Alessandro Manfrin

Alessandro Manfrin
Universität Koblenz-Landau · Department of Environmental Sciences

PhD
SystemLink Project - https://systemlink.uni-landau.de/

About

36
Publications
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Citations
Introduction
My scientific interests include theoretical and applied ecology, conservation and evolution, especially related to freshwater and riparian ecosystems. I am fascinated by the flux of allochthonous subsidies that link ecosystems across boundaries and how environmental anthropogenic alterations are likely to affect them.
Additional affiliations
August 2017 - present
University of Applied Sciences Trier and University of Duisburg-Essen
Position
  • PostDoc Position
April 2017 - August 2017
Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Position
  • PostDoc Position
December 2013 - December 2016
Freie Universität Berlin
Position
  • Employed
Education
October 2013 - May 2017
Freie Universität Berlin and Queen Mary University of London
Field of study
  • Ecology, Biology, Food Webs
September 2006 - May 2010
Università Degli Studi Roma Tre
Field of study
  • Biological Sciences
September 2000 - February 2005

Publications

Publications (36)
Article
Full-text available
Artificial light at night (ALAN) is recognized as a contributor to environmental change and a biodiversity threat on a global scale. Despite its widespread use and numerous potential ecological effects, few studies have investigated the impacts on aquatic ecosystems and primary producers. Light is a source of energy and information for benthic auto...
Article
Full-text available
Artificial light at night (ALAN) is a widespread alteration of the natural environment that can affect the functioning of ecosystems. ALAN can change the movement patterns of freshwater animals that move into the adjacent riparian and terrestrial ecosystems, but the implications for local riparian consumers that rely on these subsidies are still un...
Article
Aquatic and terrestrial ecosystems are linked by fluxes of carbon and nutrients in riparian areas. Processes that alter these fluxes may therefore change the diet and composition of consumer communities. We used stable carbon isotope (δ¹³C) analyses to test whether the increased abundance of aquatic prey observed in a previous study led to a dietar...
Article
Full-text available
Small standing water emits a large amount of methane into the atmosphere. It has been found that chironomid larvae which dwell in sediment at their larval stage, reduce methane production and increase methane oxidation by enhancing oxygen transport into the sediment. Thus chironomids' presence may reduce methane emissions. We performed our study in...
Article
Full-text available
Ecosystems are complex structures with interacting abiotic and biotic processes evolving with ongoing succession. However, limited knowledge exists on the very initial phase of ecosystem development and colonization. Here, we report results of a comprehensive ecosystem development monitoring for twelve floodplain pond mesocosms (FPM; 23.5 m × 7.5 m...
Article
In a meta-ecosystem, spatially separated ecosystems are linked by biotic and abiotic cross-ecosystem flows. Hence, food webs in a meta-ecosystem are functionally linked. They are susceptible to multiple stressors threatening ecosystem functions and associated services. Although empirical studies can help understand stressor effects on meta-ecosyste...
Article
Full-text available
Intraspecific diet specialization, usually driven by resource availability, competition and predation, is common in natural populations. However, the role of parasites on diet specialization of their hosts has rarely been studied. Eye flukes can impair vision ability of their hosts and have been associated with alterations of fish feeding behavior....
Technical Report
Full-text available
River floodplains hold a central role in supporting the status of water, nature and biodiversity conservation, climate change mitigation, and ecosystem services. They build an important link between rivers and their catchments, mainly through their water retention capacity and the lateral connectivity controlled by flood events and groundwater exch...
Article
Vorliegende Studie erfasst erstmalig sämtliche Standgewässer in Niedersachsen und zeigt, dass künstlich ge-schaffene kleine Baggerseen der dominierende Gewässertyp der Region sind. Zudem legt diese Studie verglei-chende Ergebnisse zur Biodiversität anglerisch bewirtschafteter und unbewirtschafteter Baggerseen vor. Ob-wohl die anglerisch bewirtschaf...
Article
Southern Africa has one of the highest densities of temporary pools and some of the most understudied temporary wetlands in the world. Additionally, the eastern African annual killifishes (Nothobranchius spp.) are rare in southern Africa and found exclusively in temporary habitats. There is a notable lack of literature regarding the diet of these f...
Book
Die heimische Flora und Fauna reagieren auf künstliche Beleuchtung. Die Bewertung der Auswirkungen von künstlicher Beleuchtung auf insbesondere dämmerungs- und nachtaktive Arten und ihre Lebensgemeinschaften ist schwierig, weil Änderungen der Beziehungen und Abhängigkeiten von Arten und Lebensgemeinschaften unter dem Einfluss von künstlichem Licht...
Article
Assessments of river restoration outcomes are mostly based on taxonomic identities of species, which may not be optimal because a direct relationship to river functions remains obscure and results are hardly comparable across biogeographic borders. The use of ecological species trait information instead of taxonomic units may help to overcome these...
