitoring and research surveys since the early 80’s. To our knowledge,
however, they have not been gathered systematically and subjected to
comparative analysis. In this WP we will gather all the available information
from published and unpublished, scientific and technical sources (e.g. National
Park and END management plans; RBD-ICTS monitoring program; Soriguer 1981,
1983, 1988; Lazo et al. 1991; Delibes &Soriguer 1993; Soriguer et al. 1994,
2001) and use them to reconstruct the long-term changes in their abundance.
Inasmuch as the available data allow for
it, we will also develop simple demographic models to evaluate the effect of
historical changes on resource availability (estimated using remote sensing,
see below), inter-specific competition (within the herbivore’s guild) and
management measures (e.g. culling of fallow deer, reductions and increases in
the stock of domestic herbivores) on the survival, recruitment and population
size of the different species.
Task 1.2. Spatial distribution and individual movements
- Achievement H2: Assessment of spatial variation in ungulate abundance,
in relation to the availability and exploitation of food resources, completed
(data collection and statistical tests).
- Deliverable E1: Scientific Article (together with Task 1.1. and 1.3.).
Previous studies have shown that the
distribution of herbivores is not homogeneous across the Doñana Nature Reserve
(END). The abundance of cattle and horse varies largely among the different
management areas, which are separated by fences for the purpose of livestock
management (see above). Wild ungulates, though generally able to cross such
fences, also show large differences in abundance across states. As these
studies acknowledge, the extent to which these differences (which are based on
one to three censuses a year, plus trimestral surveys of droppings for a
certain states and years) adequately reflect seasonal and diel changes in space
and habitat use remains unknown. Some of these changes are strong determinants
of the spatial gradients in grazing pressure, e.g. in the marsh area, where
grazing progresses from shallower to deeper areas as the inundation recedes
along the spring. Such knowledge is therefore essential to evaluate the extent
to which herbivores compete for their food sources and/or they have synergic or
merely additive impacts on their food plants.
To evaluate the importance of temporal and
spatial variation in the local abundance (space use) by the different herbivore
species, we will work at four different spatio-temporal scales:
1.2.1. We will analyze the data available
from the monitoring of four species of wild ungulates (red deer, fallow deer
and wild boar) by the RBD-ICTS. These data consist of direct counts on 8
transects of approx. 15 km, recorded three times a year since 2005, and provide
density estimates (#individuals/km) based on the adjustment of detectability
curves (distance sampling).
1.2.2. We will complement these
observations with the analysis of yearly counts of droppings (fecal items) at
24 transects placed next to the 24 herbivore exclusions installed at all main
vegetation types of the END between 1992 and 2000 (17 of them in 1992-3), and
monitored every spring and summer-autumn since their installation by the team
led by R. Soriguer (who will collaborate actively in their analysis; see below
for details). Each year, observers counted (and removed) the droppings present
along 200x1 m transects, separately for each ungulate species, at the end of
the growth season (September-October).
|
Table 1: Location and characteristics of the
herbivore-exclusion plots (and associated control plots) for which long-time
series of plant standing crop are available to be used in the analyses of
Tasks 1.2.2. and 2.1.1.
|
|||
|
Name
|
Locality
|
Position (GPS)
|
Dominant species
|
|
C_BOLIN
|
Bolin
|
N36.99390 W6.44241
|
Herbaceous meadow (vera)
|
|
C_CHOZA ALMAJAL
|
Choza Pelitos
|
N37.07739 W6.39863
|
Saltworts
|
|
C_COMPTA
|
Compuertas
|
N36.91508 W6.29282
|
Saltworts
|
|
C_CORNEJO
|
Pozo Cornejo
|
N37.06459 W6.43063
|
Saltmarsh bulrush (S. maritimus)
|
|
C_ESQUINA
|
Esquina Noguera
|
N37.04060 W6.42241
|
Saltmarsh bulrush (S. maritimus)
|
|
C_JUNQUILLO
|
Junquillo
|
N36.98377 W6.39683
|
Somerset rush (Juncus
subulatus)
|
|
C_LEO_ALMAJ
|
Leo Biaggi - almajal
|
N36.97566 W6.32183
|
Saltworts + Somerset rush
|
|
C_LEO_CAÑO
|
Leo Biaggi - caño
|
N36.97586 W6.32304
|
Bulrush (S.
