Lyons et al. 2016

Holocene shifts in the assembly of the plant and animal communities implicate human impacts

S. Kathleen Lyons1, Kathryn L. Amatangelo2, Anna K. Behrensmeyer1, Antoine Bercovici1, Jessica L. Blois3, Matt Davis1,4, William A. DiMichele1, Andrew Du5, Jussi T. Eronen6, J. Tyler Faith7, Gary R. Graves8,9, Nathan Jud10,11, Conrad Labandeira1,12,13, Cindy V. Looy14, Brian McGill15, Joshua H. Miller16, David Patterson5, Silvia Pineda-Munoz17, Richard Potts18, Brett Riddle19, Rebecca Terry20, Anikó Tóth1, Werner Ulrich21, Amelia Villaseñor5, Scott Wing1, Heidi Anderson22, John Anderson22,
Donald Waller23 & Nicholas J. Gotelli24

Summarized by Altangerel Tsogtsaikhan

Background:  Exploring the hitten effects and mechanisms of how ecological communities’ assemblage are crucial to making predictions of the effects of climate change. Recent work reported that the co-occurrence of species pairs are getting less and less than how it would be expected by random chance. Chronological details of how this co-occurrence structure by change is still unknown. The current study assesses the changes in plant and animal community organizations over geological time (300 million years) with quantification of 359,896 unique taxon pairs co-occurring in 80 assemblages categorizing the aggregation or segregation.

Questions: how are plant and animal communities organized, and does their structure change through time? 

-Do the patterns of species segregation that characterize modern assemblages also hold in the fossil record, or is the present different?

-If whether the non-random species associations of plant and animal assemblages over the past 300 million years are dominated by segregated or aggregated species pairs? 

-Why are species associations so different in fossil versus modern assemblages?

Methods: Plant datasets arranging from 307 million years ago to present including taxon presence and absence across multiple localities in different time. Also, 80 fossil data (38 mammals and 42 plants) and recent assemblage data from North America and Africa were used. Mammal dataset ranged from 21.4 ma. to present.

Each dataset was compared to a null’ assemblage generated by randomization. 39 modern communities were analyzed and compared.

Detecting of non-random species pairs: using binary presence-absence matrix for each taxon. First, the calculated C score was found.

0.0 (aggregation: maximal co-occurrence of both species)

1.0 (segregation: minimal co-occurrence of both species)

PAIRS calculates C score for each pair of species.

Next, the p-value was estimated for association with each species pair by a randomization test.

Weighted Loess regression. A Loess smoothing line was created with the stat smooth function in the R package ggplot2 version 1.0.0 (ref. 37) using default parameters.

Analysis of climate variability impacts: percentage of aggregated species pairs. Last 65 million years of assemblage dataset was used (European Project for Ice Coring in Antarctica).

Individual Evolution of Terrestrial Ecosystems Program (ETE) data set was used.

Breakpoint analysis: a maximum likelihood approach to estimate the breakpoint time (sharper decline in aggregated species in pairs).

Findings: 87-100% fossil data sets were random taxon pairs. 62 out of 80 assemblages showed significant associations that are stronger than the null model which is different than the modern mainland assemblages (most significant associations in the fossil record are aggregated in positive associations which is consistent with last 300 million years of fossil diverse assemblages include mammals, plant macrofossils, and pollen from all other continents. Around 6000 years ago (beginning of Holocene), there was a significant temporal trend towards a greater proportion of segregated species pairs were found. It is pretty similar to the modern assemblages. 64% of significant pairs were aggregated before the breakpoints which dropped to 37% after the breakpoints. A significant decrease in the percentage of positive associations were found in the Pleistocene-Holocene transition (11.700 years ago) indicating the probable human activity.

Thoughts: this is an important research for assessing macroscale pattern of community structure and their specific associations in different time scale to compare the natural versus human impact. For me it is interesting to see the time 6000. Some religious documents claim that this time as the beginning of the life formation. I wonder it has something to do with the socialized and structured human behavior. Also, I know that the Holocene climate stability is pretty unusual and I wonder if it favored the human activities and intensified the decrease in positive associations of ecological assemblages.

Kirch 1996

Kirch PV. 1996. Late Holocene human-induced modifications to a central Polynesian island ecosystem. Anthropology. 93:5296-5300.