Article
The increasing impairment of lotic ecosystems has promoted a growing effort into assessing their ecological status by means of biological indicators. While community-based approaches have proven valuable to assess ecosystem integrity, they mostly reflect long-term changes and might not be suitable for tracking and monitoring short-term events. Resp...
Conference Paper
Full-text available
In recent decades, the use of artificial illumination has rapidly increased, transforming nocturnal environments worldwide. Inappropriate and extensive use of artificial illumination results in light pollution: an increase in nocturnal light above natural levels and a disruption of natural light cycles. Light/dark cycles have been stable over geolo...
Article
The increasing impairment of lotic ecosystems has promoted a growing effort into assessing their ecological status by means of biological indicators. Community-based approaches are a valuable way of assessing ecosystem changes, but reflect local extirpation and long-term changes and might not be suitable for tracking and monitoring short-term and s...
Article
The increasing use of artificial light at night (ALAN) has led to exposure of freshwater ecosystems to light pollution worldwide. Simultaneously, the spectral composition of nocturnal illumination is changing, following the current shift in outdoor lighting technologies from traditional light sources to light emitting diodes (LED). LEDs emit broad-...
Article
Freshwaters are increasingly exposed to artificial light at night (ALAN), yet the consequences for aquatic primary producers remain largely unknown. We used stream-side flumes to expose three-week-old periphyton to LED light. Pigment composition was used to infer community changes in LED-lit and control periphyton before and after three weeks of tr...
Preprint
Full-text available
The increasing impairment of lotic ecosystems has promoted a growing effort into assessing their ecological status by means of biological indicators. While community-based approaches have proven valuable to assess ecosystem integrity, they mostly reflect long-term changes and might not be suitable for tracking and monitoring short-term events. Resp...
Article
Full-text available
Artificial light at night (ALAN) is one of the most obvious hallmarks of human presence in an ecosystem. The rapidly increasing use of artificial light has fundamentally transformed nightscapes throughout most of the globe, although little is known about how ALAN impacts the biodiversity and food webs of illuminated ecosystems. We developed a large...
Article
Full-text available
Although the assembly of stream macroinvertebrates is regulated by environmental heterogeneity at multiple spatial scales, field bioassessment studies that explicitly considered such scale-dependency are rare. Here, we investigated how large scale longitudinal gradients and local microhabitat structure jointly regulate the assembly of macroinverteb...
Article
Full-text available
Although the assembly of stream macroinvertebrates is regulated by environmental heterogeneity at multiple spatial scales, field bioassessment studies that explicitly considered such scale-dependency are rare. Here, we investigated how large scale longitudinal gradients and local microhabitat structure jointly regulate the assembly of macroinverteb...
Article
Full-text available
The main aim of this study was to improve the knowledge about the concordance among macrophytes and macroinvertebrates to provide complementary information and facilitate the procedures for quality assessment of river ecosystems. Macrophytes and macroinvertebrates were collected in 11 sampling sites along a central Apennine calcareous river in Octo...
Article
Full-text available
Several studies on concordance between macrophyte and macroinvertebrate communities were carried out for decades while any investigation on co-occurrence of single pair of taxa of these two groups was never addressed. Our main aim was to verify the existence of co-occurrence of single macrophyte–macroinvertebrate pair in a Mediterranean river of ce...
Article
Full-text available
Inland waters are constituted by a lot of seriously threatened habitats. The increasing need to safeguard these ecosystems led European Union Member States to propose the Water Framework Directive which decided the creation of homogeneous areas characterized by very similar geology, topography and climate, known as hydroecoregions (HER) and firstly...
Article
Full-text available
River impoundments and waste water discharge are a serious threat to the integrity and biodiversity of river ecosystems, especially in central Italy. Benthic macroinvertebrates were sampled in autumn and summer along the Aniene River to assess the cumulative biological effect of the numerous dams and sewage treatment plants that affect its middle a...
Conference Paper
The main aim of this study was to improve the knowledge about the concordance among macrophytes and macroinvertebrates to provide complementary information and facilitate the procedures for quality assessment of river ecosystems. Macrophytes and macroinvertebrates were collected in 11 sampling sites along a central Apennine calcareous river in Octo...
Data
L‘analisi delle minacce costituisce un processo di valutazione che comprende una fase di classificazione, quantificazione, comparazione, ranking di questi eventi. La quantificazione delle minacce può essere effettuata con un approccio expert-based, acquisendo punteggi (scores) da parte di esperti tecnici sia dei target di conservazione che del sito...