litoralis)
|
|
C_LR_ALMAJAL
|
Lucio del Rey - almajal
|
N36.91980 W6.34959
|
Saltworts
|
|
C_LR-L
|
Lucio del Rey - lucio
|
N36.92227 W6.34745
|
Saltworts
|
|
C_MATIAS
|
Casa Matias
|
N37.01424 W6.32215
|
Saltworts
|
|
C_MILLAN
|
Millan
|
N37.01911 W6.36498
|
Bulrush (S. litoralis)
|
|
C_MTZ_CANCELA
|
Cancela de Martinazo
|
N37.02831 W6.42930
|
Saltmarsh bulrush (S. maritimus)
|
|
C_MZO
|
Martinazo (viejo)
|
N37.03292 W6.43764
|
VERA
|
|
C_OJILLO
|
Ojillo
|
N37.00583 W6.50785
|
LAGUNA
|
|
C_PACIL
|
Pacil
|
N37.03013 W6.43298
|
PACIL
|
|
C_POZO_ALM
|
Pozo Almajal
|
N37.00765 W6.32695
|
Saltworts
|
|
C_RESOLIMAN
|
Resoliman
|
N37.07502 W6.43317
|
Saltmarsh
bulrush (S. maritimus) + spikerush
(Eleocharis spp.)
|
|
C_STA_OLALLA
|
Santa Olalla
|
N36.98216 W6.47814
|
Meadow (sandy
shore of a large pond)
|
|
C_TRAVIESO
|
Caño Travieso
|
N37.00620 W6.31065
|
Somerset rush (Juncus subulatus) + saltworts
|
|
C_VETA
|
Veta del Palacio
|
N36.99211 W6.43368
|
Grassland (“veta”)
|
|
C_VETA_CARRIZOSA
|
Veta Carrizosa
|
N36.97950 W6.40672
|
Grassland (“veta”)
|
|
C_VETA_MARISMA
|
Veta Marisma
|
N36.99299 W6.43445
|
Saltmarsh
bulrush (S. maritimus)
|
|
C_ZORRABARBAS
|
Zorrabarbas
|
N37.08515 W6.43321
|
Saltmarsh
bulrush (S. maritimus) + spikerush
(Eleocharis spp.)
|
1.2.3. To be able to refer these data to
actual grazing pressure by the different herbivores, we will combine trimestral
counts of droppings at the same transect with camera-trap photographs taken, at
hourly intervals, at marked areas of vegetation placed next to such transects
(see Table 1). Droppings will be collected to obtain deposition rates per
interval and for fecal analysis (see Task 1.3.2.). Besides providing a
calibration of the relation between dropping density and grazing pressure, data
from camera traps will provide information on temporal (seasonal and diel)
changes in such grazing pressure.
1.2.4. To obtain data on the spatial scale
at which ungulates (from the five main species present at EBD: cattle, horse,
red deer, fallow deer and wild boar) are exploiting the available plant
resources, as well as the extent to which they are able to complement the
availability of food items at different sites (different states within the EBD,
and different areas within each state), we will analyze the movements of 10-20
individuals from each species using GPS trackers. Whenever possible, we will
select individuals belonging to different social groups, so that their
movements can be taken to represent that of the whole group (e.g. for cattle;
Lazo 1995). Part of these data will be provided by R. Soriguer (EBD-CSIC) and
J. Vicente (IREC-CSIC), who collected them in the course of previous projects
focused on different aspect of the eco-epidemiology of tuberculosis (e.g.
cattle and wild boar, in Barasona et al. 2014), thus expanding the time span
and reducing the equipment costs of the current project. GPS collars will be
installed within the first semester of the project, allowing for a tracking
period of at least two years (though it will hopefully extent beyond such
duration). Building on the availability of detailed (abiotic and biotic)
environmental information from Doñana’s monitoring program (RBD-ICTS), data
will be analyzed using the environmental-data automated track annotation
(Env-DATA) system, which provides an easy-to-use platform for data acquisition,
data transformation and integration, resampling, and interpolation (Dodge et
al. 2013) that facilitates a comprehensive assessment of the basic question how
movements are shaped by the environment (Nathan & Giuggioli 2013).
