The functional consequences of the biodiversity: Experimental studies with intertidal communities

The functional consequences of the biodiversity: Experimental studies with intertidal communities. Airam Prieto Martín. Mestrado em Ecologia, Ambiente e Território. Departamento de Biologia 2014. Orientador Doutor Francisco Arenas Parra. Investigador . CIIMARCentro Interdisciplinar de Investigação Marinha e Ambiental. Laboratório de Biodiversidade Costeira. Porto AGRADECIMENTOS Quero agradecer ao Ciimar por me aceitar nas suas instalações para a realização desta tese de mestrado, em especial ao Laboratorio de Biodiversidade Costeira. Um grande obrigado ao meu orientador, Drº. Francisco Arenas, pelo apoio, ajuda e incentivo prestado em todos os momentos. Sem ele esta tese não tinha sido possível. Tambem gostaria de fazer um agradecimento especial ao colega Ivan Rodil pela ajuda na discussão do trabalho. Á Sonia pelo apoio e ajuda, nos bons e maus momentos. Á minha família que mesmo estando numa ilha “perdida” no Atlântico está sempre presente. Aos meus colegas de laboratório (menina Raquel, sr Diogo, menina Patrícia, lord Davide, Mr Duarte, cunhada Angela, etc) pelo apoio, ajuda e alegrias vividas. Em geral, a todas as pessoas que de certa forma estiveram presentes durante a realização deste trabalho. ABSTRACT Over the last decades, global lost of biodiversity has fuelled considerable research to investigate the functional consequences of declining diversity in communities. Rapid changes in the biological composition and richness of most of earth´s ecosystems as a result of human activities have brought new urgency into these questions. Biodiversity can affect traits of ecosystem function. This study presents an experimental approach to examine the effects and interactions of species richness and evenness on the primary productivity of synthetic assemblages. We used a modification of the design proposed by Benedetti-Cechii (2004) which included explicitly diversity, evenness while controlling the effect of identity. The experiment shows that Species identity was the most of the relevant effect on assemblages functioning the higher productivity and efficiency values were found for Sargassum muticum. Conversely, Bifurcaria bifurcata seems to be the species with lower overall performance Our approach was unable to detect some of the effects of species richness and evenness suggested in literature. Probably only longer experiments would allow species to develop strong positive interactions and reduce the prevalence of large identity effects Keywords: Biodiversity, Species Richness, Evenness, Productivity. Macroalgal assemblages RESUMO Nas últimas décadas, as perdas globais de biodiversidade tem incrementado a investigação científica sobre as consequências funcionais do declínio da diversidade nas comunidades. As rápidas mudanças na composição biológica e riqueza dos ecossistemas Terrestres como resultado das atividades humanas suscitou a resposta a este problema. A biodiversidade pode afetar as características e o funcionamento dos ecossistemas. Este estudo apresenta uma abordagem experimental para aferir acerca dos efeitos e interações da riqueza específica e do Evenness na produtividade primária das comunidades artificias de macroalgas. Assim, foi utilizada uma modificação do desenho experimental proposto por Benedetti-Cechii (2004), que inclui a diversidade e o Evenness para o controlo do efeito da identidade de espécies.O trabalho realizado mostra que a identidade de espécies foi mais relevante no funcionamento das comunidades. Valores de produtividade e eficiência mais elevados foram encontrados para Sargassum muticum. Por outro lado, Bifurcaria bifurcata parece ser a espécie com um desempenho global inferior. Neste trabalho não foram detetados os efeitos da riqueza especifica e do Evenness sugeridos na bibliografia. Provavelmente a aplicação de desenhos experimentais mais longos permitirão estabelecer interações positivas e reduzir a prevalência de grandes efeitos de identidade nas espécies.. Palavras chave: Biodiversidade, Riqueza Específica Evenness, Productividade, Comunidades macroalgas TABLE OF CONTENTS 1 INTRODUCTION ..................................................................................................................... 