Questions

Questions (19)
Question
Dear all, I would like to start a discussion here on the use of generalised mixed effect (or additive) models to analyse count data over time. I reported here the "few" analyses I know in R for which I found GOOD (things) and LIMITS /DOUBTS. Please feel free to add/ comment further information and additional approaches to analyse such a dataset. Said that, generalised mixed effect modelling still requires further understanding (at least from me) and that my knowledge is limited, I would like to start here a fruitful discussion including both people which would like to know more about this topic, and people who knows more.
About my specific case: I have counted data (i.e., taxa richness of fish) collected over 30 years in multiple sites (each site collected multiple times). Therefore my idea is to fit a model to predict trends in richness over years using generalised (Poisson) mixed effect models with fixed factor "Year" (plus another couple of environmental factors such as elevation and catchment area) and random factor "Site". I also believe that since I am dealing with data collected over time I would need to account for potential serial autocorrelation (let us leave the spatial correlation aside for the moment!). So here some GOOD (things) and LIMITS I found in using the different approaches:
glmer (lme4):
GOOD: good model residual validation plot (fitted values vs residuals) and good estimation of the richness over years, at least based on the model plot produced.
LIMITS: i) it is not possible to include correction factor (e.g., corARMA) for autocorrelation.
glmmPQL(MASS):
GOOD: possible to include corARMA in the model
LIMITS: i) bad final residual vs fitted validation plot and completely different estimation of the richness over years compared to glmer; ii) How to compare different models e.g., to find the best autocorrelation structure (as far as I know, no AIC or BIC are produced)? iii) I read that glmmPQL it is not recommended for Poisson distributions (?).
gamm (mgcv):
GOOD: Possible to include corARMA, and smoothers for specific dependent variables (e.g., years) to add the non-linear component.
LIMITS (DOUBTS): i) How to obtain residual validation plot (residuals vs fitted)? ii) double output summary ($gam; $lme): which one to report? iii) in $gam output, variables with smoothers are not estimated (only degree of freedom and significance is given)? Is this reported somewhere else?
If you have any comment, please feel free to answer to this question. Also, feel free to suggest different methodologies.
Just try to keep the discussion at a level which is understandable for most of the readers, including not experts.
Thank you and best regards
Question
Dear all,
My question is the following:
I have large datset: 100,000 observations, 20 numerical and 2 categorical variables (i.e. mixed variables)
I need to cluster these observations based on the 22 variables, I have no idea how many clusters/groups a priori I should expect.
As the large dataset I use clara() function in r (based on "pam").
Because of the large number of observations, there is no way to compare distance matrixes (R does not allow such calculations, and is not a problem of RAM), therefore the common way of cluster selection using treeClust() and pamk() and comparison of "silhouette" does not work.
My main quesitons is: can I use factors like total SS, within SS, between SS to have an idea of the best performing Tree (in terms of number of clusters)? Do you have any other idea of how can I select the right number of clusters?
Best regards
Alessandro
Question
Dear all,
I am trying to understand the diet of different fish parasites using stable isotope analysis. I have indications (isospace) that some of them are feeding directly on the fish tissues, but others on other sources (not fish tissues). How do I correct C13 and N15 for fractionation in this case? Are you aware of studies and /or correction factors applied to fish parasites?
Best regards
Alessandro Manfrin
Question
Dear all,
do you know if:
1 - can I run an RDA with negative (taxa) values (as delta Control - Treatment)?
2 - Do I have to use the function decostand function on these delta values before performing the RDA?
3 - Shall I use Bray-Curtis distance (dist='bray") in the RDA function?
Best
Alessandro
Question
Dear all,
I have a dataset of fish collected in different rivers over different years each of them sampled a different number of times during different projects . This different number of observations among rivers in some cases can be important: e.g.
River X = 1 project (1 observation=1 sampling x 1 year);
River Y = 5 projects (15 observations= 1 sampling x 3 years x 5 projects);
River Z= 15 projects (105 observations=1 sampling x 7 years x 15 projects);
I want to calculate in the all region (so not interested in specific rivers) how the abundance is related to Years, Latitude, Altitude and Anthopic pressures (APindex). I thought to use the following model:
lme: Abu~Years+Latitude+Altitude+APindex + (1|river/project) + corrARMA (form = time|River/project).
-What is the influence of RiverZ with its 105 observation compared to the other rivers which have less number of observations?
-Am I accounting for this unbalanced observations in the random structure (1|river/project)?
-Do I have to account in the model for the different number of observations with (weight=1/n observation for each project?)
Thank you
Question
Manfrin et al. 2018. Dietary changes in predators and scavengers in a nocturnally illuminated riparian ecosyst. Oikos. DOI: 10.1111/oik.04696.