Task 1.3. Feeding requirements
- Achievement H3: Assessment of spatial and temporal changes in feeding
requirements, associated to changes in food availability, food choice and
digestion efficiency, completed (data collection and statistical tests).
- Deliverable E1: Scientific Article (together with Task 1.1. and 1.3.).
Previous studies have provided already
global estimates of the feeding requirements of four ungulates addressed in
this project (cattle, horse, red deer and fallow deer), based on available
estimates of their energy and protein requirements (Soriguer et al. 2001). A
similar procedure will be used to calculate the historical changes, as well as
the spatial and temporal variation, in the feeding requirements of the populations
of the five species of ungulates estimated in the previous Objective (Task
1.3.1.).
These studies acknowledge, however, that
the estimates provided are subjected to substantial variation in diet across
seasons (particularly, as the pasture dries in summer), among localities and
across individuals. Such information is essential to evaluate the impact of
competition among the different herbivore species, and their responses
thereupon; to estimate the extent to which such species are able to respond to
food shortages through changes in diet choice (e.g., complementing unpalatable
or toxic food sources with palatable or undefended ones) and/or foraging areas
(displacement); and to evaluate adequately the impact of the different
herbivore species on the different plant
species (i.e., the actual drivers of changes in species composition under
different grazing pressures, see below).
To obtain a more detailed description of
herbivore diet composition choices and requirements for the different herbivore
species, we will work at two different scales:
1.3.2. Fecal analysis: We will analyze the
nutrient and energy content of the fecal samples collected in Task 1.2.3. and
compare them with vegetation samples taken at the same moment, to estimate
nutrient and energy uptake. These estimates will provide information on the
intake rates required to meet energy and nutrient demands of the different
ungulate species, and the different vegetation types and seasons.
1.3.3. Food analysis: We will register and
analyze the diet of the individual herbivores tracked with GPS collars (Task
1.2.4) by means of video-recordings obtained by animal-borne video-cameras
(e.g. Loyd et al. 2013). These systems have a proven accuracy to provide
information on numerous aspects of the behavior of elusive species, including
the selection of food item to the level of individual plant species (e.g.
Thompson et al. 2012). In largely mobile and elusive animal, the use of such
systems has been limited by its high cost. In our case, however, the relatively
easy access to the domestic herbivores will allow us to use relative
inexpensive systems that must be renewed over shorter periods of time (e.g.
7-10 days for the Kitty Cams Project, http://www.kittycams.uga.edu/research.html). For more elusive animals (deer and wild boar), we will resort to more
expensive equipment with prolonged battery life and detachable collars (to
recover the images without having to recapture the individual). Cameras will be
deployed, for periods of 1-2 weeks, at four different moments in the year
(autumn, winter, spring and summer).
Ob.2. Estimate the effects of rainfall
level and herbivore pressure on the productivity and standing crop of the
vegetation of Doñana
Task 2.1. Analyze historical data on the productivity and standing crop
of the vegetation of Doñana.
- Achievement H4: Assessment of historical changes in the productivity
and standing crop of the vegetation of Doñana, and the effect of rainfall and
grazing pressure thereupon, completed (data collection and statistical tests).
- Achievement H5: Collection of a dataset for ground-truthing the
standing-crop estimates obtained from RS data (Ob.3) completed.
- Deliverable E2: Scientific Article (together with Task 2.2.).