1 2 MATERIAL AND METHODS ................................................................................................. 4 2.1 Synthetic assemblages construction and experimental design ................................ 4 2.2 Incubation procedures and Ecosystem functioning surrogates ................................ 8 2.3. Statistical analyses ....................................................................................................... 10 3. RESULTS .............................................................................................................................. 11 3.1. Functional performance of single species assemblages ........................................ 11 3.2. Functional performance of multiple species assemblages: Richness, Evenness and Identity effects. .............................................................................................................. 12 3.3. Functional performance of multiple species assemblages: Overyielding ............ 13 3.4. Functional performance of multiple species assemblages: Truly significant predictors ............................................................................................................................... 15 4.DISCUSSION AND CONCLUSSIONS .............................................................................. 17 5.REFERENCES ...................................................................................................................... 20 FCUP | 5 The functional consequences of the biodiversity: Experimental studies with intertidal communities Figure 2.pictures taking during the process of building our synthetic assemblages We built 96 synthetic communities in quadrates with an area of 196 cm2. To assemble the communities, small groups of fronds were secured with small cable ties to a plastic 5 mm mesh in a way to keep fronds upright. Groups of fronds were regularly distributed throughout the mesh with a distance among frond groups of around 1 cm. Seaweeds and plastic mesh were them secured to a PVC plate to increase strength and ensure negative buoyancy. Once assembled, plates were submerged in a 300 l seawater outdoor sheltered tank set with aeration to create turbulence and temperature controlled at 16ºC using Aqua Medic® Titan 2000 and Teco TR 10-coolers units. To avoid nutrient limitation, seawater was enriched every two days by adding inorganic N (NaNO3) and P (NaH3PO4 ) to a final concentration of 50μM N and 5μM P. Salinity was regularly monitored and tanks were regularly refilled with freshwater to compensate for water evaporation. Figure 1 Diagram of the experiment designed to separate the effects of species richness, identity and evenness (distribution of biomass) of macroalgal in our synthetic assemblages. Species that occur at high richness level also occur in treatments with low richness treatments. Dominant species in low evenness treatment are in red. FCUP | 6 The functional consequences of the biodiversity: Experimental studies with intertidal communities Our experiment aimed to unravel the ecosystem functioning consequences of three different components of diversity, namely species richness, species identity and evenness. To do so, we used a similar design to the one proposed by BenedettiCecchi, (2004) considering in the experimental design the three components of diversity cited above: i) Species richness with two levels, 2 species and 4 species, ii) Evenness also with two levels (low and high) and iii) Identity, this factor have 4 levels for each species richness; i.e. we included four different combinations of 2 species and 4 species. Species were randomly selected to create the different Species richness and identities. Species richness (SR) levels were built by creating assemblages with 2 species and with 4 species selected from the initial pool of eight species. Initially we created four different assemblages of 2 species assemblages randomly selecting species from the pool of 8 species. Them we created 4 species assemblages adding 2 new randomly selected species to the previous 2 species assemblages. In this way, we were able to include all the species present in the high species richness treatment also in the low species richness assemblages, preventing any effect confounding of strong identity effects with diversity ones (Bulling et al 2006; Stachowicz et al 2007). Thus, by selecting our assemblages randomly we