Blog Author: Alex Shupinski

Author: 

Patrick Kirch 

EDUCATION

Ph.D., Yale University, 1975

M. Phil., Yale University, 1973

B.A. (cum laude), University of Pennsylvania, 1971

Punahou Academy (Honolulu), 1968

Prehistory and ethnography of Oceania, ethnoarchaeology and settlement archaeology, prehistoric agricultural systems, cultural ecology and paleoenvironmentalism, ethnobotany and ethnoscience, development of complex societies in Oceania.

Abstract

7,000 years of geomorphological and palynological data during the Holocene for Pacific Island (Cook Island) tracking resource exploitation.

2500-1800 were the most significant years from changes and coincided with the arrival of Polynesian people colonizing the island. These human-induced effects included major forest clearance, increased erosion of volcanic hillsides and alluvial deposition in valley bottoms, significant increases in charcoal influx, extinctions of endemic terrestrial species, and the introduction of exotic species.

Introduction

Humans have influenced the land for a long time, it is not a modern phenomenon. 

Perfect ecosystem to study because it is separated from the mainland and has a steady-state equilibra.

Austronesians were a horticultural economy, used marine exploitation, transferred livestock, used fire to clear habitats, used stone, shell, bone, fiber.

Managaia Island, 16-18 million years old along the volcanic chain.  Deep stratigraphic record and strong archeological evidence makes the island very useful.

-Includes 5 vegetative zones on the island, few animal species, possibly colonized by 2.5 kyr.

Methods

25 cores used for stratigraphic records.  

-archeological evidence was obtained from bones (birds, fish, invertebrates), wood charcoal, plant parts and rock shelters. 14C allowed for radiometric dating, 23 bone samples, 40 charcoal samples. 89 samples total

increases in sio2 and A1203, along with free iron, and a decrease in P205. These trends correlate with the pollen evidence indicating removal of climax forest vegetationfrom the central volcanic cone, erosion of the thin organic soil horizon, and exposure of the deeply weathered laterite. Organic content of cores drops in top levels

-increase in erosion and clay deposition

-1.6 kyr signals the removal of indigenous forest vegetation, increase in fernland. Decrease in diversity.  Wood charcoal shows the conversion from native forests to anthropogenic vegetation.

-decrease in bird diversity, introduced invasive species like the Pacific rat, crops

-marine and aquatic changes over 1,000 years: freshwater eels were exploited, decrease in gastropod shell size

Discussion 

Before the arrival of humans the island had high levels of biodiversity, a forested landscape with insignificant amounts of natural fires and only slight erosion. Major environmental changes occurring during the early-to-mid Holocene were lake formation and peat deposition over Pleistocene land surfaces in the valley bottoms, resulting from rapid sea level rise. Polynesian arrival precipitated the following interrelated changes

-burning, erosion, population reduction, introduction of invasive and domestic animals, introduction of anthropogenic vegetation

Humans were fully capable of dramatically altering the environment even before industrialism.

Thoughts 

I really enjoyed this paper because I appreciate tying in all these environmental aspects to drive home the extent of human impact so early on.  I was shocked by the rate of change in such a short period of time even after reading many other papers similar to this.  We used the evidence of this paper to argue in a debate about recognizing the Anthropocene against the idea that by 1945 we have not made enough of a stratigraphic impact to be recognized as a new epoch.

Dornelas et al. 2014

Assemblage Time Series Reveal Biodiversity Change but Not Systematic Loss

Dornelas et al. 2014. Science 344: 296-299

Blog by Willow Guy

Authors

Maria Dornelas

            Reader at U. St. Andrews, UK.

My research focuses on quantifying biodiversity and understanding the processes that shape it. I often work on tropical systems and specifically coral reefs, but I also work with tropical freshwater fish, mangrove crabs and plants for example, as I am more question-driven that organism-driven. I like to combine ecological theory, synthesis of existing data, and fieldwork in my research, and most of the research questions I’m interested in fall under the disciplines of community ecology, macroecology and biogeography. I tend to work on intermediate spatio-temporal scales (that is communities and networks of communities over time-scales of years to tens of years).

Nicholas J. Gotelli

            Professor at U. Vermont

My research addresses basic questions about the organization of animal and plant communities. What are the forces that determine the species composition and abundance of natural assemblages? How do competition and predation affect local community structure? What are the biotic and abiotic factors that control population growth and the risk of extinction?