In the course of previous studies and
management interventions, a considerable number of exclusion plots (and
associated control areas) have been installed and monitored at the different vegetation/landscape
units of the END. We will analyze the available data of those which have been
monitored in previous years, and monitor those that will be made available
during the course of this year, as follows:
2.1.1. Analysis of historical data on
community composition and plant standing crop from 24 (excluded and control)
plots installed at all main vegetation types of the END between 1992 and 2000,
and monitored every spring and summer-autumn since their installation by the
team led by R. Soriguer (who will collaborate actively in their analysis (see
Table 1). Monitoring included record of the cover (per species) and biomass
yield (all species pooled) inside and outside the exclusion plots. Cover and
biomass yield (aboveground biomass, clipped at ground level) were estimated at
the end of each growth season (September-October) in 1x1 m squares (N=8 within
the exclusion and N=20 along 200-m transects placed outside the exclusion).
2.1.2. Monitoring the community
composition and plant standing crop of 9 plots that will be installed at the
end of 2016, in the course of Life+ Project ADAPTAMED. These plots will aim at
facilitating the recruitment of large shrubs and trees, and such recruitment
will be monitored twice a year by the ADAPTAMED team. We will be allowed to
join in and monitor the two variables mentioned above, as well as the analyses
of grazing pressure and dropping production described in Objectives 1.2.3. and
1.3.2. The use of this plots will fill the main gap of those for which
historical data are available (task 2.1.1.), since they are located at
shrubland areas within three different livestock management areas (thus largely
different grazing pressure) of the END. Cover and biomass yield will be
estimated as in task 2.1.1.
2.1.3. Monitoring the community
composition and peak standing crop at 10 additional sites per vegetation unit
(as defined in Obj.3) during the first two years of the project, with the aim
of providing data to validate the remote sensing models developed in Obj.3.
Cover and biomass yield will be estimated as in task 2.1.1.
Task 2.2. Experimental determination of the effect of precipitation and
herbivory on plant productivity and standing crop
- Achievement H6: Assessment of the effect
of precipitation and herbivory on plant productivity and standing crop (experiment and statistical tests).
- Deliverable E2: Scientific Article (together with task 2.1.)
To obtain experimental estimates of the
separate and combined effect of precipitation and herbivory on the productivity
of the Doñana vegetation. For this purpose, we will use two vegetation types,
chosen to represent situations with low and high plant diversity: the “marisma
de castañuela”, dominated by a single species, Scirpus maritimus; and the highly-diverse pastures of the ecotone
between the marsh and the sand, the “vera”. In both cases, we will cross
factorially two types of treatments with four levels each: (i) Rainfall: four
levels corresponding to the mean, median, upper (75%) and lower (25%) quartile
of the historical rainfall record. The distribution of rainfall over time will
also reproduce the average distribution observed in the historical record (for
the subset of year in which a precipitation equal, with 10%, to the chosen
level of annual rainfall). (ii) Herbivory: Removal of the upper 0%, 33%, 66%and
100% part of the plant (to the nearest cm of the plant’s length) present at
each monthly interval. The proportion of biomass removed will be weighed to
estimate total plant production at the end of the experiment. A subsample of
the plants from each treatment will be harvested each month, to estimate
biomass yield, biomass allocation (to leaves, shoots, rhizomes, roots and, if
present, tubers). The experiment will take place at the experimental facilities
(mesocosm facility) and field plots (provided with herbivore-exclusion fences
and water supply) of the Doñana Biological Reserve (RBD-ICTS).
Ob.3. Reconstruct the long-term changes in
productivity and standing crop of the Doñana vegetation, using remote-sensing
tools
- Achievement H7: Development, calibration and validation of RS models
estimating the productivity and standing crop of the vegetation of Doñana.
- Deliverable E3: Scientific Article.