were able to define an identity random factor which was nested in the factor species richness. We created 4 assemblages replicates per identity. Evenness treatment was implemented by considering two different ways of distribution of biomass among species in the assemblages. Therefore, high evenness assemblages have equal amount of biomass per specie, while low evenness had a “dominant” species which presented a higher biomass than the other species in the assemblage. Dominant species were selected randomly and corresponded to Bifurcaria bifurcata, Osmundea pinnatifida, Mastocarpus stellatus and Sargassum muticum. Evenness was estimated using Shannon diversity index, following (Camargo, 1995) for the biomass data. Figure 3 Evenness treatment D 4 Species high evenness A 2 Species low evenness B 2 Species high evenness C 4 Species low evenness FCUP | 7 The functional consequences of the biodiversity: Experimental studies with intertidal communities . Overall biomass in the plates was 100 g of FW seaweeds. This is within the range of FW biomass in rock-pools with erected seaweeds in the collecting area (personal observation). In plates with 2 species and high evenness, each species was represented by 50 g of FW biomass. In the case of low evenness the dominant species had 75 g FW and the other 25 g FW biomass. For the 4 species assemblages, in the case of high evenness each species included 25 g FW while in the low evenness the dominant species contributed with 62.5 g FW and the other three species with 12.5 g FW each. Wet weights were determined after removing excess water from the algae using a salad spinner (Bruno et al., 2005) Additionally, we built single species assemblages to allow assessment of overyielding (D. U. Hooper & Dukes, 2003b). On overall, a total of 96 assemblages were created. To gain further insight into the mechanisms underlying community attribute effects on ecosystem functioning, we calculated the overyielding for Gross primary productivity, Respiration and Net Primary Productivity. Overyielding allows to recognize the existence of increased biomass production in species mixtures relative to monoculture. Overyielding was estimated as ln(O/E), where O is observed value, and E is expected value (Orwin, et al 2014). Expected values were calculated based on monoculture responses and the relative proportion of each species within the mixed communities Overyielding index(i+j): Log (O(i+j)/E(i+j)) O(i+j) – Observed Primary Productivity (PP) for the assemblage i+j for the corresponding spatial aggregation E(i+j) – Estimated Primary Productivity (PP) for the assemblage i+j for the corresponding spatial aggregation FCUP | 8 The functional consequences of the biodiversity: Experimental studies with intertidal communities 2.2 Incubation procedures and Ecosystem functioning surrogates Productivity-irradiance (P-I) curves were estimated by measuring oxygen fluxes inside a sealed incubation chamber at 7 irradiance levels. The incubation chamber consisted of a 12.5 l Plexiglas chamber partially submersed in a larger, thermo-statically controlled cooling chamber in white PVC, we used a temperature controlled chamber with 7 consecutive light irradiance levels, from 0 μEm-2s-1 (dark period) to 1578 μEm-2s1. Mean ± SE temperature inside the incubation chamber was 16.5± 0.06°C (Aqua Medic® Titan 2000 and Teco TR10). Filtered sea water and the water movement inside the incubation chambers was maintained through a submersible pump (300 l h–1) equipped with diffusers to reduce turbulence. Oxygen concentration variations were measured using a luminescent dissolved oxygen probe connected to a data-logger (Hach® HQ40) that registered a new measurement every 30 s and was continuously monitored. To reduce possible effects of circadian rhythms on algal productivity, incubations were always carried out during daylight hours (between 08:00 and 18:00h) . The irradiance levels facilities which allowed us to measure assemblage respiration and productivity rates at 7 successive and increasing light levels: 0 (dark), 24, 164, 262, 345, 417 and 1578 µE m–2 s–1. Maximum irradiance levels in the chamber were lower than those recorded in the field at sea surface level where, during sunny days in winter, irradiance can reach >2000 µE m–2 s–1 (authors’ pers. obs. using a scalar quantum sensor) (Arenas et al., 