Brian McGill

            Professor at U. Maine

I seek to understand the patterns and processes controlling the distribution and abundance of organisms at medium to large scales to lead to more predictive theories of how distribution and abundance will change under anthropogenic global change (especially climate change and landcover change).

Intro

There are increasing numbers of threatened species across the globe, but most of this data comes from local analyses.

Goal: to quantify and assess global patterns of temporal change in species diversity

Background

α diversity- diversity at a site

β diversity- diversity overlap between sites

Temporal β diversity- here is a measure of diversity overlap between the same site at different times. Treating site 1 at time A as different than site 1 at time B.

Methods

100 time series (1 time series= collections of data made at one site in different years= a time progression of community change)

Measure α diversity at each time slice and find the slopes of the lines for each community

Measure temporal β diversity with similarity indices 

Results/Discussion

α diversity- there are variations within sites, but no global pattern of change in α diversity

This means that sites around the globe generally have the same number of species in them across time even though they vary locally

-there is no significant difference between marine and terrestrial species

-When sorted by taxonomic group, plants have a slightly positive slope indicating they have, on average, more species in a site today

-When sorted by climatic zone, temperate sites have a positive trend. Tropical sites were nonsignificant and global trends were significantly negative.

This means that temperate sites have more species in them today even though globally there are fewer species.

temporal β diversity- communities exhibit a long-term negative trend in similarity

This means that a community sampled in 1850 has significantly different species in it than the same community sampled today.

Although turnover is expected, this rate of turnover is much more pronounced than expected.

            -Globally, β diversity measures are increasing regardless of sorting

This means that the same species are now found in more sites around the globe =homogenization!

Conclusions

Local and regional assemblages are not losing numbers of species, but numbers of different species. This happens through substitution of species at a site. Communities are becoming more homogenous. 

            “Assemblages are undergoing biodiversity change, but not systematic biodiversity loss”

Thoughts

I thought this was a really neat way to look at this- treating a community at different times like a completely separate community was an interesting way to examine β diversity. I like that homogenization was kind of a surprise result. I got looking at the trends and puzzling over why, then they hit me with the homogenization hypothesis. Wow! I do think they could have improved their climatic analysis, though. Looking at their map, most series fall in the temperatre-tropical and few fall as just tropical and I think that could have influenced how they viewed some of their trends, but not the results as a whole.

Gonzalez et al. 2016

Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity

Authors: Andrew Gonzalez, Bradley J. Cardinale, Ginger R. H. Allington, Jarrett Byrnes, K. Arthur Endsley, Daniel G. Brown, David U. Hooper, Forest Isbell, Mary I. O’Connor, and Michel Loreau. 2016. Ecology97(8): 1949 – 1960.

Blog author: Maria Goller

First author bio: Andrew Gonzalez

Professor at McGill University

His lab focuses on causes and consequences of changes in biodiversity. They translate their research into conservation policy and are particularly interested in retaining ecological connectivity in cities.

Twitter handle is @bio_diverse

Second author bio: Bradley Cardinale

Professor at University of Michigan

Director of the Cooperative Institute for Great Lakes Research, CIGLR

He uses modeling, meta-analyses, and observational research to look at how human behavior impacts biodiversity.

Overview

Earth is losing many species incredibly quickly.

Biodiversity is decreasing but it is unclear what local trends are.

            Locally, species richness varies with human impact.

            Locally, humans can increase diversity (introducing new species, etc...).

This paper is a direct critique of Velland et al. (2013) and Dornelas et al. (2014), who argued that local biodiversity is remaining the same (species turnover may occur, but total richness is constant). 

These authors wanted to know whether the findings of these two papers are representative of global trends in biodiversity. 

They quantified three potential areas of bias in the two meta-analyses.

1) Quantified spatial bias

Created maps of human impact across globe using various impact databases

Randomly sampled same number of locations as used in each paper's dataset, did this 1,000 times, then looked at spatial bias of their studies.