We will combine remote sensing data,
consisting of NDVI estimated derived from MODIS satellite images from the study
area, with biomass production data obtained in the previous objective (Ob.2),
to produce models allowing for the estimation of plant biomass (standing crop)
and productivity (changes in plant standing crop) from such images. These model
will be used to (i) model the seasonal cycle of biomass production, and its
variation across years and its relation to total biomass yield, (ii) model the
effect of key environmental factors (such as rainfall, topography and grazing
pressure) on such cycles, and (iii) reconstruct historical changes in biomass
yield (last three decades) and evaluate its potential drivers (e.g. changes in
grazing pressure). For this purpose, we will proceed in
three steps:
Task 3.1. Obtain long-term series of NDVI for the different vegetation
types of the END and fit them to existing models based on key environmental
factors (such as rainfall, topography and grazing pressure).
This task will be based on the vegetation
units defined and mapped at the “Cartografía de los Sistemas de Vegetación del
Parque Nacional de Doñana 1:10000” (2014). This is the last vegetation map
published. It is based in the interpretation of orthophotos from 2009 and it
incorporates previously published vegetation maps.
For each of the main vegetation units for
which biomass yield data are available (see Table 1), we will produce a NDVI
temporal curve at 10-16 groups of 3x3 pixels (‘sites’ hereafter). These sites
will include those for which biomass data are available (N=1-6), which will be
used for cross-calibration; plus 10 additional sites, distributed as to
maximize variation in current plant productivity (estimated from a
classification of average NDVI values during the last five years), which will
be used for validation (see below).
Data will be
derived from MODIS satellite images (spatial resolution of 250 m, temporal
resolution: 7 days) from 2000 until the last image available at the time of
task execution. The series that we will use is already processed in form of
NDVI values provided by BOKU Vienna (Vuolo, Mattiuzzi, Klisch, & Atzberger,
2012).
NDVI temporal curves characterize the
development and photosynthetic activity of the green vegetation. Firstly, we
will derive phenological parameters of the curves in two steps. We will use
Timesat, a software package specifically developed to analyze time-series of
satellite data (Jonsson & Eklundh, 2004), to analyze the time series derived
from MODIS images (since Timesat does not accept irregular temporal series). In
a second step, we will compare the interannual variation in phenological
parameters across vegetation units, to evaluate their reliability as food
resource for herbivores; and will evaluate the effect of different
environmental variables (such as precipitation, inundation probability and/or
grazing pressure) on such variation.
Task 3.2. Calibrate and validate the predictions of the model, using the
available data of plant biomass obtained in Task 1.2.
Phenological curves fitted to NDVI values
will be used to obtain different estimates of plant standing crop (based, e.g.,
on the peak values or the area under the curve). Separate subsets of these
values will be used for calibration and validation, as follows:
3.1.1.
At the sites where biomass-yield data are
available (N=1-3), annual estimates derived from NDVI curves (N=20-30 per site)
will be compared to ground-truth values and their relationship modelled using
Generalized Linear (Mixed) Models. Departing from full models with random
intercept and slopes, we will select the most parsimonious model based on the
AIC scores.
3.1.2.
Based on the previous calibration, we will
calculate the biomass yield of the remaining sites (N=17-19) for the first two
years of the project, and compare these values to field observations of peak
biomass yield taken at these two years.
Task 3.3. Extrapolate the available estimates to the rest of the END.
Based on the parameter values obtained in
the previous sections, and the NDVI values derived from MODIS images, we will
produce maps of plant standing crop across the whole END. These maps will be
used to (i) estimate the carrying capacity of the plant’s vegetation for
herbivores, and its recent changes (last 2-3 decades), and (ii) estimate the
interaction between different descriptors of space use and grazing pressure by
ungulates, and the spatial variation in the availability of food resources
(plant standing crop).
Ob.4. Develop models of the relationship between rainfall, grazing
pressure and plant standing crop at the END, and use them to evaluate different
management scenarios under current and forecasted climate conditions.
Task 4.1. Develop models of the effect of
rainfall and grazing on plant standing crop
- Achievement H8: Development, calibration and validation of
spatially-explicit models of the relationship between rainfall, grazing
pressure and plant standing crop at the END.
- Achievement H9: Collaborative design, generation and evaluation of scenarios
reflecting different management strategies and forecasted changes in climatic
conditions.