2009). The light source in the chamber was composed of sixtyfour 30 W fluorescent tubes (Osram L® 965 Biolux). Irradiance inside the chamber was measured using a sensor (Walz® ULM500 Universal Light Meter). For each P-I incubation, the successive irradiance periods lasted between 20 min, the time necessary for the fluorescent tubes to warm up and the assemblages to reach linear rates of oxygen flux (Migné et al. 2002). All the timing of the light system was controlled Figure 4 Incubation procedures FCUP | 9 The functional consequences of the biodiversity: Experimental studies with intertidal communities using Aqua Medic ® (AT Control System controllers, GmbH, Bissendorf, Germany). The entire set of incubations took around 2:30 h per assemblage. Respiration and productivity were estimated through oxygen fluxes by regressing oxygen concentration (µmol) through time (s-1) during dark and light periods of increasing intensities. Estimations were normalized by biomass and corrected by seawater volume inside the chamber to take into account the different volumes of the boulders. The variables Respiration, Photosynthetic efficiency at low light irradiance (alpha, α) and Light compensation point were measured as surrogates of ecosystem functioning. Respiration of assemblages (mg O² h-¹); corresponded to the oxygen consumption rate during the dark period and we assessed net primary productivity (mg O² h-¹) as the productivity recorded at different irradiance intensities in order to calculate alpha. Both variables were calculated by plotting oxygen concentration over incubation time and fitting a linear regression line to calculate rates of oxygen change. Alpha (α) (mg O² μEm-2s-1), was estimated as the slope of P-I relationship at light-limited irradiances through linear regressions. Gross Primary Productivity where calculated as the sum of NPP and Respiration. Regressions were also used to estimate light compensation point of assemblages, the irradiance level at which respiration rate is equal to photosynthetic rate and net oxygen exchange is zero Figure 5 Example P-I curves and ecosystem functioning surrogates. FCUP | 10 The functional consequences of the biodiversity: Experimental studies with intertidal communities 2.3. Statistical analyses Analysis of variance (ANOVA) was used to test hypotheses involving productivity and all related surrogates. Analyses were done on data collected after 15 and 30 days. GMAV version 5 for Windows was used for computations (Underwood, & Chapman, 1998) Cochran’s test was used to test for homogeneity of variance. Variances were not heterogeneous and data were not transformed. StudentNewman-Keuls procedure was used to make post hoc comparisons among levels of significant terms at alpha p<0.05. All nested factors are displayed in parentheses in the analysis tables. Multiple linear regression models were used to examine simultaneously the influence of species identity, diversity and evenness on the functional performance of the assemblages (i.e. GPP, NPP, Respiration and Alpha). We used linear models to analyze causality between predictors and functional responses. Therefore once each full multiple regression model was set, we proceeded to select those predictors with a truly significant effect on the response variable. Hierarchical partitioning, is particularly suitable for this task (Chevan, A., 1991). Hierarchical partitioning compares all possible models in a multiple regression setting and determines the independent capacities of the predictive variables to explain the patterns of variability in the corresponding response variable. For each predictor, its independent explanatory power on the dependent variable is characterized with an index ‘‘I,’’ which reflects the independent contribution of the predictor to the variance explained by the models. Variables that independently explained a larger proportion of variance than by chance were identified using randomization tests. For each predictor, the observed contribution to the explained variance (I) was compared to the distribution of a population of Is of 1000 randomizations of the data matrix. Significance was accepted at the upper 95% confidence limit. Hierarchical partitioning procedures were estimated using the hierarchical partitioning software for the public domain package R (Walsh & Nally, 2003) FCUP | 11 The