Artificial Light is affecting spider diet as a consequence of changes in aquatic-terrestrial insect prey fluxes.
best
Alessandro
Question
Dear all,
I have maybe for the "time series" experts a silly question:
-I have a dataset of European rivers =80
-In 50% of the rivers I have more than 1 project; in the other 50% is 1 river = 1 project
-In 50 % of the projects I have data collected only for 1 year; in the other 50% of the projects data were collected over years (from 2 untill 20 years, depending on the project)
->I want to assess the Fish diversity depending on the altitude, latitude, catchment size.
After exploring data for the model assumption of normality, variance heterogeneity etc..I though to run this model:
mod<-lme(Fish Diversity~log(altitude)+log(latitude)+log(catchment size), random~1|Rivers/Projects, method="ML", data=dati)
When I look at the residuals of model mod and at the acf (residuals(mod) and pacf(residuals(mod), they are pretty good but in acf there is autocorrelation in lag1
and in pacf the line goes slightly over in lag 3. I think I would give it a try with CorAR1 (p=1) correction in lme.
My questions are:
1- Is the model developed in your opinion correct?
2- Can I fit a correlation CorrAR1 in the lme by just looking at the acf and pacf plots from the model mod? As u see I have different project over time that means potentially multiple time series (for each project). Can I just fit a unique AR1 structure looking at the residuals of the model (without CorrAR1) and not at the raw data and assume that the same temporal trend is present in all the projects analysed? How can the acf and pacf know what is the temporal repetion (i.e.
how the acf and pacf biuld the lags in the plots)?
3- if the question number 2 is yes, do I have to organise in the dataframe chronologically in the dataset for each project? (e.g. Project1 from 2000 untill 2008; Project 2 from 1998 untill 2015, and so on?) as dati[order(dati$Project_names, dati$Year_evaluation), ]
and give to the corrAR1 the form structure form=1|Rivers/Project_names
Would this model be ok?
modAR<-lme(Abu~log(altitude)+log(latitude)+log(catchment size), random~1|Rivers/Project_names, method="ML",
correlation=corARMA(form = ~1|Rivers/Project_names, p=1)
Thank you for your time
Alessandro
Question
What is the best way to calculate the delta of a Control vs a Impact condition? In my study I have many rivers restored that are compared to a temporal or spatial unrestored condition. I would like to observe patterns of change between restored vs unrestored rivers over time, For this reason I thought to calculate the effect as DELTA. What do you think is the best way to calculate this?
1- Control - Impact
2- (Control-Impact)/Control
Is there a substantial difference?
Thanks for your consideration
Alessandro
Question
Dear all,
I am struggling to find the best way to analyse my dataset. I have to compare fish diversity in restored and unrestored river sites over time. Fish samples were collected from 80 comparable rivers. However, in some rivers the sampling was conducted only 1 time, in other rivers the sampling was conducted up to 15 times (once per year).
To start I thought to use this simple mixed effect model:
Fish diversity~restoration*years from restoration, random=(1|rivers).
However, I believe I have to run my model accounting for temporal autocorrelation (ARMA correction in lme) as data in many rivers are collected mulitple times over years.
My question is: can I use such a correction when in my daset I have rivers in which the sampling was conducted only 1 year while in other rivers the sampling was conducted multiple years (up to 15)?
Thanks for your consideration
Alessandro
Question
What could be the reason of a massive single-night macroinvertebrate drifting event occurred in an sub-alpine stream after 2 days of a 4 week experiment performed in Mai 2014? Drifting rate of the night before and of the night after was 100 times lower then the one observed during the night of "the event". Moon-light intensitites? Ice melting? Thanks in advance

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Projects

Projects (5)
Project
Crossing boundaries: Propagation of in-stream environmental alterations to adjacent terrestrial ecosystems SystemLink investigates bottom-up and top-down mediated interactions in terrestrial ecosystems, which propagate from aquatic environments as a result of their exposure to anthropogenic stress. Doctoral researchers in SystemLink either conduct experiments in unique aquatic-terrestrial mesocosm facilities combined with laboratory and field research, or develop and apply process-based environmental models. https://www.uni-koblenz-landau.de/de/landau/fb7/umweltwissenschaften/systemlink
Project
Most natural phenomena are scale-dependent in that different patterns and processes are likely to manifest when viewed at different scales. However, explicit consideration of this scale-dependency is seldom included in ecological research, despite being particularly relevant, for example for the assessment of biodiversity change. In this set of papers, we specifically examined how the inclusion of multiple spatial and temporal scales can reveal the complexity of biodiversity change and its drivers, with implications for both applied and basic research.
Project
Nature knows no boundaries. Boundaries are mental fences that we humans impose on ourselves. We investigate how aquatic and terrestrial ecosystems exchange energy and matter, and how environmental change is affecting this process.