Caveat: human impact maps weren't created to show impact on biodiversity specifically

Spatial bias of both studies

            V. et al. study focused on US and EU => underrepresentation of tropics, boreal forest, tundra, desert

                        Overrepresentation of forests now recovering from logging

            D. et al. study focused on only one of the oceans (North Atlantic), but did include the most heavily impacted areas based on their maps

RESULTS: studies limited in scope to specific areas, ignoring areas of major changes in human impact, and also focused on recovering habitats

2) Quantified temporal bias

Analyses based on short time scales do not accurately reflect changes to diversity

Used the datasets and did a linear regression looking at the effect of study duration on biodiversity decrease => excluding long studies underestimates diversity loss

They argue this is because "extinction debt" may be "repaid" only after many years (local extinctions take time)

3) Quantified post-disturbance bias

Studies often include species richness measures AFTER the ecosystem has begun to recover, so overall it seems that fewer species were lost

When they removed post-disturbance categories, significant negative effect on richness

Take-away: 

Richness is decreasing locally

Scientists should be careful about applying their findings on different scales

Tucker at al. 2018

Moving in the Anthropocene: Global reductions in terrestrial mammalian movements

Blog author: Devra Hock

Author:

Marlee A Tucker: Senckenberg Biodiversity and Climate Research Centre, Senckenberg Gesellschaft für Naturforschung, 60325 Frankfurt (Main), Germany

            Post-doctoral researcher in movement ecology at the Senckenberg Biodiversity and Climate Research Centre and Goethe University, Frankfurt, Germany

            PhD at Evolution and Ecology Research Centre at the University of New South Wales, Australia

            

            Research Interests: Aim to examine animal movement patterns and behaviors from a macroecological perspective. More broadly, interested in large scale patterns in ecology, biogeography and evolution that can aid our understanding of species vulnerability to changing environments that can be utilized for conservation. This includes global patterns in species richness, species extinction risk, energetics and allometric scaling.

Summary/Main Points:

1. Main Question:

            Background— Earth’s surface has been modified 50-70% by human activities, causing changes in biodiversity and ecosystem functions. Human footprint is impacting loss of habitat and biodiversity and how animals move through fragmented and disturbed habitats. Previous research on the extent of animal movements and how they are affected by anthropogenic impacts on landscapes has been done in local geographic regions or within single species. These studies display a decrease in animal movements as a result of habitat fragmentation, barrier effects, or resource changes. Only a few studies reporting animal movements increasing. 

            Main Questions— Conducted a global comparative study of how the human footprint affects movements of terrestrial nonvolant mammals. For each mammalian individual, locations were annotated with the Human Footprint Index. Also included other covariates that are known to influence mammalian movements: environments with lower productivity, body size, dietary guild. 

2. Methods: 

            Human Footprint Index—an index with a global extent that combines multiple proxies of human influence: the extent of built environments, crop land, pasture land, human population density, nighttime lights, railways, roads, and navigable waterways. HFI ranges from 0 (natural environments) to 50 (high-density built environments)

            Normalized Difference Vegetation—well-established, satellite-derived measure of resource abundance for both herbivores and carnivores

            Calculated displacements as the distance between subsequent GPS locations of each individual at nine time scales ranging from 1 hour to 10 days. For each individual at each time scale, calculated the 0.5 and 0.95 quantile of displacement. Examine the effect of human footprint on both the median and long-distance movements for within-day movements (1 hr time scale) up to longer time displacements of more than 1 week (10 day). 

            Used linear mixed-effects models that accounted all covariates, taxonomy, and spatial autocorrelation

3. Results:

            Found strong negative effects of the human footprint on median and long-distance displacements of terrestrial mammals.

            Displacements of individuals across species living in areas of high footprint were shorter than displacements of individuals in low footprint by as much as a factor of 3.

            Median displacements for carnivores over 10 days were 3.3km in areas of high footprint versus 6.9 km in areas of low footprint

            Maximum displacements for carnivores at 10 days averaged 6.6 km in areas of high footprint versus 21.5 km in areas of low footprint. Effect significant on all temporal scales with 8 hrs or more between locations.

            Effect not significant at shorter time scales, suggesting human footprint affects ranging behavior and area over longer time scales, rather than altering individual travel speeds

Human footprint index was separated into two components: the individual behavioral effect represented by individual variability of HFI relative to the species mean, and the species occurrence effect as the mean HFI for each species. 

Results indicate behavioral as well as species effects. Significant behavioral effect on median displacements and on long-distance displacements at most time scales were observed. Species occurrence effect was only significant over longer time scales. 

Body mass, dietary guild, and resource availability were also related to movement distances. Larger species traveled farther than smaller species. Also, a negative relationship between resource availability and displacement, such that movements were on average shorter in environments with higher resources. Carnivores traveled on average farther per unit time than herbivores and omnivores. For all variables, effects were significant across time scales longer than 8 hrs for both median and long-distance displacements.