functional consequences of the biodiversity: Experimental studies with intertidal communities 3. RESULTS 3.1. Functional performance of single species assemblages Assemblages with just one single species allows to characterize the functional performance of each species under the same density conditions occurring at multiple species assemblages. For all the four functional parameters estimated throughout incubations (GPP, Respiration, NPP and alpha) significant identity effects were detected (ANOVA, p<0.05 in all the cases). Consistently higher productivity and efficiency values were found for Sargassum muticum. Conversely, Bifurcaria bifurcata seemed to be the species with lower overall performance. Figure 6 Mean (±SE, n=4) of the functional measures for the eight species utilized in our experiment. A) Gross primary productivity, GPP. B) Respiration rate (Resp). C) Net primary productivity (NPP) and D) Alpha, i..e assemblages efficiency under light restricting conditions. All measures refer to the whole assemblage. Bars sharing same letter did not differ in ANOVA test at p-level 0.05. FCUP | 12 The functional consequences of the biodiversity: Experimental studies with intertidal communities 3.2. Functional performance of multiple species assemblages: Richness, Evenness and Identity effects . When we measured the functional performance of our assemblages after the adjustment period, i.e. two weeks after the start of the experiment, we found that neither species richness, evenness nor their interactions drove functional responses in our synthetic assemblages. Species identity within the synthetic assemblages seemed to consistently be the most of the relevant effect on assemblages functioning (see table 1, Figure 2, a, b, c and d). a) GPP b) RESP c) NPP d) Alpha df effect df error F p-level F p-level F p-level F p Diversity 1 6 0.06 0.8088 0.19 0.6792 0.04 0.8461 0.03 0.8591 Evenness 6 48 0.88 0.3856 0.28 0.6161 0.82 0.3991 1.16 0.3237 Identity(Di) 1 6 7.29 <0.001 4.99 0.0005 6.40 <0.001 5.22 0.0003 DiXEv 1 6 0.06 0.8198 0.11 0.7541 0.12 0.7435 0.10 0.7675 EvXId(Di) 6 48 1.52 0.1929 1.25 0.2972 1.61 0.1643 1.97 0.0887 Table 1 Summary of ANOVA analyses of the effect of the experimental treatments for the four functional variables: A)Gross primary productivity, GPP. B) Respiration rate (RESP). C) Net primary productivity (NPP) and D) Alpha. Numbers in bold indicate significant effects. FCUP | 13 The functional consequences of the biodiversity: Experimental studies with intertidal communities Figure 7 Mean (±SE, n=4) of the Identity source ID1 Bifurcaria. ID2 Osmundea ID3 Mastocarpus ID4 Sargasum. Different lowercase letters indicate differences between groups FCUP | 14 The functional consequences of the biodiversity: Experimental studies with intertidal communities 3.3. Functional performance of multiple species assemblages: Overyielding When we examined the effect of the different treatments on the overyielding in our assemblages no significant effects where observed in Gross Primary Productivity or Respiration but in the overyielding for Net Primary Productivity we observed significant differences in the Evenness x Identity interaction. These differences originated by the apparently low performance of the assemblages with ID 3 in low evenness assemblages. This identity corresponded to assemblages where the dominant species was Mastocarpus stellatus and included also C. teddi for the 2 spp assemblages plus B. bifurcata and C. acicularis in the 4 spp assemblages These assemblages produced less than expected showing a very negative value of overyielding, i.e. probably a significant underyielding (negative overyielding value). Table 2 Summary of ANOVA analyses of the effect of the experimental treatments for overyielding effect in: a) gross primary productivity, GPP. b) Respiration rate (RESP) and c) Net primary productivity (NPP). Numbers in bold indicate significant effects. a) GPP b) RESP c) NPP df effect df error F p-level F p-level F p-level Diversity 1 6 0.16 0.7036 4.21 0.0860 1.84 0.2242 Evenness 6 48 4.70 0.0732 3.28 0.1201 0.37 0.5660 Identity(Di) 1 6 1.50 0.1992 1.43 0.2219 4.38 0.0013 DiXEv 1 6 1.88 0.2195 1.81 0.2276 0.60 0.4667 EvXId(Di) 6 48 0.90 0.5038 1.14 0.3526 11.58 <0.001 Figure 8 Mean (±SE, n=4) Interaction Evenness-Identity combination ID1 Bifurcaria. ID2 Osmundea ID3 