- Deliverable E4: Scientific Article.
- Deliverable E5: Adaptive management strategy. (The achievement of this
deliverable is contingent on achieving the necessary levels of trust and
cooperation among managements and stakeholders.)
Based on the results of previous
objectives, we will develop spatially-explicit, process-based models of the
relationship between rainfall, grazing pressure and plant standing crop. We
will model the behavior of the different vegetation units of the END
separately, while allowing for the ungulates to move freely among these units
(within the restrictions imposed by the physical barriers associated to the
different management units, see above). The model will incorporate simple
demographic models for wild ungulates, while the abundances of domestic
herbivores will be considered as fixed (i.e. as determined by the management
regime).
The main state variable of the model will
be plant standing crop. This is the main descriptor of plant production
addressed throughout the project, owing largely to its availability from
historical observations. However, this variable is actually the result of the
dynamic interplay between plant growth and plant consumption by herbivores. To
be able to derive estimates of plant biomass available for herbivore
consumptions, the model will simulate these two processes separately. To
evaluate the reliability of these predictions, we will calibrate and validate
the model using the estimates of plant standing crop obtained in Ob.3 (Task
3.3.), both separately for each vegetation unit and pooled across them.
Separated subsets for calibration and validation will be obtained in two
different ways: (i) by splitting the complete time series in two (10-15 years
each), and (ii) by randomly sampling separate sets of observation units (3x3
pixels) for calibration and validation, within each year of the time series
(following autocorrelation analysis to ensure independence of the two
datasets).
Task 4.2. Generate and evaluate different
management scenarios under current and forecasted climate conditions (climate
change)
The model developed in 5.2. will be used
to evaluate different scenarios arising from the factorial combination of
different management strategies and different climate conditions (both current
and forecasted). The development and evaluation of the different management
scenarios will be undertaken in close collaboration with the END managers and
key stakeholders (e.g. local rancher associations, environmental NGOs), using
participatory techniques in which the research team has already ample
experience (e.g. Méndez et al. 2012, Santamaría et al. 2013). These
interactions will be structured in three different workshops, respectively
addressing (i) the purpose and structure of the model, (ii) model development
and preliminary model simulations, (iii) final, interactive simulations. If
possible (i.e., if the level of trust and collaboration raised during the participatory
modelling phase allows for it), we will aim at the elaboration of a (draft)
adaptive management plan for the domestic and wild ungulates of the END to be a
result of the third workshop.
Work plan
|
Task
|
Workteam members
|
Year 1
|
Year 2
|
Year 3
|
|
Task 1.1.Historical data on herbivore abundance
|
LS,FC,RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 1.2. Spatial distribution and individual movements
|
|
|
|
|
|
1.2.1. Analyze monitoring data
|
LS, FC, RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
1.2.2. Analyze dropping counts
|
LS, FC, RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
1.2.3. Camera traps
|
LS, FC
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
1.2.4. GPS collars
|
LS, PC, RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 1.3. Feeding requirements
|
|
|
|
|
|
1.3.1. Literature analysis
|
LS, RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
1.3.2. Fecal analysis
|
LS, FC
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
1.3.3. Food analysis
|
LS, FC, RS
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 2.1. Historical data on the plant standing crop
|
|
|
|
|
|
2.1.1. Analyze historical data
|
LS, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
2.1.2. Survey shrubland plots
|
LS, CP
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
2.1.3. Survey additional sites
|
LS, CP
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 2.2. Experiment on effects of precipitation and herbivory
|
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 3.1. NDVI models
|
LS, AM, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 3.2. Calibrate and validate model predictions
|
LS, AM, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 3.3. Maps of plant standing crop
|
LS, AM, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 4.1. Develop dynamic models of plant standing crop
|
LS, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Task 4.2. Generate and evaluate different management scenarios
|
LS, RD
|
JFMAMJJASOND
|
JFMAMJJASOND
|
JFMAMJJASOND
|
|
Achievements
|
|
***H1*H4******
|
H7*******H5H6*
|
******H2*H3H8*H9
|
|
Deliverables
|
|
************
|
*****E3******
|
E2********E1E4E5
|
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C.2.
