Advanced analytical approaches in ecological data analysis The world comes in fragments

Early plant succession in the Saxon (Germany) post brown coal mining area Chicken Creak Succession starts with colonising species from a regional species pool and from the initial seed bank

Species co-occurrences How do patterns of species co-occurrences change in time? 2005A1-2A3-2A4-2A4-3B1-2B2-1B2-4 Agrostis_capillaris Agrostis_stolonifer Cirsium_arvense A1-1A1-2A1-3A1-4A2-1A2-2A2-3 Achillea_pannonica Agrostis_capillaris00.50 Agrostis_stolonifer Agrostis_vinealis Ajuga_genevensis Apera_spica-venti Arenaria_serpyllifo Early plant succession Starting hypothesis 1.Island biogeography predicts initial species occurrences to be random. 2.Compretition theory predicts equilibrium species occurrences to be not random but driven by interspecific competition. Basic questions 1.Which species colonise initially? 2.Is initial colonisation directional? 3.Is colonisation predictable?

How to test for (non-) randomness? Sites Species A B C D E Clustered co-occurrence Joined co-occurrence SegregationReciprocal segregation Checkerboard Common ecological requirements Habitat filtering Niche conservatism Competition Reciprocal habitat requirements Facilitation, mutualism Habitat engineering by the earlier colonizer Joined absences Habitat filtering Niche conservatism is the tendency of closed related species to have similar ecological requirements and life history raits

Sites Species A B C D E EV EV Sites Species C B A E D Sort according to the dominant eigenvector of correspondence analysis Spatial species turnover (  -diversity) Sorting a presence- absence matrix according to the dominant eigenvectors of corresondence analysis (seriation) maximizes the number of occurrences along the left to right diagonal. Metric for spatial species turnover Squared correlation R 2 of row and column ranks of species occurrrences. RCPearson R2R

Sites Sum Species A B C D E Sum A nested subset pattern Nestedness describes a situation where a species poorer site is a true subset of the next species richer site. A presence – absence matrix ordered according to total species richness (marginal totals, degree distributions) Sites Sum Species A B C D E Sum Unexpected absence Unexpected presence

The measurement of nestedness The distance concept of nestedness. Sort the matrix rows and columns according to some gradient. Define an isocline that divides the matrix into a perfectly filled and an empty part. The normalized squared sum of relative distances of unexpected absences and unexpected presences is now a metric of nestedness the nestedness temperature.

Nestedness based on Overlap and Decreasing Fill (NODF) NODF is a gap based metric and more conservative than temperature.

Back to the Huehnerwasser How does species co-occurrence change during early succession?

The number of reciprocal species co- occurrences increases in time The degree of nestedness is at an average level (neithert nested nor anti- nested) The degree of species spatial turnover decreases in time But are raw scores reliable? What do we expect if colonisation were a simple random process?

Statistical inference using null models What is random in ecology? Sites Sum Species A B C D E Sum Fill the matrix at random but proportional to observed marginal (row/column) totals until the observed total number of occurrences is reached The proportional- proportional null model Fill the matrix at random until for each row and each column the observed total number of occurrences is reached The fixed - fixed null model Sites Sum Species A B C D E Sum Take a checkerboard pair and swap. Do this times to randomize the matrix.

Statistical inference using null models Observed score 400 randomized matrices For each randomized matrix we calculate the respective metric (C-score, NODF, R 2 ). Standardized effect sizes (SES) are Z- transformed scores and can be linked to a normal distribution. P(-1 < X <+1) = 68% P(-1.65 < X < +1.65) = 90% P(-1.96 < X < +1.96) = 95% P(-2.58 < X < +2.58) = 99% P(-3.29 < X < +3.29) = 99.9% The Fisherian significance levels SES- SES

YearScore Average null distribution score Standard deviation Z-score (SES) FF null model P(Z) C-score E E NODF R2R E

SES scores (FF mull model) The degree of reciprocal species segregation constantly increases during early succession Local plant communities are not significantly nested during succession Species spatial turnover peaks at intermediate stages of succession In ecological research raw metrics are most often meaningless!!

Different null assumptions give different answers FF PP FF PP

FF PP The FF null model assumes that sites are filled with species and that each species occupies the maximal number of sites. The PP null model assumes that sites might differ dynamically in species richness and that each species might occupy a variable number of sites. The PP null model points often to a random pattern in species occupancy.

Idiosyncratic species are those that deviate in their patterns of occurrences Species 2005 Total Occ NODFExpNODFSpResultZ-SpResuDeltaSpC Cirsium_arvense Chenopodium_album_agg Agrostis_stolonifera_agg Crepis_tectorum Echium_vulgare Rumex_acetosella_var._te nuifoliu Calamagrostis_epigejos Arenaria_serpyllifolia_agg Festuca_rubra_agg Daucus_carota Agrostis_capillaris Carex_ericetorum Bromus_tectorum Robinia_pseudoacacia Lupinus_luteus Poa_palustris Rubus_fruticosus_agg Sites Species A B C D E Cirsium arvense increases (DeltaC < 0) the degree of nestedness None of the species decreases the nestedness pattern. There are few unexpected occurrences. All species behave similar.