4. Discussion/Conclusion:

            Reduction of mammalian movements in areas of high HFI stems from two nonexclusive mechanisms: 1) movement barriers such as habitat change and fragmentation, and 2) reduced movement requirements attributable to enhanced resources. Both mechanisms vary responses across populations or species, acting together on single individuals or populations. 

            Consequences of reduced vagility affect ecosystems regardless of underlying mechanisms and go beyond the focal individual themselves. Animal movements are essential for ecosystem functioning because they act as mobile links and mediate key processes such as seed dispersal, food web dynamics, and metapopulation and disease dynamics. 

            The global nature of reduced vagility across mammalian species that is demonstrated in the paper suggests consequences for ecosystem functioning worldwide. 

Questions/Comments:

             I thought this research was presented very clearly. The graphs are also very illustrative of the patterns in the data, especially the two groups visible in the Human Footprint Index and the Normalized Difference Vegetation Index. 

            One thing I would have liked to see discussed is the relationship between Human Footprint Index and the Normalized Difference Vegetation Index. HFI measures the level of human impact on a variety of factors, while the NDVI looks at level of productivity/resource abundance. Very similar patterns are seen with animal displacement and I wonder what everyone thinks about the relationship between these two indices.  

Ceballos et al. 2015

Ceballos, G. 2015. Accelerated modern human-induced species losses: Entering the sixth mass extinction.

Blog Author:Angel Sumpter

Paper Author: Gerardo Ceballos

●      Undergraduate degree in Biology from the Metropolitan Autonomous University (UAM) Campus Iztapalapa, Mexico

●      Master's degree in Ecology from the University of Wales under the supervision of ecologist John. L. Harper

●      PhD in Ecology from the University of Arizona with Dr. James H. Brown.

●      Has published 124 scientific articles, 39 dissemination articles, 187 book chapters and 31 books

●      Started the Long Term Ecological Research Network Chapter in Mexico

Background/Introduction:

●     At this current rate, valuable ecosystem services are at risk. The dwindling number of diverse species plagues the world with critical environmental problems. With over 1000 bird species extinct within approximately 2000 years, rates grow at an alarming rate over pre-human times, not only in the island tropical Oceania, but all over the world. Records from far back as the 19th century detail more accounts of the various species extinct. Sadly, there is even worry for species not yet extinct due to their direct negative correlation between population level and ecosystem. 

Question:

●      Are modern  rates of  mammal  and vertebrate  extinctions higher  than  the highest empirically  derived  background rates?  

○      (ii) How  have  modern extinction  rates in  mammals  and vertebrates changed  through time? 

○      (iii)  How many  years  would  it have  taken  for species  that  went extinct in  modern  times to  have  been lost  if  the background  rate had  prevailed?

Materials/ Methods

●     The 2014 IUCN Red List was used to compile data on  the  total number of  described  species and  the  number of  extinct  and possibly extinct  vertebrate  species. Modern extinction was calculated in two ways: estimation of a highly conservation modern extinction rate and a highly modern extinction rate. The conservations were compare to each other by assuming the background extinction rate of 2 E/MSY. This ended up with a result of a mass extinction on the way.

Results

●     Modern  rates of  vertebrate  extinction were  much  higher than  a background  extinction rate  of  2 E/MSY.

○     For example it was expected that there would be 9 vertebrate extinctions starting from 1900, instead more than 468 vertebrates have gone extinct.

●     Modern extinction rates have increased greatly and are higher than the background rates. 

○     What should have taken between 800 to 10,000 years (the extinction rate) disappeared in 2 E/MSY.

Discussion

●     The world can be very worried if it continues eliminating any percent of biodiversity. The rates from this analysis show major increase in extinction rates than in natural average rates. It is imperative we focus solely pm species. If things don’t change soon the Earth could be heading towards a sixth mass extinction. Effects of this could take millions of years to rediversify and normalize extinction rates.

Comments

●     I really appreciate how the author had the results at the beginning of the paper. I feel like this author truly did think about his audience because he wrote this paper in the simplest form starting with what I consider the most important part after the introduction.

●     I know that we’ve talk about the sixth extinction but wow.. It never actually clicked until this paper explained how many vertebrates are dying and at what rate. 