Mastocarpus ID4 Sargasum. Different lowercase letters indicate differences between groups. FCUP | 21 The functional consequences of the biodiversity: Experimental studies with intertidal communities Bruno, J. F., Boyer, K. E., Duffy, J. E., Lee, S. C., & Kertesz, J. S. (2005). Effects Of Macroalgal Species Identity And Richness On Primary Production In Benthic Marine Communities. Ecology Letters, 8(11), 1165–1174. Bruno, J. F., Lee, S. C., Kertesz, J. S., Carpenter, R. C., Long, Z. T., & Duffy, J. E. (2006). Partitioning The Effects Of Algal Species Identity And Richness On Benthic Marine Primary Production. Oikos, 115(1), 170–178. Retrieved from <Go to ISI>://WOS:000240998300017 Bruno, J. F., Stachowicz, J. J., & Bertness, M. D. (2003). Inclusion Of Facilitation Into Ecological Theory. Trends In Ecology & Evolution, 18(3), 119–125. Bulling, M. et al, White, P., Raffaelli, D., & Pierce, G. (2006). Using Model Systems To Address The Biodiversity-Ecosystem Functioning Process, 311, 295–309. Camargo, J. A. . (1995). On Measuring Species Evenness And Other Associated Parameters Of Community Structure. Oikos, 74: 538-542. 1995. Cardinale, B. J., Duffy, J. E., Gonzalez, A., Hooper, D. U., Perrings, C., Venail, P., … Naeem, S. (2012). Biodiversity Loss And Its Impact On Humanity. Nature, 486(7401), 59–67. Cardinale, B. J., Nelson, K., & Palmer, M. a. (2000). Linking Species Diversity To The Functioning Of Ecosystems : On The Importance Of Environmental Context. Oikos, 91(March), 175– 183. Cardinale, B. J., Srivastava, D. S., Duffy, J. E., Wright, J. P., Downing, A. L., Sankaran, M., & Jouseau, C. (2006). Effects Of Biodiversity On The Functioning Of Trophic Groups And Ecosystems. Nature, 443(7114), 989–992. Cardinale, B. J., Wright, J. P., Cadotte, M. W., Carroll, I. T., Hector, A., Srivastava, D. S., … Weis, J. J. (2007). Impacts Of Plant Diversity On Biomass Production Increase Through Time Because Of Species Complementarity. Proceedings of the National Academy of Sciences of the United States of America, 104(46), 18123–18128. Chevan, A., and M. S. (1991). Hierarchical partition, 376–379. Duffy, J. E., Cardinale, B. J., France, K. E., McIntyre, P. B., Thébault, E., & Loreau, M. (2007). The Functional Role Of Biodiversity In Ecosystems: Incorporating Trophic Complexity. Ecology Letters, 10(6), 522–38. Fridley, J. D., Carolina, N., & Hill, C. (2001). FORUM FORUM FORUM The Influence Of Species Di versity On Ecosystem Productivity : How , Where , And Why ?, 3. Gamfeldt, Lars. Hillebrand, H. (2008). Multiple Functions Increase The Importance Of Biodiversity For Overall Ecosystem Functioning, 89(5), 1223–1231. Hillebrand, H., & Matthiessen, B. (2009). Biodiversity In A Complex World: Consolidation And Progress In Functional Biodiversity Research. Ecology Letters, 12(12), 1405–19. Hooper, D. U. (1998). The Role Of Complementarity And Competition In Ecosystem Responses To Variation In Plant Diversity. Ecology 79(2): 704-719. FCUP | 22 The functional consequences of the biodiversity: Experimental studies with intertidal communities Hooper, D. U., Adair, E. C., Cardinale, B. J., Byrnes, J. E. K., Hungate, B. a, Matulich, K. L., O’Connor, M. I. (2012). A Global Synthesis Reveals Biodiversity Loss As A Major Driver Of Ecosystem Change. Nature, 486(7401), 105–8. Hooper, D. U. and V. (1998). Effects Of Plant Composition And Diversity On Nutrient Ciclyng. Ecological Monographs 68(1): 121-149. Hooper, D. U., & Dukes, J. S. (2003a). Overyielding Among Plant Functional Groups In A LongTerm Experiment. Ecology Letters, 7(2), 95–105. Hooper, D. U., & Dukes, J. S. (2003b). Overyielding Among Plant Functional Groups In A LongTerm Experiment. Ecology Letters, 7(2), 95–105. Huston, M. a. (1997). Hidden Treatments In Ecological Experiments: Re-Evaluating The Ecosystem Function Of Biodiversity. Oecologia, 110(4), 449–460. Kirwan, L., Lüscher, a., Sebastià, M. T., Finn, J. a., Collins, R. P., Porqueddu, C., … Connolly, J. (2007). Evenness Drives Consistent Diversity Effects In Intensive Grassland Systems Across 28 European Sites. Journal of Ecology, 95(3), 530–539. Kraufvelin, P., Bonsdorff, E., Lindholm, A., Kirkerud, L. A., & Pedersen, M. F. (2010). Biomass, Diversity And Production Of Rocky Shore Macroalgae At Two Nutrient Enrichment And Wave Action Levels. Marine Biology, 157(1), 29–47. Loreau, M., Naeem, S., & Inchausti, P. (2002). Biodiversity