IMPACTO ESPERADO DE LOS RESULTADOS
The main
contribution expected from this project will be the development of a knowledge base, long-term criteria and modelling tools
for the management of free-ranging livestock in Mediterranean protected areas
with high climatic variability, taking the Doñana Protected Area (Espacio
Natural Doñana, END) as a case study. The project impact should therefore span
from general science, where it will provide insight into cutting-edge questions
such as the spatial factors underpinning resource use by herbivores and the
role of landscape heterogeneity as a buffer against the crossing of tipping
points leading to environmental degradation; to applied research, where it will
provide specific tools and guidelines for the management of free-ranging
livestock-production system, which should be readily applicable to Doñana and,
should they prove useful, could be extrapolated to other areas with similar
characteristics. More importantly, it will provide elements for the proactive
management of such exploitations in the face of climate change, increasing the
resilience of socio-natural system against expected changes associated to it.
The participatory approach proposed during the modeling phase will increase the
likelihood of a speedy transfer of he project results, and will hopefully
introduce elements of social innovation in a management system that has
traditionally relied quite exclusively on specialist from the fields of natural
sciences append engineering.
Besides several deliverables directly applicable
to knowledge transfer into policy and management (RS and dynamic models,
collaborative adaptive management strategy), the project will also aim at
achieving a high-quality scientific output, in the form of (i) four
publications in high impact journals (such as Ecography, Ecology, J Ecol, J
Appl Ecol, Conserv Biol or Ecol Modelling, where we have published extensively
in the past) - two of them, if funding allows, in open-access journals to
increase their visibility; (ii) one article summarizing the results in a
science journal for the general public; (iii) one national (Spanish Association
of Terrestrial Ecology AEET) and one international conference (Ecological
Society of America, British Ecological Society or INTECOL); and (iv) two
presentations for practitioners (Park Managers), stakeholders
(livestock-breeder associations, environmental NGOs) and the general public
(e.g. Science Week, technical and secondary schools).
Outreach towards academics, practitioners and
more general public will be also achieved through the development of a project
web page, hosted at the general page of the EBD-CSIC, where all project results
(including modeling products) will be made publicly available. Entries to this
page will be disseminated using other social media, through the accounts
managed by the outreach team of EBD-CSIC.
C.3. CAPACIDAD FORMATIVA DEL EQUIPO SOLICITANTE
The IP and other researchers of the work team
has formed a high number of researchers that have obtained their PhD thesis,
MSc degrees or senior graduate projects. In particular, Luis Santamaría has
supervised five MSc Theses and seven PhD Thesis. The later include those
defended by Jörn Pilon at Wageningen University (The Netherlands) in 2002;
Helen Hangelbroek, at Nijmegen University (The Netherlands) in 2004; Ainhoa
Magrach, at the University of Santiago de Compostela (Spain), in 2011; Iris
Charalambidou, at Utrecht University (The Netherlands), in 2012; Lucía Latorre,
at the University of Santiago de Compostela (Spain), in 2013; Duarte Viana at
the Pablo de Olavide University ( Spain) and Pablo Fernández Méndez, at the
University of the Balearic islands (Spain). All these PhD theses obtained
outstanding marks and resulted in high quality scientific papers.
The interdisciplinarity and the high quality of
the working team are a guarantee of a good environment for the formation of new
researchers. At the same time, the IP and sole member of the research team
(Luis Santamaría) will be able to provide fully-committed supervision to the PhD
student requested, since his only commitment at present is the co-supervision
of one PhD researcher, who will be in the third year of her work by 2017. The project results will represent a suitable departure
point from which the PhD student will be able to add an in-depth assessment of
the effects of ungulates on other elements of the Doñana ecosystem, having from
the start the freedom to select a topic of his/her own and the opportunity to
benefit from the scientific quality, interdisciplinarity and internationality
of the work team in developing such topic.