Wright et al. 1993

Wright, D. H., Currie, D. J., & Maurer, B. A. (1993). Energy supply and patterns of species richness on local and regional scales. Species diversity in ecological communities: historical and geographical perspectives, 66-74. 

Blog author: Laura Segura-Hernandez

Energy Supply and Patterns of Species Richness on Local and Regional Scales

David H. Wright, David J. Currie, and Brian A. Maurer

David H. Wright:

Retired.

Entomologist; Fish and Wildlife Biologist. U.S. Fish and Wildlife Service

David J. Currie:

Emeritus professor. University of Ottawa.

The goals of Dr. Currie’s researchprogram are: 1) to identify broad-scale patterns in the distribution, abundance and diversity of life; 2) to determine which environmental variables exert the strongest control on those patterns, and 3) to determine how human activities influence them. Recent research focuses on influences of climate, habitat conversion and pesticide use on these properties of natural systems. 

Brian A. Maurer:

 PhD, Wildlife Ecology, University of Arizona 

My interest focuses on the largest spatial and longest temporal scales studied by ecologists.  To understand the importance of processes at geographical scales, it is important to understand how they connect to local scale processes.  Thus, I am interested in modeling population and community dynamics in a geographical context.  I am working with a variety of vertebrate organisms to model how population dynamics and abundance vary from one place to the next within their geographical ranges.  

Introduction

• Species richness varies a lot regarding geography, and at different geographical scales too.
• Species richness gradients are present at local and large scales.
• So,  “Why are there so many species in some places and few in others?”
• There are many proposed explanations regarding this matter, however, in the recent years the one regarding energy supply has gained more attention. This new research has focused on both empirical and theoretical ways, and the results either support a positive species-energy relationship, or a negative one, of the two together.
• A good approach to compile all the evidence concerning this relationship should include: 1. the factors that account for the greatest amount of the natural variability in species richness, 2. the mechanisms behind 1, and 3. the perturbations that alter richness. 
• The authors will cover topics related to these three things in this review, specifically patterns and mechanisms liking species-energy.

A survey of the literature

·     Question: “If one surveys extant studies, what characteristics have been observed to be most strongly correlated with patterns of species richness?

·     The authors have several criteria to select the studies for this. Mainly, they looked for studies that addressed spatial variation of species richness and its relationship to environmental characteristics.

·     Environmental variables most frequently correlated to species richness: mean annual temperature, precipitation, potential and actual evapotranspiration (Table 6.1). 

·     Also, primary productivity measures that show correlation to richness: food availability and limiting-nutrient availability. All these factors would be referred as “energy-related factors”. These showed the highest correlation values.

·     Which variable best predicted richness depend on the organism studied, but the main correlate was usually primary productivity. 

·     Large scale studies showed that measures of water availability and radiant energy were correlated to richness and productivity.

·     Studies in dry areas show that precipitation was correlated to richness and productivity. In wetlands, biomass accumulation (=annual primary productivity) was correlated to richness. In Fresh water, it was the phosphorus supply.  In animals, richness was related to heat.

·     The richness-energy relationship is scale dependent. Globally, richness increases with energy. 

·     This relationship is also dependent on the taxonomic scale: correlations are weaker at the genus or family level, than at the order or class. But this is not statistically significant.

·      Marine systems provide exceptions to the patterns observe for the terrestrial organisms.

·     The correlations between richness and environmental characteristics depended on other factors, such as the increase of quadrant size. This was more pronounced in studies of energy related factors and is also correlated to the geographic scale of the investigation. This shows that measures of energy availability are good predictors of large scale richness, possibly because large scale studies include a greater amount of information.

·      There is a lack of evidence in the literature to support the other highly cited explanations for species richness patterns. Even if there are solid experimental demonstrations of how this factors might affect richness, there is no record of, for example, how habitats with higher predation might contain more or less species. This lack could be due to the difficulties of quantifying biotic interactions and historical influences. However, since energy-related factors accounted in a large proportion to the variation in riches, these other factors must be strongly correlated to energy or explain a small proportion of the richness present. 

·     Conclusion: the most powerful explanatory variable for the spatial variation in species richness is the energy in the environment. Other questions: “Is there a casual link between energy and richness? If so, how does it operate? Why do energy and richness co-vary in different manners at different scales?”