And Ecosystem Functioning: Synthesis And Perspectives. Biodiversity and Ecosystem Functioning: Synthesis and Perspectives, xii + 294 pp. Maestre, F. T., Castillo-Monroy, A. P., Bowker, M. a., & Ochoa-Hueso, R. (2012). Species Richness Effects On Ecosystem Multifunctionality Depend On Evenness, Composition And Spatial Pattern. Journal of Ecology, 100(2), 317–330. Mcgrady-steed, J., Harris, P. M., & Morin, P. J. (1997). Biodiversity Regulates Ecosystem Predictability, 390(November). Middelboe, a L., & Binzer, T. (2004). Importance Of Canopy Structure On Photosynthesis In SingleAnd Multi-Species Assemblages Of Marine Macroalgae. Oikos, 107(2), 422–432. Retrieved from Mouillot, D., & Mouquet, N. (2006). Species Richness Peaks For Intermediate Levels Of Biomass In A Fractal Succession With Quasi-Neutral Interactions. Oikos, 115(2), 349–357. Mulder, C. P. H., Dimitrakopoulos, P. G., Hector, A., & Schmid, B. (2004). Species Evenness And Productivity In Experimental Plant Communities, 1(February). Murphy, G. E. P., & Romanuk, T. N. (2014). A Meta-Analysis Of Declines In Local Species Richness From Human Disturbances. Ecology and Evolution, 4(1), 91–103. Naeem, S. (2002). Ecosystem Consequences Of Biodiversity Loss :, 83(6), 1537–1552. FCUP | 23 The functional consequences of the biodiversity: Experimental studies with intertidal communities Orwin, K. H., Ostle, N., Wilby, A., & Bardgett, R. D. (2014). Effects Of Species Evenness And Dominant Species Identity On Multiple Ecosystem Functions In Model Grassland Communities. Oecologia, 174(3), 979–92. Reiss, J., Bridle, J. R., Montoya, J. M., & Woodward, G. (2009). Emerging Horizons In Biodiversity And Ecosystem Functioning Research. Trends in Ecology & Evolution, 24(9), 505–14. Impact Of The Invasive Seaweed Sargassum Muticum (Phaeophyta) On An Intertidal Macroalgal Assemblage. Journal of Phycology, 41, 923– 930. Stachowicz. (2008). Diversity Enhances Cover And Stability Of Seaweed Assemblages : The Role Of Heterogeneity And Time, 89(11), 3008–3019. Stachowicz, J., & Byrnes, J. (2006). Species Diversity, Invasion Success, And Ecosystem Functioning: Disentangling The Influence Of Resource Competition, Facilitation, And Extrinsic Factors. Marine Ecology Progress Series, 311, 251–262. Stachowicz, J. J., Bruno, J. F., & Duffy, J. E. (2007). Understanding The Effects Of Marine Biodiversity On Communities And Ecosystems. Annual Review of Ecology, Evolution, and Systematics, 38(1), 739–766. Stevens, M. H. H., & Carson, W. P. (2001). Phenological Complementarity, Species Diversity, And Ecosystem Function. Oikos, 92(2), 291–296. Stirling, G., & Wilsey, B. (2001). Empirical Relationships Between Species Richness, Evenness, And Proportional Diversity. The American Naturalist, 158(3), 286–99. Thompson, R., & Starzomski, B. M. (2006). What Does Biodiversity Actually Do? A Review For Managers And Policy Makers. Biodiversity and Conservation, 16(5), 1359–1378. Underwood, A. J., Chapman, M. G., Underwood, J., & Chapman, G. (1998). A Method For Analysing Scales Of Variation In Composition Of Assemblages. Oecologia (Berlin), 117, 570–578. Van Ruijven, J., & Berendse, F. (2005). Diversity-Productivity Relationships: Initial Effects, LongTerm Patterns, And Underlying Mechanisms. Proceedings of the National Academy of Sciences of the United States of America, 102(3), 695–700. Vaz-Pinto, F., Olabarria, C., & Arenas, F. (2014). Ecosystem Functioning Impacts Of The Invasive Seaweed Sargassum Muticum (Fucales, Phaeophyceae). Journal of Phycology, 50(1), 108– 116. Walker, M. D., Wahren, C. H., Hollister, R. D., Henry, G. H. R., Ahlquist, L. E., Alatalo, J. M., … Wookey, P. a. (2006). Plant Community Responses To Experimental Warming Across The Tundra Biome. Proceedings of the National Academy of Sciences of the United States of America, 103(5), 1342–6. Walsh, A. C., & Nally, R. Mac. (2003). Package “hier.part”, 1–12. FCUP | 24 The functional consequences of the biodiversity: Experimental studies with intertidal communities Wardle, D. a. (1999). Is “ Sampling Effect ” a Problem for Experiments Investigating Is “ sampling effect ” a problem for experiments investigating biodiversity - ecosystem function relationships ?, 87(2), 403–407. Wilsey, Brian J. Potvin, C. (2000). Biodiversity and Ecosystem Functioning: Importance of species evenness in an old field.