Statistical mechanism of species richness and available energy

• If energy flow is the cause of species richness, this mechanism should act at the individual level as they forage to get energy to survive and reproduce. However, differences between species and in the environment can create large scale variation.
• They developed a model that focus on these ecological features:

◦     Local habitats have many resources

◦     Local habitats differ in the production of energy

◦     Species differ on how they use resources

◦     Species differ in their metabolic requirements

◦     The success/abundance of a species in a habitat is stochastic, and partially related to the production of adequate resources, competition and its metabolic requirements.

◦     There is a regional pool of potential colonist species that is much richer that any local habitat.

From energy acquisition to abundance

• Basically, the authors explain mathematically the number of individuals per patch as a function of the resource energy obtained for each species and the number of energy “bits” required to support one individuals of a particular species.
• They consider that the probability of acquiring energy varies within species and within patches if the environment is not homogeneous.

From local abundance to incidence and local species richness

• Another mathematical explanation. Basically, they propose that local richness can be calculates as the sum of the probabilities that each species is found a that patch. 
• This depends only on the probabilities of the species present. 

From patterns of incidence to regional species richness

• This refers to the total of species present in all the patches in a landscape,
• More math: Same as before, the expected species riches is explained as the sum of probabilities of all independent species within the region, but this time each probability is calculated differently (equation 6.7).
• The variation of energy acquisition depends on each species ability to gain energy. Therefore, patches with some species that dominantly get more energy would have less species and lower richness at the large scale level. 
• Result: heterogeneous environment have more species at the regional level. 
• This effect could soften or reverse negative local effects of energy on richness.

Generalization

• “Local an regional richness are both functions of the incidence probabilities of species in patches”
• This has the assumption that population size is stochastic.
• As mean abundance increase, the probability that a species would be present increases too.
• So, if energy has a positive effect on abundance, the effect of energy on local richness would be positive. “Thus, to the extent that gross energy supply has a positive effect on species abundances, the effect of energy on local species richness will be positive, regardless of the form of the underlying model.”

Enrichment experiments and counterexamples

Enrichment experiments

• These experiments -done mostly by adding P or N to plants or aquatic systems  -  shows that the additional energy increases productivity but it produces a decrease in species richness. This is the “paradox of enrichment”. It is associated with the increase of abundance of a few species that interfere (compete or limit) the surrounding species.
• In terms of niche: adding one nutrient will fevour those species that use that nutrient over the other species that do not require it.
• However there are some considerations and limitations associated with the methods of this experimental designs. Including whether this approach actually mimic natural variation in energy availability: studies are short term, at a small scale. Also, it casts doubts about the applicability of these results to animals.
• However, the paradox of enrichment is real, and these experimental approaches can give useful insights to understand how species use different resources in their natural setting. 

Counterexamples

• Salt marshes: productive habitats with low species. Explanation: contain few species because they present difficult environment to survive and adapt, that isolates them from colonist species too, and are ephemeral so the chances of extinction increase. 
• Ocean floor: large, consistent and not very productive habitat that support lots of species. Proposed explanation: they proposed the same theory than Island Biogeography but replacing are and distance with energy and isolation (physical separation and/or dissimilar environments). Energy should be measured by the energy produced in the whole large area (not per patch). 

Conclusion

• Effects of energy on species richness are common, yet complex and deserve more detailed and systematic approaches.
• They proposed to include in model the energy gained by each species as a way to approach this relationship.
• Regional species-richness patterns tend to be more positive and pronounced than local patterns, as long as the landscape is heterogeneous. This divergence in the patterns at different scales may explain why it has been difficult to find a unified explanation for the mechanisms behind the pattern. 
• There is much to be done and improved, but it is time to include energy as another very likely pattern that might lead to the species richness patterns recorded so far. 

Questions/comments

• I liked how they approached their review. I wonder, however, if they could have go back and check the literature they discarded to see if they found similar pattern than the one they got from the literature and their own models, by maybe using some other analyses, maybe just as a descriptive assessment.
• Given that the counterexamples are all aquatic, I wonder if the patterns they are trying to describe are actually universal of just something that could be explained for terrestrial organisms. This still makes me a bit uncomfortable though: why should we try to find one explanation/mechanism/factor for each pattern and also why should we assume that all patterns are the same for all organisms/environments? As the authors say at the beginning, there might be many causes behind the pattern, and they show that energy could be one of the main factors behind it. But I don’t think the counterexamples should be something bad, it is a reminder that not everything has to be “universal”.